Zbornik 23. mednarodne multikonference INFORMACIJSKA DRUŻBA Proceedings of the 23rd International Multiconference INFORMATION SOCIETY Slovenska konferenca o umetni inteligenci .si Slovenian Conference on Artificial Intelligence .ijs Kognitivna znanost IS Cognitive Science http://is Odkrivanje znanja in podatkovna skladišča - SiKDD Data Mining and Data Warehouses - SiKDD Etika in stroka Professional Ethics 20 13. Mednarodna konferenca o prenosu tehnologij – 13. ITTC 13th International Technology Transfer Conference – 13 ITTC Ljudje in okolje People and Environment Vzgoja in izobraževanje v informacijski družbi Education in Information Society 20 Interakcija človek-računalnik v informacijski družbi Human-Computer Interaction in Information Society Uredili / Edited by Mitja Luštrek, Matjaž Gams, Rok Piltaver, Toma Strle, Jaša Černe, Olga Markič, Dunja Mladenić, Marko Grobelnik, Franci Pivec, Marjan Krisper, Špela Stres, Robert Blatnik, Janez Malačič, Tomaž Ogrin, Uroš Rajkovič, Borut Batagelj, Veljko Pejović, Matjaž Kljun, Vida Groznik, Domen Šoberl, Klen Čopič Pucihar, Bojan Blažica, Jure Žabkar, Matevž Pesek, Jože Guna, Simon Kolmanič 5.–9. oktober 2020 / 5–9 October 2020 Ljubljana, Slovenia INFORMACIJSKA DRUŽBA Zbornik 23. mednarodne multikonference – IS 2020 INFORMATION SOCIETY Proceedings of the 23rd International Multiconference – IS2020 Slovenska konferenca o umetni inteligenci Slovenian Conference on Artificial Intelligence Kognitivna znanost Cognitive Science Odkrivanje znanja in podatkovna skladišča - SiKDD Data Mining and Data Warehouses - SiKDD Etika in stroka Professional Ethics 13. mednarodna Konferenca o prenosu tehnologij – 13. ITTC 13th International Technology Transfer Conference – 13 ITTC Ljudje in okolje People and Environment Vzgoja in izobraževanje v informacijski družbi Education in Information Society Interakcija človek-računalnik v informacijski družbi Human-Computer Interaction in Information Society Uredili / Edited by Mitja Luštrek, Matjaž Gams, Rok Piltaver, Toma Strle, Jaša Černe, Olga Markič, Dunja Mladenić, Marko Grobelnik, Franci Pivec, Marjan Krisper, Špela Stres, Levin Pal, France Podobnik, Duško Odić, Robert Blatnik, Janez Malačič, Tomaž Ogrin, Uroš Rajkovič, Borut Batagelj, Veljko Pejović, Matjaž Kljun, Vida Groznik, Domen Šoberl, Klen Čopič Pucihar, Bojan Blažica, Jure Žabkar, Matevž Pesek, Jože Guna, Simon Kolmanič http://is.ijs.si 5.–9. oktober 2020 / 5–9 October 2020 Ljubljana, Slovenia Uredniki: Mitja Luštrek, Odsek za inteligentne sisteme, Institut »Jožef Stefan«, Ljubljana Matjaž Gams, Odsek za inteligentne sisteme, Institut »Jožef Stefan«, Ljubljana Rok Piltaver, Celtra, d. o. o. in Odsek za inteligentne sisteme, Institut »Jožef Stefan«, Ljubljana Toma Strle, Center za Kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Jaša Černe, Center za Kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Olga Markič, Filozofska fakulteta, Univerza v Ljubljani Dunja Mladenić, Department for Artificial Intelligence, Jožef Stefan Institute, Ljubljana Marko Grobelnik, Department for Artificial Intelligence, Jožef Stefan Institute, Ljubljana Franci Pivec, DOBA fakulteta, Maribor Marjan Krisper, Fakulteta za računalništvo in informatiko, Univerza v Ljubljani Špela Stres, Center za prenos tehnologij in inovacij, Institut »Jožef Stefan«, Ljubljana Levin Pal, Center za prenos tehnologij in inovacij, Institut »Jožef Stefan«, Ljubljana France Podobnik, Center za prenos tehnologij in inovacij, Institut »Jožef Stefan«, Ljubljana Duško Odić, Center za prenos tehnologij in inovacij, Institut »Jožef Stefan«, Ljubljana Robert Blatnik, Center za prenos tehnologij in inovacij, Institut »Jožef Stefan«, Ljubljana Janez Malačič, Ekonomska fakulteta, Ljubljana Tomaž Ogrin, Odsek za anorgansko kemijo in tehnologijo, Institut »Jožef Stefan«, Ljubljana Uroš Rajkovič, Fakulteta za organizacijske vede, Univerza v Mariboru Borut Batagelj, Fakulteta za računalništvo in informatiko, Univerza v Ljubljani Veljko Pejović, Univerza v Ljubljani, FRI, ACM SIGCHI Chapter Bled Slovenia Matjaž Kljun, Univerza na Primorskem, FAMNIT Vida Groznik, Univerza na Primorskem, FAMNIT Domen Šoberl, Univerza na Primorskem, FAMNIT Klen Čopič Pucihar, Univerza na Primorskem, FAMNIT Bojan Blažica, Inštitut Jožef Stefan Jure Žabkar, Univerza v Ljubljani, FRI Matevž Pesek, Univerza v Ljubljani, FRI Jože Guna, Univerza v Ljubljani, FE Simon Kolmanič, Univerza v Mariboru, FERI Založnik: Institut »Jožef Stefan«, Ljubljana Priprava zbornika: Mitja Lasič, Vesna Lasič, Lana Zemljak Oblikovanje naslovnice: Vesna Lasič Dostop do e-publikacije: http://library.ijs.si/Stacks/Proceedings/InformationSociety Ljubljana, oktober 2020 Informacijska družba ISSN 2630-371X Kataložni zapis o publikaciji (CIP) pripravili v Narodni in univerzitetni knjižnici v Ljubljani COBISS.SI-ID=36194819 ISBN 978-961-264-207-5 (epub) ISBN 978-961-264-208-2 (pdf) PREDGOVOR MULTIKONFERENCI INFORMACIJSKA DRUŽBA 2020 Triindvajseta multikonferenca Informacijska družba (http://is.ijs.si) je doživela polovično zmanjšanje zaradi korone. Zahvala za preživetje gre tistim predsednikom konferenc, ki so se kljub prvi pandemiji modernega sveta pogumno odločili, da bodo izpeljali konferenco na svojem področju. Korona pa skoraj v ničemer ni omejila neverjetne rasti IKTja, informacijske družbe, umetne inteligence in znanosti nasploh, ampak nasprotno – kar naenkrat je bilo večino aktivnosti potrebno opraviti elektronsko in IKT so dokazale, da je elektronsko marsikdaj celo bolje kot fizično. Po drugi strani pa se je pospešil razpad družbenih vrednot, zaupanje v znanost in razvoj. Celo Flynnov učinek – merjenje IQ na svetovni populaciji – kaže, da ljudje ne postajajo čedalje bolj pametni. Nasprotno - čedalje več ljudi verjame, da je Zemlja ploščata, da bo cepivo za korono škodljivo, ali da je korona škodljiva kot navadna gripa (v resnici je desetkrat bolj). Razkorak med rastočim znanjem in vraževerjem se povečuje. Letos smo v multikonferenco povezali osem odličnih neodvisnih konferenc. Zajema okoli 160 večinoma spletnih predstavitev, povzetkov in referatov v okviru samostojnih konferenc in delavnic in 300 obiskovalcev. Prireditev bodo spremljale okrogle mize in razprave ter posebni dogodki, kot je svečana podelitev nagrad – seveda večinoma preko spleta. Izbrani prispevki bodo izšli tudi v posebni številki revije Informatica (http://www.informatica.si/), ki se ponaša s 44-letno tradicijo odlične znanstvene revije. Multikonferenco Informacijska družba 2020 sestavljajo naslednje samostojne konference: • Etika in stroka • Interakcija človek računalnik v informacijski družbi • Izkopavanje znanja in podatkovna skladišča • Kognitivna znanost • Ljudje in okolje • Mednarodna konferenca o prenosu tehnologij • Slovenska konferenca o umetni inteligenci • Vzgoja in izobraževanje v informacijski družbi Soorganizatorji in podporniki konference so različne raziskovalne institucije in združenja, med njimi tudi ACM Slovenija, SLAIS, DKZ in druga slovenska nacionalna akademija, Inženirska akademija Slovenije (IAS). V imenu organizatorjev konference se zahvaljujemo združenjem in institucijam, še posebej pa udeležencem za njihove dragocene prispevke in priložnost, da z nami delijo svoje izkušnje o informacijski družbi. Zahvaljujemo se tudi recenzentom za njihovo pomoč pri recenziranju. V 2020 bomo petnajstič podelili nagrado za življenjske dosežke v čast Donalda Michieja in Alana Turinga. Nagrado Michie-Turing za izjemen življenjski prispevek k razvoju in promociji informacijske družbe je prejela prof. dr. Lidija Zadnik Stirn. Priznanje za dosežek leta pripada Programskemu svetu tekmovanja ACM Bober. Podeljujemo tudi nagradi »informacijska limona« in »informacijska jagoda« za najbolj (ne)uspešne poteze v zvezi z informacijsko družbo. Limono je prejela »Neodzivnost pri razvoju elektronskega zdravstvenega kartona«, jagodo pa Laboratorij za bioinformatiko, Fakulteta za računalništvo in informatiko, Univerza v Ljubljani. Čestitke nagrajencem! Mojca Ciglarič, predsednik programskega odbora Matjaž Gams, predsednik organizacijskega odbora i FOREWORD INFORMATION SOCIETY 2020 The 23rd Information Society Multiconference (http://is.ijs.si) was halved due to COVID-19. The multiconference survived due to the conference presidents that bravely decided to continue with their conference despite the first pandemics in the modern era. The COVID-19 pandemics did not decrease the growth of ICT, information society, artificial intelligence and science overall, quite on the contrary – suddenly most of the activities had to be performed by ICT and often it was more efficient than in the old physical way. But COVID-19 did increase downfall of societal norms, trust in science and progress. Even the Flynn effect – measuring IQ all over the world – indicates that an average Earthling is becoming less smart and knowledgeable. Contrary to general belief of scientists, the number of people believing that the Earth is flat is growing. Large number of people are weary of the COVID-19 vaccine and consider the COVID-19 consequences to be similar to that of a common flu dispute empirically observed to be ten times worst. The Multiconference is running parallel sessions with around 160 presentations of scientific papers at twelve conferences, many round tables, workshops and award ceremonies, and 300 attendees. Selected papers will be published in the Informatica journal with its 44-years tradition of excellent research publishing. The Information Society 2020 Multiconference consists of the following conferences: • Cognitive Science • Data Mining and Data Warehouses • Education in Information Society • Human-Computer Interaction in Information Society • International Technology Transfer Conference • People and Environment • Professional Ethics • Slovenian Conference on Artificial Intelligence The Multiconference is co-organized and supported by several major research institutions and societies, among them ACM Slovenia, i.e. the Slovenian chapter of the ACM, SLAIS, DKZ and the second national engineering academy, the Slovenian Engineering Academy. In the name of the conference organizers, we thank all the societies and institutions, and particularly all the participants for their valuable contribution and their interest in this event, and the reviewers for their thorough reviews. For the fifteenth year, the award for life-long outstanding contributions will be presented in memory of Donald Michie and Alan Turing. The Michie-Turing award was given to Prof. Dr. Lidija Zadnik Stirn for her life-long outstanding contribution to the development and promotion of information society in our country. In addition, a recognition for current achievements was awarded to the Program Council of the competition ACM Bober. The information lemon goes to the “Unresponsiveness in the development of the electronic health record”, and the information strawberry to the Bioinformatics Laboratory, Faculty of Computer and Information Science, University of Ljubljana. Congratulations! Mojca Ciglarič, Programme Committee Chair Matjaž Gams, Organizing Committee Chair ii KONFERENČNI ODBORI CONFERENCE COMMITTEES International Programme Committee Organizing Committee Vladimir Bajic, South Africa Matjaž Gams, chair Heiner Benking, Germany Mitja Luštrek Se Woo Cheon, South Korea Lana Zemljak Howie Firth, UK Vesna Koricki Olga Fomichova, Russia Marjetka Šprah Vladimir Fomichov, Russia Mitja Lasič Vesna Hljuz Dobric, Croatia Blaž Mahnič Alfred Inselberg, Israel Jani Bizjak Jay Liebowitz, USA Tine Kolenik Huan Liu, Singapore Henz Martin, Germany Marcin Paprzycki, USA Claude Sammut, Australia Jiri Wiedermann, Czech Republic Xindong Wu, USA Yiming Ye, USA Ning Zhong, USA Wray Buntine, Australia Bezalel Gavish, USA Gal A. Kaminka, Israel Mike Bain, Australia Michela Milano, Italy Derong Liu, Chicago, USA prof. Toby Walsh, Australia Programme Committee Mojca Ciglarič, chair Andrej Gams Vladislav Rajkovič Bojan Orel, co-chair Matjaž Gams Grega Repovš Franc Solina, Mitja Luštrek Ivan Rozman Viljan Mahnič, Marko Grobelnik Niko Schlamberger Cene Bavec, Nikola Guid Špela Stres Tomaž Kalin, Marjan Heričko Stanko Strmčnik Jozsef Györkös, Borka Jerman Blažič Džonova Jurij Šilc Tadej Bajd Gorazd Kandus Jurij Tasič Jaroslav Berce Urban Kordeš Denis Trček Mojca Bernik Marjan Krisper Andrej Ule Marko Bohanec Andrej Kuščer Tanja Urbančič Ivan Bratko Jadran Lenarčič Boštjan Vilfan Andrej Brodnik Borut Likar Baldomir Zajc Dušan Caf Janez Malačič Blaž Zupan Saša Divjak Olga Markič Boris Žemva Tomaž Erjavec Dunja Mladenič Leon Žlajpah Bogdan Filipič Franc Novak iii iv KAZALO / TABLE OF CONTENTS Slovenska konferenca o umetni inteligenci / Slovenian Conference on Artificial Intelligence .......................... 1 PREDGOVOR / FOREWORD ................................................................................................................................. 3 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ..................................................................................... 5 Using Mozil a’s Deep Speech to Improve Speech Emotion Recognition / Andova Andrejaana, Bromuri Stefano, Luštrek Mitja ....................................................................................................................................................... 7 Towards Automatic Recognition of Similar Chess Motifs / Bizjak Miha, Guid Matej ............................................ 11 Drinking Detection From Videos in a Home Environment / De Masi Carlo M., Luštrek Mitja .............................. 15 Semantic Feature Selection for AI-Based Estimation of Operation Durations in Individualized Tool Manufacturing / Dovgan Erik, Filipič Bogdan .................................................................................................. 19 Generating Alternatives for DEX Models using Bayesian Optimization / Gjoreski Martin, Kuzmanovski Vladimir .......................................................................................................................................................................... 23 Detekcija napak na industrijskih izdelkih / Golob David, Petrovčič Janko, Kalabakov Stefan, Kocuvan Primož, Bizjak Jani, Dolanc Gregor, Ravničan Jože, Gams Matjaž, Bohanec Marko .................................................. 27 Data Protection Impact Assessment - an Integral Component of a Successful Research Project From the GDPR Point of View / Gültekin Várkonyi Gizem, Gradišek Anton .............................................................................. 32 Deep Transfer Learning for the Detection of Imperfectionson Metallic Surfaces / Kalabakov Stefan, Kocuvan Primož, Bizjak Jani, Gazvoda Samo, Gams Matjaž ......................................................................................... 35 Fall Detection and Remote Monitoring of Elderly People Using a Safety Watch / Kiprijanovska Ivana, Bizjak Jani, Gams Matjaž ............................................................................................................................................ 39 Machine Vision System for Quality Control in Manufacturing Lines / Kiprijanovska Ivana, Bizjak Jani, Gazvoda Samo, Gams Matjaž ......................................................................................................................................... 43 Abnormal Gait Detection Using Wrist-Worn Inertial Sensors / Kiprijanovska Ivana, Gjoreski Hristijan, Gams Matjaž ............................................................................................................................................................... 47 Avtomatska detekcija obrabe posnemalnih igel / Kocuvan Primož, Bizjak Jani, Kalabakov Stefan, Gams Matjaž .......................................................................................................................................................................... 51 Povečevanje enakosti (oskrbe duševnega zdravja) s prepričljivo tehnologijo / Kolenik Tine, Gams Matjaž ....... 55 Analiza glasu kot diagnostičn ametodaza odkrivanje Parkinsonove bolezni / Levstek Andraž, Silan Darja, Vodopija Aljoša ................................................................................................................................................. 59 STRAW Application for Collecting Context Data and Ecological Momentary Assessment / Lukan Junoš, Katrašnik Marko, Bolliger Larissa, Clays Els, Luštrek Mitja ............................................................................. 63 URBANITE H2020 Project Algorithms and Simulation Techniques for Decision-Makers / Machidon Alina, Smerkol Maj, Gams Matjaž .............................................................................................................................. 68 Towards End-to-end Text to Speech Synthesis in Macedonian Language / Neceva Marija, Stoilkovska Emilija, Gjoreski Hristijan .............................................................................................................................................. 72 Improving Mammogram Classification by Generating Artificial Images / Peterka Ana, Bosnić Zoran, Osipov Evgeny .............................................................................................................................................................. 76 Mobile Nutrition Monitoring System: Qualitative and Quantitative Monitoring / Reščič Nina, Jordan Marko, De Boer Jasmijn, Bierhoff Ilse, Luštrek Mitja ......................................................................................................... 80 Recognition of Human Activities and Falls by Analyzing the Number of Accelerometers and their Body Location / Shulajkovska Miljana, Gjoreski Hristijan ........................................................................................................... 84 Sistem za ocenjevanje esejev na podlag ikoherence in semantične skladnosti / Simončič Žiga, Bosnić Zoran . 88 Mental State Estimation of People with PIMD using Physiological Signals / Slapničar Gašper, Dovgan Erik, Valič Jakob, Luštrek Mitja ................................................................................................................................. 92 Energy-Efficient Eating Detection Using a Wristband / Stankoski Simon, Luštrek Mitja ...................................... 96 Comparison of Methods for Topical Clustering of Online Multi-speaker Discourses / Stropnik Vid, Bosnić Zoran, Osipov Evgeny ............................................................................................................................................... 100 Machine Learning of Surrogate Models with an Application to Sentinel 5P / Szlupowicz Michał Artur, Brence Jure, Adams Jennifer, Malina Edward, Džeroski Sašo .................................................................................. 104 Deep Multi-label Classification of ChestX-ray Images / Štepec Dejan ............................................................... 108 Smart Issue Retrieval Application / Zupančič Jernej, Budna Borut, Mlakar Miha, Smerkol Maj ........................ 112 Adaptation of Text to Publication Type / Žontar Luka, Bosnić Zoran ................................................................. 116 Kognitivna znanost / Cognitive Science .............................................................................................................. 121 PREDGOVOR / FOREWORD ............................................................................................................................. 123 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 124 Phenomenology of dissolution experiences: An exploratory study / Jaya Caporusso, Ema Demšar ................ 125 v Primerjava rezultatov analize funkcijske magnetne resonance z različnimi programskimi orodji / Nina Demšar ........................................................................................................................................................................ 130 What anime to watch next? The effect of personality on anime genre selection / Sara Jakša .......................... 134 Zaznavanje lastnosti zdravil brez recepta / Karin Kasesnik, Jani Toroš, Mihael Kline ...................................... 138 Kognitivno–motivacijski model čustvovanja v vsakdanjem življenju / Darja Kobal Grum .................................. 143 Motor learning and cortical plasticity: TMS motor mapping using the pseudorandom walk method / Eva Koderman, Jos van der Geest, Carolin Gaiser, Maarten Frens ..................................................................... 147 Chronotopic maps in temporal processing and perception / Shrikanth Kulashekhar ......................................... 151 Being in brackets: A first-person exploration of the phenomenological method of epoché / Viktorija Lipič ....... 154 A new study of expected human longevity / Anže Marinko, Klara Golob, Ema Jemec, Urša Klun, Matjaž Gams ........................................................................................................................................................................ 158 Does sight provide insight into Alzheimer’s dementia? / Katarina Marjanovič, Matej Perovnik ......................... 162 Patterns of mental behavior during psychological task performance / Aleš Oblak ............................................ 166 Vpliv posturalnih perturbacij na stresni odziv pri človeku / Carolina Petrič, Jernej Čamernik, Gregor Geršak, Jan Babič ............................................................................................................................................................... 169 Facial skin temperature during deception / Blaž Počervina, Ajda Centa, Gregor Geršak ................................. 173 Cognitive, psychological and social influence on spread of COVID-19 / Gašper Slapničar, Vito Janko, Tine Kolenik, Mitja Luštrek, Matjaž Gams .............................................................................................................. 176 Od orodja do umetnika / Neža Marija Slosar ...................................................................................................... 180 Social media use & digital stress among adolescents / Simon Šalomon, Dayana Hristova .............................. 184 Special sciences: Stil not reducible after all these years / Tadej Todorović, Janez Bregant ............................ 188 Odkrivanje znanja in podatkovna skladišča (SiKDD) / Data Mining and Data Warehouses (SiKDD) ............ 193 PREDGOVOR / FOREWORD ............................................................................................................................. 195 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 196 A Dataset for Information Spreading over the News / Sittar Abdul, Mladenić Dunja, Erjavec Tomaž ............... 197 Learning to fill the slots from multiple perspectives / Zajec Patrik, Mladenić Dunja ........................................... 201 Knowledge graph aware text classification / Petrželková Nela, Škrlj Blaž, Lavrač Nada .................................. 205 EveOut: Reproducible Event Dataset for Studying and Analyzing the Complex Event-Outlet Relationship / Swati, Erjavec Tomaž, Mladenić Dunja .......................................................................................................... 209 Ontology alignment using Named-Entity Recognition methods in the domain of food / Popovski Gorjan, Eftimov Tome, Mladenić Dunja, Koroušič Seljak Barbara ........................................................................................... 213 Extracting structured metadata from multilingual textual descriptions in the domain of silk heritage / Massri M.Besher, Mladenić Dunja ............................................................................................................................. 217 Hierarchical classification of educational resources / Žunič Gregor, Novak Erik ............................................... 221 Are You Following the Right News-Outlet? A Machine Learning based approach to outlet prediction / Swati, Mladenić Dunja ............................................................................................................................................... 225 MultiCOMET – Multilingual Commonsense Description / Mladenić Grobelnik Adrian, Mladenić Dunja, Grobelnik Marko .............................................................................................................................................................. 229 A Slovenian Retweet Network 2018-2020 / Evkoski Bojan, Mozetič Igor, Ljubešić Nikola, Kralj Novak Petra .. 233 Toward improved semantic annotation of food and nutrition data / Jovanovska Lidija, Panov Panče .............. 237 Absenteeism prediction from timesheet data: A case study / Zupančič Peter, Mileva Boshkoska Mileva, Panov Panče.............................................................................................................................................................. 241 Monitoring COVID-19 through text mining and visualization / Massri M.Besher, Pita Costa Joao, Andrej Bauer, Grobelnik Marko, Brank Janez, Luka Stopar ................................................................................................. 245 Usage of Incremental Learning in Land-Cover Classification / Peternelj Jože, Šircelj Beno, Kenda Klemen ... 249 Predicting bitcoin trend change using tweets / Jelenčič Jakob .......................................................................... 253 Large-Scale Cargo Distribution / Stopar Luka, Bradeško Luka, Jacobs Tobias, Kurbašić Azur, Cimperman Miha ........................................................................................................................................................................ 257 Amazon forest fire detection with an active learning approach / Čerin Matej, Kenda Klemen ........................... 261 Etika in stroka / Professional Ethics ..................................................................................................................... 265 PREDGOVOR / FOREWORD ............................................................................................................................. 267 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 268 Should Algorithms Replace Teachers and Lecturers? / Grušovnik Tomaž ........................................................ 269 Humanist med informatiki: Jacques Berleur 1938 - 2020 / Pivec Franci ............................................................ 270 Etika in mediji / Gams Matjaž ............................................................................................................................. 272 Prispevek vernikov za bolj etično slovensko družbo / Osredkar Mari Jože........................................................ 276 Vloga religij pri oblikovanju globalne etike / Globokar Roman ........................................................................... 281 vi Etika in informatika / Schlamberger Niko............................................................................................................ 285 13. Mednarodna Konferenca o prenosu tehnologij (13.ITTC) / 13th International Technology Transfer Conference (13 ITTC)......................................................................................................................................... 289 PREDGOVOR / FOREWORD ............................................................................................................................. 291 ORGANIZACIJSKI ODBOR, PRIDRUŽENI PARTNERJI IN SPONZORJI / ORGANIZING COMMITTEE, ASSOCIATED PARTNERS AND FINANCERS ............................................................................................. 295 A decade of knowledge transfer in Slovenia / Stres Špela, Pal Levin ................................................................ 303 Patents on plasma treatments in agriculture / Recek Nina, Gselman Peter, Krajnc Mitja, Kozole Blaž, Rupnik Maja, Korošec Tamara, Primc Gregor ............................................................................................................ 312 Rare earth-based permanent magnets: A proposed way to the circular economy / Žužek Rožman Kristina, Xu Xuan, Kobe Spomenka, Tomše Tomaž, Podmiljšak Benjamin, Šturm Sašo ................................................. 317 Real-time fluorescence lifetime acquisition system / Pestotnik Rok, Dolenec Rok, Seljak Andrej, Mrak Matej 321 Regulated toxicity-testing: Spinning out a company in a rapidly changing market / Štrancar Janez, Stres Špela ........................................................................................................................................................................ 326 Status quo of computer-implemented inventions in Slovenia and EU / Fric Urška, Tomić Starc Nina .............. 331 Strategic intellectual property management system for universities and scientific organizations for efficient technology transfer / Khvorostyanaya Anna Sergeevna ............................................................................... 335 Strategic research and innovation partnerships as enablers of technology transfer / Bučar Maja, Lipnik Aleš . 338 The awareness on environmental protection issues as reflected through the inventions / Pal Levin ................ 341 Transfer of knowledge and skills in STEM: Exploring and promoting digital analysis skills - Testing optimal conditions of X-ray irradiation / Pestotnik Stres Svit ..................................................................................... 348 DODATEK / APPENDIKS .................................................................................................................................... 353 INTRODUCTION AND AIM OF THE CONFERENCE ................................................................................... 354 ACKNOWLEDGEMENTS ............................................................................................................................... 358 OVERVIEW OF THE PROGRAMME ............................................................................................................. 360 WELCOME ADDRESSES .............................................................................................................................. 361 KEYNOTE SPEECHES .................................................................................................................................. 362 BEST INNOVATION WITH COMMERCIAL POTENTIAL: PITCH COMPETITION ....................................... 367 Abstracts of the Competing Teams and their Technologies .......................................................................... 370 Award announcement: Best innovation with commercial potential ................................................................ 377 Award announcement: WIPO IP Enterprise Trophy ....................................................................................... 378 Award announcement: WIPO Medal for Inventors ......................................................................................... 379 Research2Business meetings (R2B meetings) .............................................................................................. 380 CONFERENCE CEREMONY......................................................................................................................... 382 Ljudje in okolje / People and Environment .......................................................................................................... 385 PREDGOVOR / FOREWORD ............................................................................................................................. 387 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 388 The Shrinking of Human Population and Causes for it – is Women Education and Empowerment among them? / Gams Matjaž .................................................................................................................................................. 389 Standardi kakovosti storitev zdravja na daljavo za starejše odrasle - njihov poudarjen pomen v času epidemije Covid-19 / Samar Brenčič Neja, Rudel Drago ............................................................................................... 393 Delitvena ekonomija za starejše / Ogrin Alenka, Svetelšek Ajda ....................................................................... 396 Razlike med spoloma v ekonomski odvisnosti v obdobju 2000–2012 / Istenič Tanja, Ograjenšek Irena, Sambt Jože ................................................................................................................................................................ 400 Demonstrational vegetable garden with ReSoil remediated soil / Leštan Domen ............................................. 404 Lahko migracije zaustavijo pritisk staranja prebivalstva Slovenije na ekonomsko vzdržnost? / Sambt Jože, Istenič Tanja ................................................................................................................................................... 408 Vetrne elektrarne niso za Slovenijo / Ogrin Tomaž, Deželak Ferdinand ............................................................ 412 Traffic Simulation Software in the Context of Mobility Policy Support System / Smerkol Maj, Počkar Žan, Machidon Alina, Gams Matjaž ........................................................................................................................ 418 Kako so predvidevale razvoj prebivalstva Slovenije tri izbrane projekcije prebivalstva Slovenije v preteklosti / Malačič Janez ................................................................................................................................................. 422 Vzgoja in izobraževanje v informacijski družbi / Education in Information Society ........................................ 427 PREDGOVOR / FOREWORD ............................................................................................................................. 429 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 430 Poučevanje programskega okolja LabView / Albreht Jaka ................................................................................ 433 vii Programska koda kot izrazni medij ustvarjalnosti v izrednih razmerah / Babič Davorin .................................... 438 E-učenje na dokazih podprte zdravstvene nege / Baggia Alenka, Leskovar Robert, Šmitek Branislav, Rajkovič Uroš, Mlakar Saša, Pesjak Katja, Lil o-Crespo Manuel, Riquelme Galindo Jorge, FitzGerald Christine, Cadorin Lucia, Narduzzi Barbara, Scarsini Sara ............................................................................................ 444 Inovativni pristop k širjenju znanja o standardih / Baggia Alenka, Bučer Maja, Fink Betka, Gajšek Brigita, Butkovič Amanda, Kolidžić Jovana, Mastnak Adrijana, Podgorelec Mateja, Slodnjak Valentina, Fanedl Nina, Podlogar Mateja ............................................................................................................................................. 451 Lastna postavitev in uporaba spletne storitve za verzioniranje datotek / Baloh Miha ........................................ 457 Pregled in primerjava spletnih storitev za shranjevanje datotek / Baloh Miha ................................................... 462 Usvajanje digitalnih kompetenc in dodatna pomoč učencu s posebnimi potrebami pri izobraževanju na daljavo / Borovnik Aleksandra ....................................................................................................................................... 466 Učenje angleščine z uporabo spletnega orodja Quizlet / Delovec Urška ........................................................... 470 Razvoj krmilnika za upravljanje senčil / Dojčinović Aleksandar, Prelog Martin, Rajkovič Uroš ......................... 474 Šolsko delo na daljavo v osnovni šoli / Drvarič Radmila .................................................................................... 480 Poustvarjanje Povodnega moža z animacijo / Gabrijelčič Barbara .................................................................... 484 Z IKT in dnevom dejavnosti do animiranega filma / Gulin Vesna ....................................................................... 488 Mednarodni tabori računalništva in komunikacije za slepe in slabovidne (ICC) / Hribar Grega ........................ 492 Osebna eRedovalnica / Jeram Bojan ................................................................................................................. 495 Raba IKT kot predmet filmske upodobitve / Jereb Robert.................................................................................. 499 S spletnimi zemljevidi raziskujem svoj domači kraj / Jevšnik Barbara ............................................................... 503 Geografija in izobraževanje na daljavo / Jurač Vesna ....................................................................................... 507 Učinkoviti načini učenja rabe spletnih orodij / Karanjac Blanka ......................................................................... 511 Spletna učilnica pri športni vzgoji / Klampfer Viktor ............................................................................................ 515 Vodenje aktiva med šolanjem na daljavo / Knez Jožica ..................................................................................... 518 Pl@ntNet in XMind pri pouku slovenščine in naravoslovja / Kokelj Martina ...................................................... 522 Včeraj za danes in jutri / Kolenc Metka, Močnik Alenka ..................................................................................... 525 Določevanje težnega pospeška s pomočjo pametnega telefona / Kosem Goran .............................................. 530 Uporaba aplikacije KamenCheck pri pouku geografije / Kotnik Klaužer Lidija ................................................... 534 Delo z učenci s posebnimi potrebami v času šolanja na daljavo / Kupec Lucija................................................ 537 Uporaba IKT v času šolanja na daljavo pri učenki s težko motnjo v gibalnem razvoju / Kupec Lucija .............. 541 Spletna varnost pri pouku na daljavo v času epidemije COVID-19 / Kušar Luka .............................................. 544 Timsko delo kot osnova hipoterapije / Lambić Ana, Medved Tilen, Jerin Matija, Cerkovnik Pia, Ramšak Špela, Šabec Ana, Podobnik Metka, Polner Nikita, Breznikar Tilen, Lauko Lina, Vukovič Goran, Werber Borut .... 547 Se igram ali učim? Spletna aplikacija Wordwall / Leben Jazbec Sanja ............................................................. 552 Laboratorijske vaje pri fiziki – izzivi in možne rešitve pri poučevanju na daljavo / Leskovar Kristina ............... 555 ACM Tekmovanja – Pišek, tekmovanje v programiranju z delčki / Lokar Matija, Mujkić Maja........................... 558 Uporaba Sistema Pišek pri pouku neobveznega izbirnega predmeta računalništvo / Lokar Matija, Mujkić Maja ........................................................................................................................................................................ 564 Uporaba IKT pri urah športa kot pripomoček za izboljšanje izvajanja osnovnih elementov pri skokih na mali prožni ponjavi / Malovič Janez ...................................................................................................................... 570 Uporaba aplikacije mCOBISS v 8. razredu / Mazgan Lidija ............................................................................... 574 Veščine poučevanja na daljavo in praktični nasveti / Minić Miroslava ............................................................... 579 Izdelovanje preprostih zemljevidov s programom Google Earth pri pouku geografije / Mrak Nataša ............... 584 IKT po vertikali pri pouku matematike / Mrkela Vesna ....................................................................................... 589 Aplikacije in metode dela za poučevanje angleškega jezika na daljavo / Opravž Ostrelič Lea ......................... 593 Razvijanje veščin 21. stoletja pri medpredmetni povezavi fizike z matematiko, informatiko in športno vzgojo / Ovčar Silvestar ............................................................................................................................................... 598 Učenje na daljavo v Arnesovih spletnih učilnicah / Pajnik Tina, Strgar Sonja.................................................... 602 Poučevanje tujega jezika na daljavo in nova normalnost / Paradiž Alan ........................................................... 607 Učenje besedišča z aplikacijo Quizlet / Peruš Andreja ...................................................................................... 611 Raziskovanje in promocija digitalnih veščin: Testiranje optimalnih pogojev rentgenskega obsevanja (primer sodelovanja STEM) / Pestotnik Stres Svit ..................................................................................................... 614 Uporaba IKT pri pouku športne vzgoje v času dela na daljavo / Pirc Anja ......................................................... 620 Digitalni umetniki ali pouk na daljavo / Praprotnik Žaucer Tatjana ..................................................................... 625 Delavnice snovanja poslovnega modela v kontekstu digitalne preobrazbe / Pucihar Andreja, Lenart Gregor, Marolt Marjeta, Vidmar Doroteja .................................................................................................................... 630 Pomoč pri pouku na daljavo za učitelje, učence in starše / Purg Peter ............................................................. 634 Učenje na daljavo v času pandemije covid-19 / Rajher Polona ......................................................................... 638 Uporaba elektronskih gradiv za delo na daljavo v času epidemije pri mlajših učencih v osnovni šoli / Rebec Suzana ........................................................................................................................................................... 642 viii Steganografija / Rehberger Roman .................................................................................................................... 647 Varnost informacijskih sistemov / Rehberger Roman ........................................................................................ 653 Izzivi poučevanja slovenskega jezika in književnosti na daljavo / Robida Maruša ............................................ 659 Medpredmetno povezovanje in uporaba informacijsko-komunikacijske tehnologije pri poučevanju na daljavo v osnovni šoli / Samida Cerk Simona ............................................................................................................... 663 Preverjanje in ocenjevanje znanja z aplikacijo Liveworksheet / Silovšek Saša ................................................. 667 Formativno spremljanje v času izobraževanja na daljavo / Skumavc Nuša....................................................... 671 Varna mobilnost tudi na daljavo / Skumavc Nuša .............................................................................................. 676 Razvoj obiskov na Institutu »Jožef Stefan« skozi čas - od odprtih vrat do virtualnega obiska / Stres Špela, Pal Levin ............................................................................................................................................................... 680 Uporaba aplikacije Padlet za učence s posebnimi potrebami pri pouku na daljavo / Šebjanič Oražem Maja ... 686 Oblikovanje učencu prilagojenih e-gradiv / Šuštaršič Urška .............................................................................. 690 Spremljanje srčnega utripa s pomočjo IKT pri predmetu šport / Tomić Marina ................................................. 696 Pouk angleščine na daljavo s spletnim orodjem BookWidgets / Tonić Aleksandar ........................................... 700 Pozitivni in negativni vidiki igrifikacije v izobraževanju / Urh Marko, Jereb Eva ................................................. 707 Vpeljava, dobre prakse in spoznanja poučevanja ter učenja na daljavo na Osnovni šoli Preska / Veselinovič Tina ................................................................................................................................................................. 712 Od besede do besedila s pomočjo IKT / Vučko Tadeja ..................................................................................... 716 Uporaba spletnega orodja Classkick pri izobraževanju na daljavo / Zupanc Anita ............................................ 720 Razredna problematika in delo na daljavo / Žibert Astrid ................................................................................... 723 Poučevanje programiranja s snovanjem iger / Bevčič Mateja, Rugelj Jože ....................................................... 727 Prepoznavanje disleksije s spletno aplikacijo / Košak Babuder Milena, Korun Blažka, Štarkl Ema, Nenadović Gaja, Stanković Erika, Jakop Sara, Vranješ Luka, Boben Dušica, Žabkar Jure ............................................ 732 Interakcija človek računalnik v informacijski družbi / Human-Computer Interaction in Information Society ............................................................................................................................................................................. 739 PREDGOVOR / FOREWORD ............................................................................................................................. 741 PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ................................................................................. 742 Investigating the Role of Context and Personality in Mobile Advertising / Martinovic Andrej, Pejović Veljko .... 743 Interaktivna vizualizacija proračuna Republike Slovenije s Sankeyevim diagramom / Tušar Tea .................... 747 MightyFields Voice: Voice-based Mobile Application Interaction / Zupančič Jernej, Štravs Miha, Mlakar Miha 751 eBralec 4: hibridni sintetizator slovenskega govora / Žganec Gros Jerneja, Romih Miro, Šef Tomaž .............. 755 Sound 2121: The Future of Music is Natural / Deja Jordan Aiko, Attygale Nuwan, Čopič Pucihar Klen, Kljun Matjaž ............................................................................................................................................................. 759 Ohranjanje kulturne dediščine s pomočjo navidezne in obogatene resničnosti / Plankelj Marko, Lukač Niko, Rizvić Selma, Kolmanič Simon ....................................................................................................................... 763 Predmetnik: oprijemljiv uporabniški vmesnik za informiranje turistov / Sotlar Gregor, Roglej Peter, Čopič Pucihar Klen, Kljun Matjaž ............................................................................................................................. 767 Razvoj in Ocenjevanje Prototipa Mobilne Aplikacije z Elementi Igrifikacije in Mešane Resničnosti / Zorko Monika, Debevc Matjaž, Kožuh Ines .............................................................................................................. 771 StreetGamez: detection of feet movements on the projected gaming surface on the floor / Škrlj Peter, Lochrie Mark, Kljun Matjaž, Čopič Pucihar Klen ......................................................................................................... 775 Anamorfična projekcija na poljubno neravno površino / Cej Rok, Solina Franc ................................................ 779 Učinkovita predstavitev slovarskih jezikovnih virov pri govornih tehnologijah / Žganec Gros Jerneja, Golob Žiga, Dobrišek Simon .............................................................................................................................................. 783 The Fundamentals of Sound Field Reproduction Using a Higher Order Ambisonics System / Prislan Rok ..... 787 The use of eCare services among informal carers of older people and psychological outcomes of their use / Smole Orehek Kaja, Dolnicar Vesna, Hvalič Touzery Simona ...................................................................... 790 Indeks avtorjev / Author index .............................................................................................................................. 795 Indeks avtorjev nerecenziranih prispevkov v dodatku conference 13. ITTC / Index of authors of unreviewed contributions in the appendix of 13 ITTC conference ................................................................................... 801 ix x Zbornik 23. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2020 Zvezek A Proceedings of the 23rd International Multiconference INFORMATION SOCIETY – IS 2020 Volume A Slovenska konferenca o umetni inteligenci Slovenian Conference on Artificial Intelligence Uredili / Edited by Mitja Luštrek, Matjaž Gams, Rok Piltaver http://is.ijs.si 6. – 7. oktober 2020 / 5 - 7 October 2020 Ljubljana, Slovenia 1 2 PREDGOVOR Leto 2020 je bilo za informacijsko družbo zelo pomembno: zmanjšanje medosebnih stikov zaradi COVID-19 je pokazalo, da se da s pomočjo informacijskih tehnologij postoriti še precej več, kot smo si do zdaj mislili. S pomočjo telekonferenčnih sistemov smo se sestajali, digitalno smo prenašali in podpisovali dokumente, prek spleta smo lahko naročili domala vse izdelke in storitve ... Čeravno sta umetna inteligenca in informacijska družba vedno tesneje povezani, pa podobno dramatičnega napredka pri umetni inteligenci ni bilo opaziti. Seveda to ne pomeni, da napredka ni bilo – raznotere metode umetne inteligence še naprej postajajo vedno zmogljivejše in predvsem prodirajo v vedno manjše in cenejše naprave: opažamo lahko, da se namenski procesorji za operacije umetnih nevronskih mrež vedno pogosteje pojavljajo v pametnih telefonih, pametnih zvočnikih z govornimi asistenti in podobnih napravah. Umetno inteligenco smo zapregli tudi v spopad s COVID-19. Raziskovalci so jo uporabili za določanje strukture virusa in za iskanje učinkovitih zdravil in cepiv. Skupina ameriških organizacij je razpisala nagrado za najboljše pristope rudarjenja po besedilih, ki bodo iz 19 GB besedil, povezanih z boleznijo, izluščila koristne informacije. Razvitih je bilo več diagnostičnih sistemov za podporo odločanju, ki analizirajo slike pljuč in druge podatke. Precej raziskovalcev se je z metodami umetne inteligence lotilo napovedovanja širjenja bolezni in določanja dejavnikov, ki nanj vplivajo. Tovrstne raziskave se dogajajo tudi v Sloveniji. K sreči COVID-19 naši konferenci ni storil dosti žalega. Resda se ob pisanju tegale uvodnika še ne ve zagotovo, ali bo konferenca potekala na daljavo ali jo bomo uspeli speljati hibridno, kot načrtujemo – da bo del udeležencev prisoten v živo v predavalnici, del pa na daljavo. A verjamemo, da to na kakovost izvedbe ne bo bistveno vplivalo. Z zadovoljstvom pa ugotavljamo, da smo letos dobili največ prispevkov v zadnjih petih letih – v zbornik jih je vključenih kar 28. Tokrat je bolje kot običajno zastopana Fakulteta za računalništvo in informatiko Univerze v Ljubljani, ki ima skupaj z Institutom Jožef Stefan (od koder je – kot vsako leto – največ prispevkov) vodilno vlogo pri raziskavah umetne inteligence v Sloveniji. Nekaj prispevkov je tudi iz tujine in industrije, čeprav bi si zlasti slednjih želeli več. Slovenija namreč izobrazi veliko strokovnjakov s področja umetne inteligence in precej jih najde pot v industrijo, kjer se dogaja marsikaj zanimivega, o čemer vemo premalo. V to smer si bomo zato še bolj prizadevali v prihodnjih letih. 3 FOREWORD 2020 was an important year for the information society: social distancing due to COVID-19 showed that information technologies allow us to do even more that we previously thought. Teleconferencing systems allowed us to meet virtually, we transferred and signed documents digitally, we ordered every imaginable product and service online … However, even though artificial intelligence and information society are increasingly interlinked, the progress of artificial intelligence this year was not as significant. This certainly does not mean there was no progress – various artificial-intelligence methods are still steadily improving, and, perhaps even more importantly, becoming available in ever smaller and cheaper devices: dedicated processors accelerating neural-network computations are becoming common in smartphones, smart speakers with conversational assistants and similar devices. Artificial intelligence also helps fight COVID-19. It was used to determine the structure of the virus and to discover effective drugs and vaccines. A group of USA organizations offered a prize for the best data-mining methods that can extract information from 19 GB of texts related to the disease. Several diagnostic decision support systems were developed, which analyse images of the lungs and other data. Many researchers used artificial intelligence to forecast the spread of the disease and the factors that affect it. Such research is also conducted in Slovenia. Fortunately, COVID -19 did not much affect our conference. At the time of writing this editorial, it is still not clear whether it will take place remotely, or we will succeed with planned the hybrid approach, where a part of the participants will attend live in a lecture room with the rest connected via teleconference. Either way, we are confident this will not have a major impact on the quality of the conference. We are pleased to report that this year we have the largest number of papers in the last five years – there are 28 in these proceedings. The Faculty of Computer and Information Science is represented better than in previous years, which is quite appropriate considering that – aside from Jožef Stefan Institute (which contributed the largest number of papers, as usual) – it is the leading Slovenian research institution on artificial intelligence. There are also some papers from abroad and from the industry, although we would prefer to see more of these, especially the latter. The number of experts on artificial intelligence in Slovenia is quite large and a significant number find their way to the industry, where many interesting but not widely known developments take place. We aim to improve on this aspect in the following years. 4 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Mitja Luštrek Matjaž Gams Rok Piltaver Marko Bohanec Tomaž Banovec Cene Bavec Jaro Berce Marko Bonač Ivan Bratko Dušan Caf Bojan Cestnik Aleš Dobnikar Bogdan Filipič Nikola Guid Borka Jerman Blažič Tomaž Kalin Marjan Krisper Marjan Mernik Vladislav Rajkovič Ivo Rozman Niko Schlamberger Tomaž Seljak Miha Smolnikar Peter Stanovnik Damjan Strnad Peter Tancig Pavle Trdan Iztok Valenčič Vasja Vehovar Martin Žnidaršič 5 6 Using Mozilla’s DeepSpeech to Improve Speech Emotion Recognition Andrejaana Andova Stefano Bromuri Mitja Luštrek Jožef Stefan International Open University of the Netherlands Jožef Stefan Institute Postgraduate School Heerlen, Netherlands Jamova cesta 39 Jožef Stefan Institute Stefano.Bromuri@ou.nl Ljubljana, Slovenia Jamova cesta 39 mitja.lustrek@ijs.si Ljubljana, Slovenia andrejaana.andova@ijs.si ABSTRACT gather a dataset composed of speeches used in different contexts, A lot of effort in detecting emotions in speech has already been which is a hard task. made. However, most of the related work was focused on training Most of the currently available emotional speech datasets are a model on an emotional speech dataset, and testing the model composed of actors performing scenes with different emotions. on the same dataset. A model trained on one dataset seems to Finding actors and writing the scenes could be a costly and ef- provide poor results when tested on another dataset. This means fortful task and, thus, it is hard to collect large amounts of data that the models trained on publicly available datasets cannot be in this way. However, the major problem of this type of data is used in real-life applications where the speech context is different. that all of the emotions are acted and may be more exaggerated Furthermore, collecting large amounts of data to build an efficient when compared to real-life emotions [8]. This type of data is speech emotion classifier is not possible in most cases. probably pretty different when compared to data from real-life Because of this, some researchers tried using transfer learn- applications where emotions are expressed with less intensity. To ing to improve the performance of a baseline model trained on solve this problem, some researchers tried using transfer learning only one dataset. However, most of the works so far developed methods to build a model that is more robust to changes in the methods that transfer information from one emotional speech data. dataset into another emotional speech dataset. Some researchers tried using speeches recorded in real-life In this work, we try to transfer parameters from a pre-trained scenarios and asked people to listen to these speeches and anno- speech-to-text model that is already widely used. Unlike other tate the emotions they recognize in the speakers’ voices. When related work, which uses emotional speech datasets that are collecting a dataset in this way one needs to find people that usually small, in this method we will try to transfer information would listen to the whole dataset and annotate the data. The from a larger speech dataset which was collected by Mozilla and annotators would probably have different abilities to detect the whose main purpose was to transcribe speech. emotions and different perceptions of what each emotion should We used the first layer from the DeepSpeech model as the basis be like. Because of this, in many cases not all of them will agree for building another deep neural network, which we trained on on which emotion is present in a sample. Another drawback of the improvisation utterances from the IEMOCAP dataset. this type of data collection is that most of the time people do not experience extreme emotions. Because of this, such datasets KEYWORDS will result in almost no emotions – the speech would be mostly neutral. speech emotion recognition, feature transfer, DeepSpeech The main idea behind transfer learning is to use information from a dataset called source dataset to improve the performance 1 INTRODUCTION of a target dataset. The source and the target datasets may have There are many issues when trying to build a model for speech labeled or unlabeled data, may have the same data distribution or emotion recognition, but the main problem is the lack of emo- different data distribution, and they can be constructed to solve tional speech data. Collecting a dataset is often a challenging the same task or they may try to solve different tasks. Depending and effortful task, but in speech emotion recognition a few addi- on this, there are different approaches to transfer learning. They tional problems arise when creating a dataset. One of the main are more thoroughly explained by S. J. Pan et al. [5]. problems is that speech is a context-dependent problem. One In this work, we decided to follow the usual transfer learning could gather a dataset from job interviews and build a precise approach, and use a pre-trained speech-to-text model trained on model that detects emotions in job applicants’ speech. however, a large nonemotional English dataset collected by Mozilla. This the same model would probably not work for a phone application model may not contain any emotional information that would be that tries to analyze the emotions of its users. Thus, to build a useful for our task, but we believe it contains information about general model for speech emotion recognition, one would need to the speech of the subjects that could be used in speech emotion recognition. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or 2 RELATED WORK distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this While research in speech emotion recognition where training work must be honored. For all other uses, contact the owner/author(s). and testing are done on one dataset has already been well-studied, Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). using other datasets to make the model more generalized has been in focus only in recent years. 7 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Andrejaana Andova, Stefano Bromuri, and Mitja Luštrek Table 1: Emotion distribution in IEMOCAP. Anger Happiness Sadness Neutral 500 94 467 392 Some researchers tried using unlabeled target data to improve distribution of the emotions after the data reduction is given in speech emotion recognition models. Thus, Parthasarathy and Table 1. Busso [6] connected supervised and unsupervised learning to improve the performance of speech emotion recognition on a 4 METHODOLOGY target dataset. They used a network architecture similar to au- We developed methods that transfer information from a large toencoders to encode large amounts of unlabeled target data in nonemotional speech dataset into a target emotional speech an unsupervised way by putting the same speech in the input dataset. Since in most of the related work researchers were ex- and the output of the network. To force the network to encode tracting information from smaller emotional speech datasets and the emotional information from the speech, they connected the transferring this information to other emotional speech datasets, last encoding layer to another layer that was trying to learn the this is the first attempt that we know of in which a transfer of arousal, valence, and the dominance annotations on the speech information is tried from already well-defined pre-trained speech in a supervised way. When they compared their method to other dataset into a smaller emotional speech dataset, which is the state-of-the-art models, it showed improvement in the arousal standard approach in most transfer learning applications. and the dominance space while in the valence space they got However, to compare if the methods provide any useful im- results slightly worse than the state-of-the-art. provement, we compare them to a baseline model that was trained Some authors thought about bringing the feature space from and tested on IEMOCAP, and which does not use any kind of the source and the target data closer together. Thus, Song et al., [7] information transfer. used MMDE optimization and dimension reduction algorithms to bring the feature spaces from the source and the target datasets 4.1 Baseline Model closer together. After that, they used the shifted feature space To build a baseline classifier, we decided to use standard machine from the source dataset to train an SVM model. They used the learning approaches trained on features extracted using OpenS- EmoDB dataset as a source dataset, and a Chinese emotional MILE [2] as a baseline method. After testing several different dataset collected by them as a target dataset. After they trained machine learning approaches, we saw that Random Forest ob- the SVM model on the source dataset only, they applied the tained the best results for most of the target datasets. Because model on the target dataset and showed that the model performed of this, we decided to use a Random Forest classifier with 1000 with 59.8% accuracy. These results show improvement when trees and a maximal depth of 10 as a baseline model. compared to an SVM model trained on the source dataset and tested on the target dataset without any dimension reduction 4.2 DeepSpeech Model applied, which performs with 29.8% accuracy. However, the best performance was achieved with a model trained and tested on the target dataset, which achieved 85.5% accuracy. 3 DATASET In this research we used the Interactive emotional dyadic motion capture database (IEMOCAP) [1]. IEMOCAP consists of speech from ten different English-speaking actors (five male and five fe- male), and it is the largest dataset for speech emotion recognition that we found publicly available. It consists of approximately twelve hours of data where actors perform improvisations or scripted scenarios, specifically selected to elicit emotional ex- pressions. Since the actors were not given any specific emotions that they had to act, the database was annotated by multiple annotators into categorical labels, as well as dimensional labels, such as valence, activation, and dominance. The set of emotions the annotators could choose from was anger, happiness, excite- ment, sadness, frustration, fear, surprise, other, and neutral, but because most of the related work on transfer learning in speech emotion recognition only used anger, happiness, sadness and neutral utterances in their methods, we decided to also just use these emotions in our method. We noticed that most of the time, the three annotators did not Figure 1: Architecture of the original DeepSpeech model. perceive the same emotion and, thus, we decided to eliminate all data where all three annotators did not agree on the detected DeepSpeech is a model that tries to provide transcriptions emotion. This reduced the amount of data significantly. The of a given speech. The model has been trained on the English 8 Speech Emotion Recognition using DeepSpeech features Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Table 2: Classification accuracy obtained from the majority classifier and baseline Random Forest Classifier compared to the DeepSpeech features method. Model Majority Baseline DeepSpeech features Dense 34% 67% 58% LSTM 34% 67% 7% Dense1+Dense2 34% 67% 26% Dense1+LSTM2 34% 67% 66% data from the Mozilla Common Voice dataset [3]. This dataset a ‘relu’ function and has 20 hidden states. It is then connected to consists of 1469 hours of speech data that has been recorded by a dense layer activated by a ‘softmax’ activation function which 61521 different voices. The people whose voices were collected predicts the label of the whole utterance. belonged to different nationalities (and thus different English The third network architecture is composed of two parts. In accents), and different ages. All of this data is publicly available the first part we predict the emotion probabilities for each frame and can be easily accessed. separately and in the second part we use the emotion proba- The architecture of the DeepSpeech model is presented in bilities predictions from the first layer to predict the emotion Figure 1. Each utterance is a time-series data, where every time- probabilities for the whole utterance. The first part of the archi- slice is a vector of MFCC audio features [4]. The goal of the tecture is the same as in the first network architecture and is network is to convert an input sequence 𝑥 into a sequence of trained one one half of the training data. In the second part of character probabilities for the transcription 𝑦. this network, we use the predictions from the first part as input The network is composed of five hidden layers. The first three to a dense layer with a softmax activation function. The second layers are dense layers with ‘ReLU’ as an activation function. part of the network is trained on the other half of the training The fourth layer is an LSTM layer, the fifth layer is once again data. In this network architecture, for each sequence of 20 frames a dense layer with ‘ReLU’ activation function. The output layer we predict one vector of emotions. has a softmax function which outputs character probabilities. The fourth network consists of two separate parts and is pre- In the example in Figure 1 the output of the first frame is the sented in Figure 2. The first part takes the output of the Deep- character ‘C’, the second frame outputs the character ‘A’, and the Speech model, and tries to predict the probability for each of third frame outputs the character ‘T’, resulting with the word the target emotions separately. The first dense layer has a ’relu’ ‘CAT’. activation function and outputs 204 features. It is then connected to another dense layer with a softmax activation function that 4.3 Transfer Learning Using DeepSpeech predicts the emotions present in each frame separately. The sec- ond part of the network uses the output emotion probabilities We decided to experiment if we could transfer information from from the first part of the layer as an input. The second part of the DeepSpeech model that would be useful for the speech emo- the network consists of one LSTM layer which is trained on the tion recognition task. We used the representation learned by second half of the training data. The LSTM layer is activated by the DeepSpeech network to extract features for the IEMOCAP a ‘relu’ function and has 20 hidden states. It is then connected to dataset. We used the output from the first layer in the Deep- a dense layer activated by a ‘softmax’ activation function which Speech model as features for a given frame. We ended up with predicts the label of the whole utterance. This network archi- 2048 features for every 10-millisecond frame. So, if the whole tecture in a way is a combination from the first and the second utterance was 3 seconds long, we would receive a matrix with network architecture. dimensions 1800x2048 after the deep speech feature extraction. After the features from all the samples in IEMOCAP have been extracted, we trained a deep neural network using them. 5 RESULTS We simply added the layers from the new deep neural network on Since the DeepSpeech model is capable of learning language top of the first layer from the DeepSpeech model, and trained the phases in the speech, we decided to remove all scripted utter- new deep neural network from scratch by just using the samples ances from the IEMOCAP dataset and use just the utterances in from the IEMOCAP dataset. This way we repurpose the feature which the actors were asked to improvise. To evaluate the neural representations from the first layer of the DeepSpeech model. network architectures we used the leave-one-subject-out cross We experimented with several different deep neural network validation. architectures to see which one works best for this problem. In In Table 2 we present the results obtained from each of the the first architecture, we used a feed-forward network on the ex- deep neural network architectures that we tried as well as the tracted features per each frame. We used one hidden dense layer accuracy of the baseline model and the majority classifier. In the with ‘relu’ activation function and 204 neurons. We connected results we can see that the LSTM network architecture that we this layer to a dense layer with softmax activation function which tried performs quite poor, with classification accuracy of only 7%. predicted the emotion probabilities for each frame separately. Al- The most probable explanation for this is that this architecture though in the IEMOCAP dataset there are no labels for each is quite complex since it has 2048 features for each frame, and of the frames separately, we use the target label for the whole it tries to train an LSTM model on all of these features. To train utterance as target label for each of the frames. a model with this amount of parameters, we would need much The second model architecture we tried was to use the features more samples than the IEMOCAP improvisations. from the whole frame as input, and use a LSTM layer to learn the The architecture that provides the best results is the one that representations from the features. The LSTM layer is activated by uses a FFN to predict the features in each frame, and then uses a 9 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Andrejaana Andova, Stefano Bromuri, and Mitja Luštrek 6 CONCLUSION In this work we tried to improve a baseline speech emotion recognition classifier by transferring information from a pre- trained model. Although this transfer learning method has been most widely used in other computer science fields, most of the related work in speech emotion recognition developed transfer learning methods that transfer information from other emotional speech datasets into a target emotional speech dataset. The pre-trained model we used was Mozilla’s DeepSpeech that was developed as a speech-to-text model. To recognize emotions in speech, we used the first layer from the DeepSpeech model, on top of which we added a new classifier that was trained from scratch on an emotional speech dataset. This way we repurposed the feature maps learned previously for the dataset. The results from this approach did not seem to improve the classification accuracy of the improvisations part in the IEMO- CAP dataset. A possible explanation for this could be that the speech-to-text and speech emotion recognition tasks are simply not sufficiently related, and because of this the model could not extract any useful information from the DeepSpeech model. How- ever, since this was the first attempt to transfer information from a well-defined pre-trained model to a speech emotion recognition task, we believe it is still a valuable attempt. Figure 2: Architecture of the original DeepSpeech model. 7 ACKNOWLEDGMENTS This research has received funding from the European Union’s LSTM network to predict the final emotion predictions for the Horizon 2020 research and innovation programme under Grant whole utterance. We further experimented with this network Agreement No 769765 architecture to see how much the length of the frames changes the performance of the model. The results are presented in Figure REFERENCES 3. In this figure, we can notice that the performance of the model [1] Carlos Busso, Murtaza Bulut, Chi-Chun Lee, Abe Kazemzadeh, can be improved by using bigger frames when training the LSTM Emily Mower, Samuel Kim, Jeannette N Chang, Sungbok part of the DeepSpeech model. However, the performance of the Lee, and Shrikanth S Narayanan. 2008. Iemocap: interac- model does not differ a lot – only a few percentage points. tive emotional dyadic motion capture database. Language The results show that some of the DeepSpeech architectures resources and evaluation, 42, 4, 335. can perform better than the majority classifier but none of the [2] Florian Eyben, Martin Wöllmer, and Björn Schuller. 2010. architectures outperforms the baseline model. A possible explana- Opensmile: the munich versatile and fast open-source audio tion for this could be that these two tasks are simply not related feature extractor. In Proceedings of the 18th ACM interna- enough and we cannot use information from the DeepSpeech tional conference on Multimedia, 1459–1462. model to improve the performance of a model for speech emotion [3] Awni Hannun, Carl Case, Jared Casper, Bryan Catanzaro, recognition. Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, Adam Coates, et al. 2014. Deep speech: scaling up end-to-end speech recognition. arXiv preprint arXiv:1412.5567. [4] Beth Logan et al. 2000. Mel frequency cepstral coefficients for music modeling. In Ismir. Volume 270, 1–11. [5] Sinno Jialin Pan and Qiang Yang. 2009. A survey on transfer learning. IEEE Transactions on knowledge and data engineer- ing, 22, 10, 1345–1359. [6] Srinivas Parthasarathy and Carlos Busso. 2019. Semi-supervised speech emotion recognition with ladder networks. arXiv preprint arXiv:1905.02921. [7] Peng Song, Yun Jin, Li Zhao, and Minghai Xin. 2014. Speech emotion recognition using transfer learning. IEICE TRANS- ACTIONS on Information and Systems, 97, 9, 2530–2532. [8] Carl E Williams and Kenneth N Stevens. 1972. Emotions and speech: some acoustical correlates. The Journal of the Acoustical Society of America, 52, 4B, 1238–1250. Figure 3: Performance of DeepSpeech model by using dif- ferent frame lengths. 10 Towards Automatic Recognition of Similar Chess Motifs Miha Bizjak Matej Guid University of Ljubljana University of Ljubljana Faculty of Computer and Information Science Faculty of Computer and Information Science Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT 1.1 Related Work We present a novel method to find chess positions similar to a Existing chess search systems equipped with a query-by-example given query position from a collection of archived chess games. (QBE) [11] search interface are limited to searching only the exact Our approach considers not only the static similarity due to the matches in response to a given query position. To alleviate the arrangement of the chess pieces, but also the dynamic similarity problem of exact position searches, the Chess Query Language based on the recognition of chess motifs and dynamic, tactical system (CQL) [1] allows the search for approximate matches aspects of position similarity. We use information retrieval tech- of positions. However, it requires the user to define complex niques to enable efficient approximate searches, and implement queries in the system-specific language. The search results can textual encoding that captures the position, accessibility and con- be sorted by any user-defined feature. In addition, the CQL works nectivity between chess pieces, pawn structures, and moves that directly on game files and checks each game sequentially, making represent the solution to the problem. We have shown experi- it inefficient for querying larger databases. mentally how important the inclusion of both static and dynamic To overcome these problems, an approach has been proposed features is for the successful detection of similar chess motifs. which is based on information retrieval for obtaining similar In another experiment the program was able to quickly traverse chess positions [4], constructing a textual representation for a large database of positions to identify similar chess tactical each board position and using information retrieval methods problems. A chess expert found the resulting program useful for to calculate the similarity between these documents. Instead of automatically generating instructive examples for chess training. constructing a query manually, the user specifies a chess posi- tion and a query encoding the characteristics of the position is KEYWORDS automatically generated internally. Initially, a naive encoding problem solving, chess motifs, automatic similarity recognition was used, which only contains the positions of the individual pieces. The results have been improved by including additional information about the mobility of the individual pieces and the 1 INTRODUCTION structural relationships between the pieces. Further work has A significant part of acquiring human skills is to identify our been carried out to improve the quality of retrieval by implement- weaknesses and take measures to remedy them. In problem- ing automatic recognition of pawn structures [7]. The additional solving domains such as chess, the analysis of past games is information provided by the application of domain knowledge important for players trying to improve their game. Identifying has proved useful, however, the positions are still only statically their mistakes enables chess players to work on improving some evaluated. aspects of their game. This is often done by training on similar All existing approaches have a common shortcoming: they problems. Finding relevant similar problems involves recognis- only allow the search for statically similar positions, while ignor- ing both static patterns, i.e. finding similar chess positions, and ing the dynamic factors, which are often far more important to dynamic patterns, i.e. finding similar move sequences that solve a obtain relevant search results. problem. These static and dynamic patterns are often referred to as chess motifs. Learning and recognising chess motifs during the game is one of the main prerequisites for becoming a competent chess player [2]. 2 DOMAIN DESCRIPTION Chess instructors often look for examples containing relevant In this paper, we will focus on automatic retrieval of similar chess chess motifs from real games to provide their students with useful tactical problems from a large database of chess games. In chess, teaching material. However, it is impossible for a human being to the term tactic is used to describe a sequence of moves that takes go through thousands or even millions of games and find problem advantage of a certain position on the board and allows the player positions with similar chess motifs and similar solutions to those to gain material, a positional advantage, or even leads to a forced overlooked by the students in their game. Finding contextually checkmate sequence. similar chess positions could also be used for annotating chess Chess tactical problems are particularly important for the games [5] and in intelligent chess tutoring systems [10]. progress of chess players. Knowledge of tactical motifs helps The goal of our research is to develop a method to automati- them to quickly recognise the possible presence of a winning cally retrieve chess positions with similar chess motifs for a given or drawing combination in a position. Chess players improve query position from a collection of archived chess games. their tactical skills by solving tactical problems. A large number of games are decided by tactics, since a single mistake, which Permission to make digital or hard copies of part or all of this work for personal gives the opponent an opportunity for tactics can change the out- or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and come of a game. To help players to discover tactical possibilities the full citation on the first page. Copyrights for third-party components of this in games, many common patterns or tactical motifs have been work must be honored. For all other uses, contact the owner/author(s). defined in the chess literature [6]. Stoiljkovikj et al. developed a Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia method for estimating the difficulty of chess tactical problems [9]. © 2020 Copyright held by the owner/author(s). They introduced a concept of meaningful search trees, which can 11 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Miha Bizjak and Matej Guid (a) (b) (c) (a) (b) (c) Figure 1: Tactical motifs. Figure 2: Static and dynamic similarity. potentially be used either for motif recognition or as an additional For each tactic, the input consists of a starting position in FEN feature for positional similarity ranking. format and a solution move sequence in algebraic notation. The We use standard chess annotation. Chess games are stored solution can be provided with the position or calculated using using Portable Game Notation (PGN), chess positions are de- a chess engine. Sections 3.1 and 3.2 describe the features and scribed with Forsyth-Edwards Notation (FEN), and chess moves terms that are generated, and Figure 3 shows an example of a are described with Standard algebraic notation (SAN) [3]. text encoding. Figure 1 shows some of the more common motifs. In Figure 3.1 Static Features 1a, Black performs a double attack on the white king and queen at the same time. White must move the king out of check, allowing The static part of the encoding includes information about the Black to capture the queen. Figure 1b is an example of a discovered positions of pieces on the board, structural relationships between attack. By moving the bishop, White opens the queen’s line of pieces and pawn structures present in the position. attack on the rook on a2. After Black responds to move out of the The implementation is based on previous work on similar check, White can capture the black rook. The tactic in Figure 1c position retrieval [4] and pawn structure detection [7] and is is called deflection. The black king protects the rook on f8. White intended to serve as a baseline on which we aim to improve by gives a check with the bishop, forcing the black king to move implementing encoding of dynamic features. away from the rook so that it can be captured. 3.1.1 Piece positions and connectivity. The section describing To illustrate the difference between static and dynamic similar- piece positions and connectivity encoding consists of three parts: ity using an example, we compare the query position in Figure 2a with the positions in Figure 2b and Figure 2c. The position in • naive encoding - the positions of all the pieces on the board. Figure 2b seems to be very similar to that in Figure 2a: only the • reachable squares - all squares reachable by pieces on the white rook on h4 and the black rook on e8 have been removed. board in one move, with decreasing weight based on dis- These two positions are statically similar. On the other hand, tance from the original position, in format {piece symbol the position in Figure 2c seems to be quite different. However, and position}|{weight}. if we compare the move sequences that represent solutions to • connectivity between the pieces - the structural relation- these two tactical problems, we notice a great dynamic similarity. ships between the pieces in the positions. For each piece The solution in Figure 2a is 1. Rh8+ Kxh8 2. Qh6+ Kg8 3. Qxg7#. it is recorded which other pieces it attacks, defends or The solution in Figure 2c contains the same tactical motif as the attacks through another piece (X-ray attack). Attacks are solution mentioned above: the white rook is sacrificed on h8 encoded as {attacking piece symbol}>{attacked piece symbol and the black king must capture it, allowing the white queen to and position}. For defense and X-ray attack terms, < and = appear with check on h6 (note that it cannot be captured due separators are used instead. to the activity of the white bishop along the long diagonal) and 3.1.2 Pawn structures. For this section of the encoding, we use deliver checkmate on the next move. Note that such motif is not pawn structure detection algorithms [7] to detect the following possible in the position shown in Figure 2b. pawn structures in the position and encode them into terms: iso- We are particularly interested in recognising the dynamic sim- lated pawns (I{pawn position}), (protected) passed pawns (F{pawn ilarity, i.e. finding positions with similar motif(s) in the solution position}), backward pawns, doubled pawns and pawn chains. of the problem. However, we also want to take into account the Terms P({number}) and p({number}) are used to encode the num- static similarity, i.e. finding problems with similar initial position. ber of pawn islands for white and black, respectively. 3 SIMILARITY COMPUTATION 3.2 Dynamic Features To determine similarity between tactical problems we use an In the dynamic part of the encoding, we focus more on the solu- approach based on information retrieval. A set of features is tion of the tactical problem, trying to capture the motif behind computed from each problem’s starting position and its solution it. We first encode some general characteristics of the solution, move sequence. The features are then converted into textual then add more specific terms describing the move sequence. terms, forming a document that represents the problem. A collec- tion of documents is used to build an index, which can then be 3.2.1 General dynamic features. In this part we encode some queried using the textual encoding of a new position to retrieve basic features of the solution move sequence that can help us de- the most similar positions in the index. For the implementation termine similarity. We use a single term for each of the following of the system for indexing and retrieval of similar tactics we use features if it holds for the solution: the Apache Lucene Core library. Search results are ranked using • ?px - the player captures a piece in at least one of the the BM25 ranking function [8]. moves 12 Towards Automatic Recognition of Similar Chess Motifs Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia (a) Encoded position. Black to play, solution: 1... Qh1+ 2. Nxh1 (a) Base problem. Black to play, (b) Simplified problem. Black Rg2#. solution: 1... Rxa2+ 2. Kxa2 to play, solution: 1... Rxa2+ 2. Ra8+ 3. Ba7 Rxa7+ 4. Qa5 Kxa2 Ra5+ 3. Qa4 Rxa4#. Rxa5#. Feature set Generated terms static_positions qc1 Pb2 Pf2 Kh2 Pa3 Rd3 Ng3 Rh3 Qb4 ... Figure 4: A pair of tactical problems from the data set. qa1|0.78 qb1|0.89 qd1|0.89 qe1|0.78 ... q>Pb2 q>Pc4 Q>nb7 N>pg7 r>Ng3 4 EXPERIMENTAL RESULTS Pq !N>q !q>K !b>N !K>r !r>K !r>P obtain a set of position pairs that were considered similar by human experts. We manually checked the puzzles and verified (b) Text encoding of each set of features for the above position. the similarity between the solutions of the individual problem pairs. A total of 400 pairs were collected for the test data set. Figure 3: Text encoding of a tactical position. An example of such a pair is shown in Figure 4. The solution to both problems is to sacrifice the rook on the a-file to expose the king, resulting in checkmate with the other rook and the bishop on e4. The solution in the simplified problem contains the • ?ox - the opponent captures a piece in at least one of the same motif, but there are much fewer pieces, so the solution is moves generally easier for the students to find. • ?+ - the player gives a check at least once during the se- quence 4.1 Evaluation of Similarity Detection • ?= - the player promotes a pawn in at least one of the We tested the effectiveness of our methods using the set of 400 moves pairs of problems described in the previous section. We first built • ?S - the player sacrifices one or more pieces an index using the simplified version of the problem from each • ?# - the solution ends with a checkmate pair, then performed a query on the index with each of the regular • ?1/2 - the solution ends in a draw problems. For each query we recorded the rank of the matching position in the results and calculated how often the matching 3.2.2 Solution sequence features. In this section we encode infor- position appeared as the top result or within the first 𝑁 results. mation about the solution move sequence. The encoding includes We tested the search accuracy using the following feature a term for each: subsets: each feature group on its own, all static features, all • type of piece moved: !-{piece symbol} dynamic features and all features combined. All runs used the • type of piece captured: !x{piece symbol} default BM25 parameters 𝑘1 = 1.2 and 𝑏 = 0.75 and all included • attack between pieces that occurs during the solution: feature sets were weighted equally. The results are presented in !{attacking piece symbol}>{attacked piece symbol} Table 1. • type of piece sacrificed: !S{piece symbol} Using either only static or dynamic features did not yield the • (if the final position is a checkmate) type of piece involved best results. The results were significantly improved when both in checkmate: !#{piece symbol} static and dynamic features were combined. This shows that each set of features covers a different aspect of a tactic, both of which We count a piece as involved in checkmate if it is attacking either need to be considered when determining similarity. the king directly or any of the squares where the king could move from the current position (ignoring checks). 4.2 Similar Position Retrieval To include information about the order of moves and cap- In the second experiment, we selected 10 contextually different tures we also include a term for each two consecutive moves chess tactical problems and then automatically retrieved 5 most and captures in the solution. We also include a term for each similar positions for each of them from a large database of 278,840 pair of pieces involved in checkmate to capture more specific combinations of pieces. 1https://chesskingtraining.com/ct-art 13 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Miha Bizjak and Matej Guid Accuracy Feature set used top-1 top-5 top-10 static_positions 0.234 0.378 0.428 static_pawns 0.033 0.083 0.126 dynamic_general 0.008 0.038 0.071 dynamic_solution 0.421 0.657 0.761 all static features 0.252 0.370 0.433 all dynamic features 0.418 0.652 0.761 all features, equal weights 0.481 0.736 0.814 Table 1: Success rates for different configurations. (a) Query position. Black to play, solution: 1... Bh2+ 2. Kxh2 Qxe1. Position Solution Similarity score tactical problems constructed from the lichess.org game database. Building the index took about 14 minutes (it only needs to be static 38.95 done once), and retrieval was fast: only about 4 seconds. 1... Bh2+ dynamic 45.04 Figure 5 shows a query position and the first two of the five 2. Kxh2 Qxd1 total 83.99 most similar retrieved positions. This example illustrates how similarity ranking works and how the static and dynamic features contribute to the similarity scores of the results. The query posi- tion is an example of a discovered attack motif. With 1... Bh2+, Black sacrifices the bishop to later capture the rook on e1 with static 64.62 the queen. The first result shows the same motif with an almost 1... Nf3+ dynamic 12.32 identical move sequence. The main difference is that the key 2. Qxf3 Qxe1+ total 76.94 pieces are on the d-file and not on the e-file. The second result is another case of a discovered attack. In this example it is not a bishop but a knight sacrificed with a check to the white king. It is the static similarity (the arrangement and position of the pieces (b) Retrieval results. in the initial position) that contributes most to the great overall similarity of this tactical problem, although a certain dynamic Figure 5: Example of retrieval results. similarity was also detected. The resulting most similar positions were shown to a chess [2] Mark Dvoretsky and Artur Yusupov. 2006. Secrets of Chess expert. The expert was asked to comment on the reasons for Training. Edition Olms. the similarity of the resulting problems with the original query [3] International Chess Federation (FIDE). 2020. The FIDE positions, taking into account both static and dynamic aspects. Handbook. https://handbook.fide.com/. (2020). The expert was able to explain the similarity in 48 out of 50 [4] Debasis Ganguly, Johannes Leveling, and Gareth JF Jones. problems. Overall, the expert praised the program’s ability to 2014. Retrieval of similar chess positions. In Proceedings of detect dynamic similarity of positions, even if the initial positions the 37th international ACM SIGIR conference on Research & differ significantly. development in information retrieval. ACM, 687–696. 5 CONCLUSIONS [5] Matej Guid, Martin Možina, Jana Krivec, Aleksander Sadikov, and Ivan Bratko. 2008. Learning positional features for We introduced a novel method for retrieving similar chess posi- annotating chess games: A case study. In International tions, which takes into account not only static similarity due to Conference on Computers and Games. Springer, 192–204. the arrangement of the chess pieces, but also dynamic similarity [6] Chess Informant. 2014. Encyclopedia of Chess Combina- based on the recognition of chess motifs and dynamic, tactical tions, 5th Edition. Chess Informant. aspects of position similarity. The merits of the method were put [7] Matic Plut. 2018. Recognition of positional motifs in chess to the test in two experiments. The first experiment emphasized positions. Diploma thesis. University of Ljubljana. the importance of including both static and dynamic features for [8] Stephen E Robertson, Steve Walker, Susan Jones, Miche- the successful detection of similar chess motifs. In the second line M Hancock-Beaulieu, Mike Gatford, et al. 1995. Okapi experiment, the program was able to quickly traverse a large at trec-3. Nist Special Publication Sp, 109, 109. database of positions to identify similar chess tactical problems. [9] Simon Stoiljkovikj, Ivan Bratko, and Matej Guid. 2015. A A chess expert was able to explain the similarity in the vast major- computational model for estimating the difficulty of chess ity of the retrieved problems and praised the program’s ability to problems. In The Annual Third Conference on Advances in detect dynamic similarity of positions even if the initial positions Cognitive Systems. differ significantly. The resulting program can be useful for the [10] Beverly Park Woolf. 2010. Building intelligent interactive automatic generation of instructive examples for chess training. tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann. REFERENCES [11] Moshé M Zloof. 1975. Query-by-example: the invocation [1] G Costeff. 2004. The Chess Query Language: CQL. ICGA and definition of tables and forms. In Proceedings of the 1st Journal, 27, 4, 217–225. International Conference on Very Large Data Bases, 1–24. 14 Drinking Detection From Videos in a Home Environment Carlo M. De Masi Mitja Luštrek carlo.maria.demasi@ijs.si mitja.lustrek@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT parameters makes 3DCNNs generally harder to train than their 2D counterparts. One way to fix this is to produce 3D models by We present a pipeline developed with the aim of helping people "inflating" 2D ones, i.e. by adding a temporal dimension to a model with mild cognitive impairment (MCI) in the accomplishment of pre-trained for image classification. This allows to determine the every-day tasks. Our system adopts a number of computer vision architecture of the 3D network and to bootstrap its values starting methods to analyze RGB videos collected from cameras, and from the corresponding values in the 2D model: convolutional provides a successful, quasi real-time detection of the targeted kernels with dimensions 𝑁 × 𝑁 are inflated to a 3D kernel with activity (drinking) when the latter is at least partially visible to dimensions 𝑁 × 𝑁 × 𝑡 , spanning 𝑡 frames, and each of the t planes the camera. in the 𝑁 × 𝑁 × 𝑡 kernel is initialized by the pre-trained 𝑁 × 𝑁 KEYWORDS weights rescaled by 1/t [1, 9]. Another approach separately analyzes spatial components computer vision, activity recognition, object detection, pose esti- (i.e. single frames), providing static information about scenes mation and objects in the picture, and temporal components related to motion and variation between frames [11]. A two-stream network 1 INTRODUCTION parallelly processes single frames and optical flows, respectively, Mild cognitive impairment (MCI) is a common problem among and then combines their predictions. elders, affecting 15–20% of people over 65 in the USA [10]. In Finally, another method worth mentioning is based on the ob- order to help people affected by MCI in the accomplishment of servation that some actions (i.e., clapping hands) are better char- every-day tasks, we adopt various kind of detection techniques acterized by high-frequency temporal features, whereas other to predict what users are currently doing, which, combined with ones (i.e., dancing) can be better understood when lower fre- a knowledge of their activities schedule, allows our system to quency variations are observed. As a result, a model characterized provide context-based reminders. Here, we present our attempts by two parallel channels can be used. The first (slow) channel to detect one of such activities (i.e. drinking) from videos, by the operates at low framerate and analyzes few sparse frames, in use of computer vision and deep learning algorithms. order to deduce the semantics of the action, while the second This paper is organized as follows. In the remainder of this sec- (fast) branch is responsible for capturing fast variations, and so tion, we give an overview of the current SOTA regarding activity operates at higher framerate [3]. recognition from videos. In Section 2 we describe the computer In this work, we adopted a modified version of an inflated vision techniques used to trigger the more computationally in- 3D network as described in [14], to include non-local blocks. tensive task of activiry recognition, to obtain a quasi real-time Unlike convolutional and recurrent operations, which are only monitoring of the user’s activities. Finally, in Sections 3 and 4 we able to capture spatio-temporal features in a local neighborhood, present the results and conclusions of the paper. non-local blocks compute the response at a certain position as a weighted sum of features at all positions in space and time. This 1.1 Video Activity Recognition allows the model to capture dependencies between pixels that are distant both in space and time, and makes it more accurate Differently than what happened for image classification, where for video classification. in the last years a number of clear front runner architectures and techniques have been established, the topic of activity recognition from videos still presents numerous open issues [1]. 2 SYSTEM ARCHITECTURE An immediate approach to the problem consists in using image classification networks to extract features from each frame of The purpose of our system is to provide users context-based the video; then, predictions for the whole video can either be reminders related to the activity of drinking. To this aim, a RGB obtained by pooling over frames (at the cost of losing information camera is placed in the kitchen of the user’s apartment (where the about temporal ordering) [5] , or by adopting LSTM layers [2]. activity is most likely to take place) and the video is sent through A more elaborate way to adapt the concepts used in image a RTSP stream to a remote server, to be analyzed by the activity classification methods to video recognition consists in using recognition model during the day. The results are uploaded to a 3DCNN, i.e. convolutional models characterized by an additional Cloud Firestore Database, which is queried to determine whether third temporal dimension [4, 12, 13]. The increased number of the users have been drinking enough, and reminders are provided through an app running on a local device if not. Permission to make digital or hard copies of part or all of this work for personal One problem arising from this scheme is that most action or classroom use is granted without fee provided that copies are not made or recognition algorithms are computationally expensive, which distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this prevents them from running in real time. For this reason, we work must be honored. For all other uses, contact the owner /author(s). decided not to run the model continuously, but to execute it only Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia in moments where it is most likely that the users are about to © 2020 Copyright held by the owner/author(s). perform the targeted activity. We employed a combination of 15 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia De Masi, Luštrek • a classic computer vision approach, where the drinking vessel is located through a color/shape-based detection; • a deep learning object detection algorithm, re-trained to detect a personalized mug. In the fist scenario, we applied a series of filters (Gaussian blur, dilation/erosion) to reduce noise, followed by a color mask in the HSV space to select only objects with a certain color. A further selection is then done based on the shape properties of the previously selected areas; a polygonal approximation of their contours is performed, and other shape-related features such as area, circularity and convexity are considered to eliminate shapes different from the expected one. Figure 1: System architecture. Video stream from RGB cameras is sent In the second case, we collected a dataset of about 500 images to a remote server and fed to the activity recognition model. Results are of the selected mug, and used it to re-train a second SSD model. uploaded to a Firestore database, where they are monitored so that notifi- cations can be sent back to an app. In order to account for false negatives in the mug detection, that may occur in some frames even if the mug has not been moved, for each frame the current position of the mug is compared to the classic and deep-learning-based computer vision techniques to history of positions in the past few frames. Once a displacement identify some triggers for the video activity recognition model, of the mug is detected, the trigger is activated. such as: (i) user standing in certain areas of the kitchen; (ii) user standing in certain areas of the kitchen, and interacting with 2.3 Clip Recording and Activity Recognition some objects (tap, fridge); (iii) a specific object, assumed to be Following the activation of one of the triggers, the next video used by the user for drinking, is moved from its current position. frames (for a time interval of about 30 seconds) are used to gener- 2.1 User Localization And Interaction With ate short video clips, each of which has a duration of 10 seconds, the Environment with an overlapping window of 4 seconds. These values have been selected to have a higher probability to obtain at least one The localization of the user and their interactions with the envi- video clip completely capturing the whole drinking process, and ronment are detected through a combination of object detection to match the length of the videos in the Kinetics400 dataset [6], and pose estimation techniques. For the object detection, we which has been used for the activity-recognition model training. adopted a Single Shot MultiBox Detector (SSD) [8], pre-trained on the 80 classes of the COCO dataset [7], which also include 3 RESULTS AND DISCUSSION "person". As for pose estimation, we used a SimpleNet model In this section, we present the results of the various steps involved with a ResNet backbone [15]. in the whole drinking-detection pipeline. During the initial setup, the camera image is shown to the user (Fig. 2a) and regions of interest (ROIs) can be selected (Fig. 2b). 3.1 User Localization - Results These can be of two types, i.e. single or double-zone. The first ones are identified by a single rectangular box, which is activated when We tested the efficiency of the localization module in different the user’s feet are within the box, hence providing indications on scenarios, varying based on how clearly the user was visible (com- the user’s location (see Fig 2c). Double-zone ROIs are formed by pletely visible; legs occluded; head occluded; head and legs oc- two rectangular boxes; one of them, analogously to the previous cluded, only torso visible) and on which side (front/back/right/left) case, is activated when the user steps inside of it, while the second of the user was visible, and the results showed an average accu- box is activated if one of the user’s hands (located by the pose racy of over 98%. estimation model) is within it (Fig. 2d). Overall, a double-zone ROI is considered activated only if both conditions are met. Once 3.2 Drinking Vessel Position Detection - the ROI is configured, the user is requested to input: Results • the name used to identify the current ROI; As illustrated in Sec. 2.2, for the task of detecting the displacement • an observation time 𝑡 (in seconds), i.e. the time after 𝑜𝑏𝑠 of the drinking vessel we adopted two approaches, one based on which the ROI is activated, once the requirements (user classic computer vision methods and one on deep learning. and hands positions) are met; The first method does not provide a confidence score for de- • an action to be performed once the ROI is activated. Cur- tections, nor the coordinates of the object’s bounding box, so rently, only one default action - recording and analyzing we took a simpler approach than with normal object detection video clips - is supported, but this will be extended to algorithms in evaluating the results. We collected some videos include further possibilities. in a home-like environment, with the object located in different positions, or with a person handling it (moving it, using it to 2.2 Drinking Vessel Position Detection drink...), and analyzed them frame-by-frame to check whether A second trigger for activity recognition is given by the displace- the objects present in each frame were detected or not. The re- ment of a particular object (mug, cup, glass). To this regard, in sulting confusion matrix, reported in Table 1, shows that the the pilot phase of the project users will be asked to always use detection algorithm scored precision and recall values of .93 and one specific drinking vessel when they are drinking, which the .90, respectively. This method proved to be very efficient, when model will be trained to recognize. correctly fine-tuned, and the algorithm detected the object in For this task, we considered two possibilities: most of the frames where it was at least partially visible. The 16 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia (a) (b) (c) (d) Figure 2: Triggers based on user’s location and their interaction with the environment. Regions of Interest are selected during the setup phase (b), and they are activated either if the user steps inside (c), or if the user steps inside and has their hands next to another object (d). Table 1: Confusion matrix for the color/shape-based detec- 3.3 Activity Recognition - Results tion of the mug We tested the adopted activity recognition model on a new cus- tom dataset, consisting of roughly 100 videos we recorded our- Pred selves in a variety of environments and conditions. In order to P N make the clips as similar as possible to real-life situations, the P 133 15 True videos contained instances where actions similar to drinking N 10 1 were performed, to increase the recognition difficulty. The clips can be classified as belonging to two difficulty categories, based on the angle the user was facing with respect to the camera; videos were classified as "hard" whenever this angle was greater ◦ greatest issue of the method is that it had to be very carefully than 90 (see Fig. 4). The precision-recall curve for the model on tuned, especially regarding the color selection part, which is still this dataset is shown in Fig. 5. sensible to lightning variations even after converting the image to the HSV colorspace. False detection can also be a problem. 4 CONCLUSIONS We tested the algorithm in situations where some of the objects The tests performed on triggers are very encouraging for the one present in the scene had colors similar to the object we wanted based on the user location and their interaction, and indicate that to detect, and in spite of being able to filter out most of them we the deep-learning approach should be preferable for the detec- still obtained some false positives, especially when the lighting tion of the drinking vessel and its displacement, especially after varied, thus rendering the selection of the parameters for the increasing the amount of training data. The activity-recognition color mask less efficient. model based on inflated 3D CNN with the addition of non-local The results of the evaluation of the SSD model are shown in blocks provided the best accuracy in situations were the user is Fig. 3. As evident from the plot, the model immediately reached facing the camera at least partially, and the use of triggers allows a very high mAP [7], of the order ≈ 0.9, on our test dataset. It for a quasi real time usage. A number of improvements will be should be noted that, while preparing the training dataset, we added to the pipeline in the future. Currently, only one action is followed a somewhat different approach than what is usually triggered, i.e. recording and analysis of video clips, but we plan to done for training object-detection models. In most situations, include other possibilities, such as using the information on the one wants to make the model as general as possible and avoid user location to check whether they need assistance in operating overfitting, which is achieved by taking images of the desired domestic appliances. The object detection model could also be object in as many different conditions (size, aspect ratio, point of extended, in order to identify interactions with other elements view angle, rotation, lightning) as possible. In our case, however, of the environment, and provide corresponding context-based re- the location of the camera will be more or less constant, i.e. sponses. Finally, the only action currently recognized is drinking, attached to the ceiling of the room, in order to provide a good but as mentioned in the introduction the aim of the project is to view of the environment. As a result, this will greatly limit the assist users in the accomplishment of various activities. In this variability in the images of the object the system will analyze, sense, the next planned step is to include detection of parts of especially regarding the aspect ratio and the orientation of the the morning toilet routines, such as brushing teeth and washing mug. Moreover, whereas an object detector is usually tasked to hands. identify many different instances of objects in a certain class (i.e., a generic "mug"), in our case the task is greatly simplified by the fact that we are looking to locate one very specific object. 17 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia De Masi, Luštrek Figure 3: mAP values on the test dataset for the SSD model, re-trained to recognize the project custom mug. [4] Shuiwang Ji, Wei Xu, Ming Yang, and Kai Yu. 2012. 3d convolutional neural networks for human action recog- nition. IEEE transactions on pattern analysis and machine intelligence, 35, 1, 221–231. [5] Andrej Karpathy, George Toderici, Sanketh Shetty, et al. 2014. Large-scale video classification with convolutional neural networks. In Proceedings of the IEEE conference on Computer Vision and Pattern Recognition, 1725–1732. [6] Will Kay, Joao Carreira, Karen Simonyan, et al. 2017. The kinetics human action video dataset. (2017). arXiv: 1705. 06950 [cs.CV]. [7] Tsung-Yi Lin, Michael Maire, Serge Belongie, et al. 2014. Figure 4: Difficulty classes for the custom dataset we used to test the Microsoft coco: common objects in context. (2014). arXiv: activity recognition model. Video clips were classified as "hard" whenever 1405.0312 [cs.CV]. the angle between the user front side and the camera was greater than ◦ 90 . [8] Wei Liu, Dragomir Anguelov, Dumitru Erhan, et al. 2016. Ssd: single shot multibox detector. Lecture Notes in Com- puter Science, 21–37. issn: 1611-3349. doi: 10.1007/978- 3- 319- 46448- 0_2. http://dx.doi.org/10.1007/978- 3- 319- 46448- 0_2. [9] Elman Mansimov, Nitish Srivastava, and Ruslan Salakhut- dinov. 2015. Initialization strategies of spatio-temporal convolutional neural networks. arXiv preprint arXiv:1503.07274. [10] Ronald C Petersen, Oscar Lopez, Melissa J Armstrong, et al. 2018. Practice guideline update summary: mild cog- nitive impairment: report of the guideline development, dissemination, and implementation subcommittee of the american academy of neurology. Neurology, 90, 3, 126–135. [11] Karen Simonyan and Andrew Zisserman. 2014. Two-stream convolutional networks for action recognition in videos. In Advances in neural information processing systems, 568– Figure 5: Test results of the activity recognition model on the test 576. dataset. [12] Du Tran, Lubomir Bourdev, Rob Fergus, et al. 2015. Learn- ing spatiotemporal features with 3d convolutional net- REFERENCES works. In Proceedings of the IEEE international conference on computer vision, 4489–4497. [1] Joao Carreira and Andrew Zisserman. 2017. Quo vadis, [13] Gül Varol, Ivan Laptev, and Cordelia Schmid. 2017. Long- action recognition? a new model and the kinetics dataset. term temporal convolutions for action recognition. IEEE In proceedings of the IEEE Conference on Computer Vision transactions on pattern analysis and machine intelligence, and Pattern Recognition, 6299–6308. 40, 6, 1510–1517. [2] Jeffrey Donahue, Lisa Anne Hendricks, Sergio Guadar- [14] Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaim- rama, et al. 2015. Long-term recurrent convolutional net- ing He. 2018. Non-local neural networks. In Proceedings of works for visual recognition and description. In Proceed- the IEEE conference on computer vision and pattern recog- ings of the IEEE conference on computer vision and pattern nition, 7794–7803. recognition, 2625–2634. [15] Bin Xiao, Haiping Wu, and Yichen Wei. 2018. Simple base- [3] Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, et al. lines for human pose estimation and tracking. In Proceed- 2019. Slowfast networks for video recognition. In Proceed- ings of the European conference on computer vision (ECCV), ings of the IEEE international conference on computer vision, 466–481. 6202–6211. 18 Semantic Feature Selection for AI-Based Estimation of Operation Durations in Individualized Tool Manufacturing Erik Dovgan Bogdan Filipič Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia erik.dovgan@ijs.si bogdan.filipic@ijs.si ABSTRACT very diverse, which increases the difficulty of automated duration Accurate estimation of operation durations is of key importance prediction. in production processes, since the accuracy of estimations di- We propose an approach for predicting operation durations in rectly affects the quality of production plans and thus the entire the manufacturing of individualized tools. The tools are manu- production process. This task is even more challenging when ally divided into several positions of varying complexity, where individualized tools are being produced. From the machine learn- each position is specified with a 3D computer model. In addition, ing point of view, this means a low number of diverse samples, a set of operations are predefined for each of these positions. while the number of features can be significantly higher. To tackle The proposed approach processes the 3D model of each position this issue, we introduce semantic feature selection that reduces and predicts the duration of the corresponding manufacturing the number of features. This results in obtaining a better ratio operations. To this end, it firstly extracts a set of volume, sur- between the number of samples and features and, at the same face, gradient and other features from the 3D model, and then time, reduces the prediction error. We demonstrate the proposed applies the Random Forest regression model [1] to predict the approach on the problem of estimating the operation durations duration of each operation. This process is additionally enhanced in the manufacturing of injection molds and show the predic- with semantic feature selection that evaluates various sets of se- tion accuracy improvement resulting from the semantic feature mantically related features, such as volume features, in order to selection. assess the predictive capability of these feature sets. We demon- strate the proposed approach on the problem of estimating the KEYWORDS operation durations in the manufacturing of injection molds in a specific tool shop. By processing a dataset from this tool shop, injection molding, tool manufacturing, duration prediction, fea- we show the prediction accuracy improvement resulting from ture selection, random forest the semantic feature selection. 1 INTRODUCTION The rest of the paper is organized as follows. Section 2 in- troduces the relevant tool positions and the related operations, The efficiency of tool shop manufacturing processes heavily de- and describes the extracted features and the semantic feature pends on the accuracy of production plans. Inaccurate plans can selection. Numerical experiments and the obtained results are lead to significant delays in production, due date violations, late presented in Section 3. Finally, Section 4 concludes the paper delivery penalties, and even loss of customers. A key step of with the summary of our work and the ideas for future work. planning is accurate estimation of durations of all the operations to be executed in the manufacturing process. The estimation 2 PREDICTING OPERATION DURATIONS can be performed manually by an expert utilizing his/her expert knowledge, or automatically by means of tools such as those WITH AI METHODS involving AI methods as, for example, demonstrated in [3]. Prediction of operation durations consists of extracting features Automated estimation of operation durations with AI meth- from the tool data in the form of 3D computer models, and ap- ods consists of learning a predictive model from the features plying a machine learning model to predict the durations. This extracted from examples of past, i.e., already concluded opera- approach is applied for each tool position and each operation tions and their actual durations, and then applying the model to at this position independently, thus a custom machine learning new operations with known features and unknown durations. model is built and applied for each combination of position and In the case of tool manufacturing, the features can be extracted operation. In addition, when feature selection is involved, a differ- from 3D computer models of already manufactured tools. To ent set of features is considered for each of these combinations. build an accurate predictive model, a large set of already manu- factured tools has to be processed. However, this is not possible 2.1 Relevant Positions and Related in certain cases, for example, when dealing with individualized Operations tools, such as injection molds. This is due to the fact that the tool shops specialized in individualized tool manufacturing typically The tools regarded in this study are injection molds that are used produce only few such tools per year. In addition, these tools are to form the final products made of plastic under high pressure. Although the injection mold is composed of several positions, its Permission to make digital or hard copies of part or all of this work for personal most complex and thus the most relevant positions are the bottom or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and and the top element. These two elements have to be manufactured the full citation on the first page. Copyrights for third-party components of this with the highest precision. Since they are in physical contact with work must be honored. For all other uses, contact the owner/author(s). the final product, any defect of the mold surface would result in Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia a defect of the final product. An example of the injection mold © 2020 Copyright held by the owner/author(s). is shown in Figure 1, where the red color indicates the surface 19 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Dovgan and Filipič that is in contact with the final product. In the dataset used in • volumes of the entire tool position (such as volume of the this study, these two elements are marked as positions 1 and shape and volume of the mold), 30. These positions require a set of operations, where the most • volumes of the holes that are open, and of those that are relevant operations are shown in Tables 1–2. closed, • features for each of 6 directions, i.e., projections (x, y, z, each of them increasingly or decreasingly), for example, direction (z, decreasingly) defines the features obtained from the top-down projection, while direction (z, increas- ingly) defines the features obtained from the bottom-up projection; the features for each direction are as follows: – volumes (including the volumes of holes), – surface area, – number of faces, – number of faces per dm2, – valley features, computed as the height versus width ratio of the valleys (in all valley directions to find the maximum value); this feature is aimed at identifying deep and narrow valleys that are harder to process, – valley height, computed as the height of the valleys in all valley directions to find the maximum value; this Figure 1: Example of a 3D computer model of an injection feature is aimed at obtaining the depth of valleys that mold, https://grabcad.com/library/injection-mold-pc-abs- represents the drill distance, 1 by Mauro Menchini. – gradient features, calculated as the maximum gradient in all directions; this feature is aimed at identifying areas with non-horizontal and non-vertical gradient that are Table 1: Operations at Position 1 harder to process. Since the valley features, valley height and gradient features Operation Description are calculated for each point of the projection, the number of 32 CAM rough features is very high and varies across the tool positions which 31 CAM fine are of varying sizes. To reduce the number of features and obtain 43 CAM erosion a constant number of features independently of the position size, 19 Heat treatment histograms of these features are calculated using expert-defined 23 Measuring machine bins. 36 CNC milling 3 axis, rough The 3D model of each position also contains expert-defined 41 CNC milling 3 axis, fine annotations of the model parts with different colors of model 42 CNC milling 5 axis, fine faces (see the example in Figure 1). These model parts are also 13 Submersible erosion taken into account when extracting features and therefore ob- taining additional features that characterize a feature for each part independently. For example, when calculating the number Table 2: Operations at Position 30 of faces, one feature is obtained for all the faces, and for each part an additional feature is calculated denoting the number of faces on that specific part. The part-specific features are calculated for Operation Description the following features: 32 CAM rough 31 CAM fine • volumes of the holes: total, open, closed, 37 CAM wire erosion • projection features: 43 CAM erosion – volume, 19 Heat treatment – surface area, 11 Wire erosion – number of faces, 23 Measuring machine – number of faces per dm2, 36 CNC milling 3 axis, rough – valley features, 41 CNC milling 3 axis, fine – valley height, 42 CNC milling 5 axis, fine – gradient features. 13 Submersible erosion Examples of parts that are annotated in the 3D computer mod- els include: (1) Free holes, (6) Tolerance holes, (7) Parting surface, 2.2 Description of the Extracted Features (10) Matching surfaces, (12_4) Part shape: High gloss polished, The proposed approach extracts a set of features from a 3D com- (12_5) Part shape: Optical faces, (12_7) Part shape: Galvanic pins, puter model of a tool. These features were suggested by a tool (12_8) Part shape: Special surface finishing. In total, 30 parts are shop expert and can be categorized as follows: annotated by the expert. 20 Semantic Feature Selection for AI-Based Estimation of Operation Durations Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Table 3: Feature Sets The operation durations were predicted with the Random Forest regression model. Its performance was assessed with the Name Number of features leave-one-out test using the default model-building parameters. The selected performance metric was the Root Mean Squared expert 524 on average Error (RMSE), which has to be minimized. RMSE was also cal- volume 6 culated for durations estimated by the expert. The effectiveness volume_projection 30 of feature selection was determined by comparing the Random volume_no_hole 3 Forest performance when using all the features and when using volume_projection_no_hole 6 only a selected set of features. volume_hole 3 The initial experiment aimed at finding whether the prediction volume_projection_hole 24 of operation durations involving the proposed feature selection volume_hole_part 90 outperforms the prediction without feature selection considering volume_projection_no_hole_part 180 all the features (i.e., the default feature set). To this end, for material 4 each combination of position and operation, all the feature sets surface_projection 6 were processed and the feature set with the lowest RMSE was surface_projection_part 180 selected. The results are shown in Figure 2. These results are faces_count_projection 6 normalized with respect to the RMSE of durations estimated faces_count_projection_part 180 by the expert and are therefore expressed as percentages of the faces_per_dm2_projection 6 RMSE resulting from the expert estimation. They show that for faces_per_dm2_projection_part 180 each combination of position and operation, there exists at least valley_hist_projection 18 one set of features that allows for more accurate prediction than valley_hist_projection_part 540 the default feature set (since it reduces the RMSE). In addition, for valley_h_projection 48 position 1, operation 32, and position 30, operation 31, the default valley_h_projection_part 1440 feature set produces a RMSE equal to the RMSE of the expert grad_hist_projection 18 estimation, while feature selection improves it. For position 30, grad_hist_projection_part 540 operation 32, the default feature set results in a higher RMSE projection_* 562 than the RMSE of the expert estimation. Although in this case projection_side 2248 feature selection improves the result, it still performs worse than projection_top_bottom 1124 the expert estimation. part_* 111 Planned by expert 1.2 No feature selection 2.3 Semantic Feature Selection Feature selection 1.0 The total number of features obtained in the presented feature extraction procedure is 3472. Since this is a large number, we 0.8 introduce semantic feature selection that combines semantically similar features into (partially overlapping) feature sets. In addi- 0.6 tion, the tool shop expert also selected a set of the most relevant 0.4 features for each operation. However, this was defined only for a limited set of crucial operations. The resulting feature sets and 0.2 the related numbers of features are shown in Table 3. Specifically, 0.0 if the name of a set contains "part", the set contains all the fea- tures of the specific part. The "valley_hist_" contains the valley (1, 32) (1, 31) (1, 43) (1, 19) (1, 23) (1, 36) (1, 41) (1, 42) (1, 13) (30, 32) (30, 31) (30, 37) (30, 43) (30, 19) (30, 11) (30, 23) (30, 36) (30, 41) (30, 42) (30, 13) features, "valley_h_" valley height, and "grad_hist_" gradient features. Projection sets "projection_" contain all the features from specific projections and are defined as follows: Figure 2: Percentages of RMSE with respect to the RMSE of durations estimated by the tool shop expert. The horizon- • projection_100: projection from left to right (x axis) tal axis denotes the combinations of (position, operation). • projection_200: projection from right to left (x axis) • projection_010: projection from front to back (y axis) Subsequently, the most relevant combinations of positions • projection_020: projection from back to front (y axis) and operations were analyzed in more detail and selected results • projection_001: projection from bottom to top (z axis) are presented in Figures 3–5. These results show the RMSE of • projection_002: projection from top to bottom (z axis) durations estimated by the expert, the RMSE obtained without In total, 60 sets of features were defined. feature selection, and the RMSE obtained with various sets of features. To make the figures readable, we only show the best 3 EXPERIMENTS AND RESULTS 33% feature sets. Figure 3 shows position 1 and operation 36 (i.e., We evaluated the proposed approach on a dataset from the Plam- CNC milling 3 axis, rough). The best features are the gradient tex tool shop [4, 2]. Due to individualized tool manufacturing, features, surface features and features from the bottom-up pro- the number of already produced tools was low, namely 30 in- jection. Note also that the bottom side of this position is the most stances of position 1 and 26 instances of position 30. Besides the complex one, thus the bottom-up projection is of high impor- actual duration of each operation, each instance also included tance. The same projection is also the most relevant for position the duration estimated by the tool shop expert. 1, operation 13 (i.e., submersible erosion) (see Figure 4), since 21 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Dovgan and Filipič the erosion is applied only to the bottom side of this position. Position 30, Operation 13 Part 9 (i.e., released surfaces) and faces count are also among the 45 Planned by expert most important features, where faces count can be used to esti- No feature selection mate the complexity of the surface that has to be eroded. Finally, 40 Feature selection position 30, operation 13 (i.e., submersible erosion) is shown in 35 Figure 5. For this combination, the top-down projection is the most relevant, since the erosion is applied only to the top side of 30 this position. Part 1 (i.e., free holes) and faces count are also very important. The importance of the appropriate projection and the faces count is consistent with the results for position 1 and the part_1 expert part_3 part_5 part_10 same operation (see Figure 4). part_11_5 volume_hole projection_002 projection_100 projection_001 projection_side Position 1, Operation 36 volume_projection surface_projection 10 grad_hist_projection Planned by expert projection_top_bottom grad_hist_projection_part surface_projection_part 8 No feature selection Feature selection faces_count_projection_part volume_projection_no_hole volume_projection_no_hole_part 6 4 Figure 5: RMSE obtained when predicting the duration of operation 13 (submersible erosion) at position 30. expert part_9 volume the prediction accuracy, it includes semantic feature selection projection_001 projection_020 by combining features into semantically meaningful feature sets. volume_no_hole projection_200 projection_side projection_010 projection_100 The experimental results showed that this approach in most cases grad_hist_projection surface_projection valley_h_projection volume_projection projection_top_bottom valley_hist_projection outperforms the expert predictions. In addition, semantic feature surface_projection_part volume_projection_hole selection outperforms the approach with no feature selection. volume_projection_no_hole valley_hist_projection_part A detailed analysis of the proposed feature selection approach showed that there exist meaningful relations between the tool Figure 3: RMSE obtained when predicting the duration of manufacturing operations and the best performing feature sets operation 36 (CNC milling 3 axis, rough) at position 1. for predicting the durations of these operations. In future work we will evaluate additional regression algo- rithms to assess the quality of Random Forest predictions. It Position 1, Operation 13 would be also relevant to analyze the samples for which the pre- diction error is the highest. Special attention should be given to 22.5 Planned by expert the operation for which the presented approach did not outper- No feature selection 20.0 Feature selection form the expert prediction. 17.5 ACKNOWLEDGMENTS 15.0 This work was in part funded by the KET4CleanProduction project "Improved Planning of Manufacturing Processes for Indi- vidualized Tools" where the AI-based solution was developed for part_9 expert the Plamtex tool shop. The authors also acknowledge the finan- part_12_2 part_11_1 cial support from the Slovenian Research Agency (research core projection_001 projection_010 projection_side projection_100 projection_020 funding No. P2-0209). We are particularly grateful to Plamtex volume_no_hole for sharing the tool dataset and the expert knowledge on tool grad_hist_projection surface_projection volume_projection manufacturing, positions, operations, and the suitable features. faces_count_projection projection_top_bottom grad_hist_projection_part valley_h_projection_part surface_projection_part faces_count_projection_part volume_projection_no_hole REFERENCES [1] Leo Breiman. 2001. Random forests. Machine Learning, 45, Figure 4: RMSE obtained when predicting the duration of 1, 5–32. operation 13 (submersible erosion) at position 1. [2] Erik Dovgan, Peter Korošec, and Bogdan Filipič. 2020. Tool- Analysis: A program for predicting the duration of machin- ing operations in the production of tools using artificial 4 CONCLUSION intelligence. Technical report IJS-DP 13195. Jožef Stefan Institute, Ljubljana. We presented an AI-based approach to predicting the operation [3] Mesut Kumru and Pinar Yildiz Kumru. 2014. Using artifi- durations in individualized tool manufacturing, which is, in a cial neural networks to forecast operation times in metal long run, aimed at replacing the existing human-based estima- industry. International Journal of Computer Integrated Man- tion process. The proposed approach extracts a set of features ufacturing, 27, 1, 48–59. from 3D computer models of tools and applies Random Forest [4] Plamtex INT, d.o.o. 2020. https://www.plamtex.si/en/. regression to predict the operation durations. To further improve 22 Generating Alternatives for DEX Models using Bayesian Optimization Martin Gjoreski Vladimir Kuzmanovski Marko Bohanec Department of Intelligent Department of Computer Science Department of Knowledge Systems Aalto University, Finland Technologies Jožef Stefan Institute vladimir.kuzmanovski@aalto.fi Jožef Stefan Institute Jožef Stefan Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia Department of Knowledge marko.bohanec@ijs.si martin.gjoreski@ijs.si Technologies Jožef Stefan Institute Ljubljana, Slovenia ABSTRACT development of qualitative multi-attribute decision models and the evaluation of alternatives (options). DEXi has been used to Multi-attribute decision analysis is an approach to decision analyze decision problems in different domains in healthcare [9], support in which decision alternatives are assessed by multi- agriculture [10], [11], [12], economy [13], etc. criteria models. In this paper, we address the problem of A useful extension of DEX would be the possibility to search generating alternatives: given a multi-attribute model and an for new alternatives that require the smallest change to the alternative, the goal is to generate alternatives that require the existing alternative to obtain a desirable outcome. This task is smallest change to the current alternative to obtain a desirable important for practical decision support [14], however the related outcome. We present a novel method for alternative generation work on generating alternatives for qualitative multi-attribute based on Bayesian optimization and adapted to qualitative DEX decision models is quite scarce. The only related study was models. The method was extensively evaluated on 42 different presented by Bergez [15], in which the focus is on attribute DEX decision models with a variable complexity (e.g., variable scoring (and not on the alternatives), and the starting (current) depth and variable attribute’s weight distribution). The method’s alternative was not taken into a consideration. More specifically, behavior was analyzed with respect to computing time, time to Bergez developed a genetic algorithm for searching a set of the obtaining the first appropriate alternative, number of generated ‘‘worst-best’’ i.e., lowest scores for the input attributes that lead alternatives, and number of attribute changes required to reach to the highest score for the root attribute (the decision model’s the generated alternatives. The experimental results confirmed output), and ‘‘best-worst’’ i.e., highest scores for the input the method’s suitability for the task, generating at least one attributes that lead to the lowest score for the root attribute. appropriate alternative within one minute. The relation between In this study, we developed a stochastic method for the decision-model’s depth and the computing time was linear generating alternatives that require the smallest change to the and not exponential, which implies that the method is scalable. current alternative to obtain a desirable outcome. To avoid combinatorial explosion, the method uses guided search based on KEYWORDS Bayesian optimization. The method is evaluated on 42 different multi-attribute models, method DEX, alternatives, decision qualitative multi-attribute models with a varying complexity. support, Bayesian optimization The method’s behavior was analyzed with respect to several characteristics including: computing time, time to first appropriate alternative, number of generated (appropriate) 1 INTRODUCTION alternatives, and number of attribute changes required to reach Hierarchical multi-attribute models are a type of decision models the generated alternatives. [1],[2],[3], which decompose the problem into smaller and less complex subproblems and represent it by a hierarchy of attributes and utility functions. Such decision models are especially useful 2 DOMAIN DESCRIPTION in complex decision problems [4],[5]. In this study, a set of 42 DEX multi-attribute decision models DEX is a hierarchical qualitative multi-attribute method were used. The models are benchmark mock models, designed whose models are characterized by using qualitative (symbolic) by Kuzmanovski et al. [16]. The decision models are designed attributes and decision rules. The method is supported by DEXi by taking into account properties such as model depth, [6],[6],[7],[8], an interactive computer program for the distribution of attributes' aggregation weights (weights' distribution), and inter-dependency of attributes (input links). Permission to make digital or hard copies of part or all of this work for personal or Table 1 presents a summary of the decision models. The weights' classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full distribution is given with descriptive names: skewed, normal, citation on the first page. Copyrights for third-party components of this work must and uniform. All the attributes in the models are defined with be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia same value scale (low, medium, high), including the input and © 2020 Copyright held by the owner/author(s). the output attributes. Additional assumption is that all attribute combinations are possible. 23 Table 1: Properties of the mock DEX decision models. From the distance function, a similarity function 𝑠 can be also defined as one minus the normalized distance. The distance is normalized using the maximum plausible distance for the specific problem. For example, if 𝑎 ̅ has 20 attributes with possible values between 0 and 2 and each attribute has the highest possible value, and if 𝑐 ̅ has only attributes with the lowest possible value (0), then the maximum distance is 20 * 2. 𝑑( 𝑐, ̅ 𝑎 ̅ ) 𝑠( 𝑐, ̅ 𝑎 ̅̅,̅ ) = 1 − max_𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒 Finally, the optimization function can be defined as: 𝑓( 𝑐, ̅ 𝑎 ̅ , 𝐷𝑀( 𝑐, ̅ ), 𝐷𝑀( 𝑎 ̅ )) 3 METHOD FOR GENERATING 𝑠( 𝑐, ̅ 𝑎 ̅̅,̅ ), 𝑖𝑓 𝐷𝑀( 𝑎 ̅ ) > 𝐷𝑀( 𝑐 ̅) ALTERNATIVES = { 0, 𝑖𝑓 𝐷𝑀( 𝑎 ̅ ) ≤ 𝐷𝑀( 𝑐 ̅) An efficient search strategy is required to generate alternatives where 𝐷𝑀(∗) is the output of the decision model for the specific that require the smallest change to the current alternative to alternative. By optimizing 𝑓 , the method searches for obtain a desirable outcome. A naïve approach would be to alternatives that are as similar as possible to 𝑐 ̅ and improve the generate all possible alternatives, or to iteratively generate output of the decision model (𝐷𝑀( 𝑎 ̅ ) > 𝐷𝑀( 𝑐 ̅)). random alternatives, and to evaluate the outcome for each In order to apply the Bayesian optimization approach, a alternative. However, for reasonably complex decision models, surrogate function (a model), an acquisition function, and a the search space can be enormous, rendering the naïve generator of alternatives, need to be defined. The surrogate approaches unsuitable. model 𝑆𝑀 is a model that estimates the objective function for a A more appropriate approach would be to use informed given alternative as input. Typically, models based on Gaussian search based on the history of previously generated and evaluated Process (GP) [17] are used because by exploiting the mean and alternatives. The history can be used to estimate the search space the standard deviation of the output distribution, we can balance and the behavior of the decision model. Based on that estimation, the trade-off of exploiting (higher mean) and exploring (higher more promising alternatives can be generated. By focusing on standard deviation). Since GP models are computationally the more promising alternatives the search space is reduced, and expensive with the complexity of consequently, the time needed to find the appropriate alternatives 𝑂(𝑛3), ensemble models such as Random Forest (RF) can be also used [18]. In that case, the is also reduced. The next subsections describe a stochastic mean and the variance are calculated based on the predictions of method that uses Bayesian optimization to efficiently generate all base models available in the ensemble. Our method uses RF such alternatives. The method assumes that we do not know the with 1000 decision trees as base models. internal rules by which the decision models operate, thus it falls The acquisition function operates on top of the mean and into the category of ‘‘black-box’’ optimization techniques. standard deviation of the Knowing and utilizing the decision rules might help the search 𝑆𝑀’s output. The final version of the algorithm, but this option was not addressed in this study. method uses the expected improvement (𝐸𝐼 ) as an acquisition function [19]. This acquisition function checks the improvement 3.1 Implementation that each candidate alternative brings with respect to the maximum known value ( µ(𝑆𝑀( 𝑎 ̅ )) − 𝑎𝑏), and scales those The problem of generating alternatives that require the smallest improvements with respect to the uncertainty. If two alternatives change to the current alternative to obtain a desirable outcome have a similar mean value, the one with higher uncertainty can be defined as an optimization problem with two objectives: (𝜎(𝑆𝑀( 𝑎 ̅ )) will be preferred by the acquisition function. (1) improved outcome (desired output) of the decision model, Finally, we need to define the generator of alternatives. Our and (2) maximum similarity between the current alternative 𝑐, ̅ method uses two generators of alternatives: a neighborhood and the new proposed alternative 𝑎 ̅ . For each decision model generator and a random generator. Based on the distance function 𝐷𝑀, one alternative can be defined as a tuple of attributes 𝑎 ̅ = 𝑑 , neighborhood relation can be defined. Two alternatives 𝑎 ̅ 1 ̅̅ (𝑎1,𝑎2, … , 𝑎𝑛), where each attribute can take any value of a and 𝑎 ̅ 2 ̅̅ are considered as neighbors with a degree k, if 𝑑(𝑎 ̅ 1 ̅̅ , 𝑎 ̅ 2 ̅̅) limited set of values. Usually, that set includes ordinal values = k. . The random generator is a generator of alternatives which: (e.g., low, medium and high) and those values can be encoded (1) avoids generating known alternatives; and (2) is conditioned with integers (e.g., 0, 1 and 2). Consequently, a distance 𝑑 by the best-known (with respect to the optimization function) between alternatives can be defined over Euclidean space. The alternative discovered in the previous iterations. specific distance function used by the method is a modified Algorithm 1 presents the implementation of the proposed element-wise difference between the candidate alternative 𝑎 ̅ and method. The function check_promising_values runs the 𝑆𝑀 on a the current alternative 𝑐 ̅ . This distance considers only the set of promising alternatives. This set contains all alternatives attributes for which the candidate alternative has higher values that have been previously generated as neighbors to a specific compared to the current alternative 𝑐 ̅. best alternative, but have not been evaluated with the 𝐷𝑀 𝑎 because the acquisition function has selected other alternatives. 𝑗 − 𝑐𝑗, 𝑖𝑓 𝑎𝑗 > 𝑐𝑗 𝑑( 𝑐, ̅ 𝑎 ̅ ) = ∑ { 0, 𝑖𝑓 𝑎 This enables one final check of the most promising solutions 𝑗 ≤ 𝑐𝑗 which may have been missed because of an earlier bad prediction of the 𝑆𝑀. 24 Algorithm 1: varied, i.e., from low to medium, from low to high, from high to Input: Decision model DM, current alternative CA, medium, and from high to low. This experimental setup resulted Output: best_alternatives # parameters and initialization in 756 different experimental runs. Each experiment was running max_e = 150 # maximum number of epochs for a minimum of 100 epochs, a maximum of 150 epochs, and 50 n_candidates = 10 # candidates per iteration epochs without improvement. The method and the experiments objective_jitter = 0.8 # if an alternative is close to the current best (e.g, 75% as good as the current best , the were implemented in Python, and are available online1. alternative’s neighbors should be checked) random_sample_size = 10000 4.2 Experimental Results best_alternatives = [] surrogate_model = new Random_Forest() The average experiment duration for the models with depth 3 was promising_alternatives_pool = [] less than 5 min. For the models with depth 4, the duration #initial values candidate_alternatives = generate_random_alternatives(10) increased for 3 min and for the models with depth 5 the duration real_objective_values = objective_func(DM, CA, alternatives) increased for additional 3 min. This indicates that the relation surrogate_model.fit(candidate_alternatives, real_objective_values) between the computational time and the model depth is linear. known_alternatives.add(candidate_alternatives, real_objective_values) The final output of the algorithm is a set of thousands of best_alternative,best_score = max(candidate_alternatives different alternatives. However, from a user perspective, only ,real_objective_values) one or just a few alternatives should be enough. Figure 1 presents neighboring_alternatives= gen_neighborhood(best_alternative) while counter < max_e do: the number of epochs required to generate the first alternative for if size(neighboring_alternatives)>0: the most complex models (depth 5). From the figure it can be alternatives_pool = neighboring_alternatives seen that on average, the first alternatives are generated in the else: first 10 epochs. For the less complex models, the number of alternatives_pool = gen_rand_alternatives(best_alternative, random_sample_size) required epochs was less than 5. # get top ranked (e.g., 10) candidates using the acquisition function candidate_alternatives, candidate_scores = perform_acquisition(alternatives_pool, n_candidates) #evaluation of candidate alternatives real_objective_values = objective_func(DM, CA, alternatives) known_alternatives.add(candidate_alternatives, real_objective_values) #update current best and promising alternatives i=0 while i < size(candidate_scores) do: if best_score*objective_jitter <= candidate_scores[i] do: neighboring_alternatives = gen_ neighbourhood(candidate_alternatives[i]) promising_alternatives_pool.add(neighboring_alternatives) if Figure 1: Number of epochs required to generate the first best_score< candidate_scores[i] do: best_alternatives = [] alternative in the final set of alternatives. best_alternatives.add(candidate_alternatives[i]) if best_score==candidate_scores[i] do: In each epoch, the algorithm selects the top 10 alternatives best_alternatives.add(candidate_alternatives[i]) i++ with respect to the optimization score. The higher the score, the #update the surrogate model better the alternatives are. The selected alternatives depend on surrogate_model.fit(candidate_alternatives, real_objective_values) the acquisition function, which in turn depends the predictions of counter++ the surrogate model. Figure 2 present the average optimization end score in each epoch for the most complex models (depth 5). For #peform final check of the promising alternatives best_alternatives = a comparison, the average optimization score of 10 randomly check_promising_values(promising_alternatives_pool,best_alt sampled alternatives at each epoch is also presented (dashed line). ernatives) From the figure it can be seen that the optimization score of the return best_alternatives random samples is significantly lower than the optimization score of the samples selected using the proposed algorithm. 4 EXPERIMENTS Finally, the presented algorithm is stochastic and the optimality of the solution cannot be guaranteed. One metric that 4.1 Experimental Setup presents the quality of the solutions is the number of attribute changes required to achieve the final solution starting from the The method was evaluated with the 42 decision models described current state of the current alternative. Figure 3 presents that in Section 2. For each decision model, nine different randomly metric, which is the same as the distance defined in Section 3.1. sampled starting alternatives (current alternatives 𝑐 ̅ ) were From the figure it can be seen that in the majority of the cases, sampled. Three of those alternatives were with a final attribute the final solution can be reached with less than 5 attribute value low, three with a final attribute value medium, and three changes. Exception of this are the decision models that have a with a final attribute value high. The desirable outcome was also depth 5 and uniform weights’ distribution. 1 Repository link. 25 Figure 2: Average optimization score for the decision models with depth 5. Full line - alternatives generated by the surrogate model. Dashed line - random alternatives. The type of attribute weights is color-coded (blue-normal, Figure 3: Boxplots for the number of changes required to orange-skewed, green-uniform). switch from the starting alternative to the best alternative. This is because these models have a larger number of input Regarding the future work, the proposed method is stochastic attributes and the uniform distribution requires many attributes and the optimality of the final solution cannot be guaranteed. In to be changed in order for that change to be prolonged to the order to do that, the method needs to be validated additionally. aggregate attribute. On the other hand, the models with normal Promising options include comparison of the proposed method and skewed weights’ distribution require smaller number of with deterministic methods and methods that utilize internal rules attribute changes for that change to be propagated to the by which the decision models operate. aggregate attributes. REFERENCES [1] Power, D.J. Decision Support Systems: Concepts and Resources for 5 DISCUSSION AND CONCLUSION Managers. Quorum Books, Westport, 2002. [2] Turban, E., Aronson, J. and Liang, T.-P. Decision Support Systems and We presented a novel method for generating alternatives for Intelligent Systems, Prentice Hall, Upper Saddle River, 7th Edition, 2005. [3] Mallach, E.G. Decision Support and Data Warehouse Systems. Irwin, multi-attribute DEX decision models based on Bayesian Burr Ridge, 2000. [4] Sadok, W., Angevin, F., Bergez, J.-E., Bockstaller, C., Colomb, B., optimization. The main goal of the method was to generate Guichard, L., Reau, R., Messeau, A. and Doré, T. MASC: a qualitative alternatives that require the smallest change to the current multi-attribute decision model for ex-ante assessment of the sustainability of cropping systems. Agron. Sustain. Dev. 29, 447–461, 2009. alternative to obtain a desirable outcome. The method was [5] Munda, G. Multiple criteria decision analysis and sustainable extensively evaluated on 42 different DEX decision models. The development. In: Multiple Criteria Decision Analysis: State of the Art Surveys, Springer-Verlag, New York, 2005. models were with a variable complexity (e.g., variable depth and [6] Bohanec, M. and Rajkovič, V. DEX: An Expert System Shell for Decision variable attribute’s weight distribution). The method’s behavior Support. Sistemica 1(1), 145-157, 1990. [7] Bohanec, M. and Rajkovič, V. Multi-attribute decision modeling: was analyzed with respect to several characteristics: computing Industrial applications of DEX. Informatica 23, 487-491, 1999. [8] Bohanec, M. DEXi: Program for Multi-Attribute Decision Making User's time, time to first appropriate alternative, number of generated Manual." Ljubljana, Slovenia: Institut Jozef Stefan, 2008. (appropriate) alternatives, and number of attribute changes [9] Bohanec, M., Zupan, B. and Rajkovič, V. Applications of qualitative multi-attribute decision models in health care, International Journal of required to reach the generated alternatives. Medical Informatics 58-59, 191-205, 2000. The experimental results confirmed that the method is [10] Bohanec, M., Cortet, J., Griffiths, et al. A qualitative multi-attribute model for assessing the impact of cropping systems on soil quality. suitable for the task i.e., it generates at least one appropriate Pedobiologia 51, 239–250, 2007. alternative in less than a minute, even for the most complex [11] Bohanec, M., Messéan, A., Scatasta, S. et al. A qualitative multi-attribute model for economic and ecological assessment of genetically modified decision models. In the majority of the cases, the computing time crops. Ecol. Model. 215, 247–261, 2008. was lower than that. The discovery of the alternatives was [12] Coquil, X., Fiorelli, J.L., Mignolet, C., et al. Evaluation multicritère de la durabilité agr environnementale de systèmes de polyculture élevage equally distributed throughout the overall runtime. Exception of laitiers biologiques. Innov. Agron. 4, 239–247, 2009. [13] Bohanec, M., Cestnik, B., Rajkovič, V. Qualitative multi-attribute this is the final check performed by the algorithm (see modeling and its application in housing, Journal of Decision Systems 10, check_promising_values in Algorithm 1), which generates the pp. 175-193, 2001. [14] Debeljak, M., Trajanov, A., Kuzmanovski, V. et al. A field-scale decision majority of the alternatives for the more complex models (depth support system for assessment and management of soil functions. 4 and depth 5). The quality of the alternatives was also Frontiers in Environmental Science, 7, p.115, 2019. [15] Bergez, J.-E. Using a genetic algorithm to define worst-best and best- appropriate as in the majority of the cases, the generated worst options of a DEXi-type model: Application to the MASC model of alternatives could be reached by less than 5 attribute changes. cropping-system sustainability. Computers and electronics in agriculture 90: 93-98, 2013. 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PhD thesis, University of Alberta, Edmonton, Alberta, Canada, 2008. 26 Detekcija napak na industrijskih izdelkih Defect Detection on Industrial Products David Golob Janko Petrovčič Stefan Kalabakov Institut Jožef Stefan Institut Jožef Stefan Institut Jožef Stefan Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia david.golob@ijs.si janko.petrovcic@ijs.si stefan.kalabakov@ijs.si Primož Kocuvan Jani Bizjak Gregor Dolanc Institut Jožef Stefan Institut Jožef Stefan Institut Jožef Stefan Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia primoz.kocuvan@ijs.si jani.bizjak@ijs.si gregor.dolanc@ijs.si Jože Ravničan Matjaž Gams UNIOR Kovaška industrija d.d. Institut Jožef Stefan Zreče, Slovenia Ljubljana, Slovenia joze.ravnican@unior.com matjaz.gams@ijs.si POVZETEK zaznavanje napak na industrijskih izdelkih/odkovkih za podjetje Unior d.d. Raziskave so bile narejene v okviru projekta V članku predstavimo različne metode za detekcijo napak na ROBKONCEL ( [1]), ki ga sofinancira Republika Slovenija iz industrijskih odkovkih. Raziskava je bila narejena v okviru Evropskega sklada za regionalni razvoj. Klasični pristopi, ki so projekta ROBKONCEL. Napake, ki jih želimo zaznati, so manjši uporabljeni za detekcijo napak na industrijskih objektih, udarci ter poškodbe na struženi površini. V začetnih poskusih temeljijo na računalniškem vidu ( [2], [3], [4], [5]). V naši smo uporabili metode računalniškega vida ter metode zaznavanja raziskavi uporabimo dva pristopa računalniškega vida, in sicer, napak s tresljaji. Začetni rezultati niso zadovoljivi, vendar detekcijo objektov (angl. »object detection«) ter segmentacijo nekatere metode kažejo vzpodbudne rezultate, ki bi se jih dalo slike (angl. »image segmentation«). Prav tako smo poskusili izboljšati z večjim naborom podatkov. zaznati napake s tresljaji izdelkov. Glede na inicialne eksperimente, ki niso dali optimalnih rezultatov, se v prihodnje KLJUČNE BESEDE usmerjamo na poskuse strojnega učenja z večjim naborom Detekcija napak, računalniški vid, tresljaji, industrijski izdelki podatkov ter drugimi, konkretno laserskim čitalnikom, ki se trenutno kaže kot najbolj perspektivna možnost. Raziskave so ABSTRACT zanimive predvsem zato, ker so pokazale določene težave v In this paper different methods for error detection on industrial uporabi metod strojne inteligence pri delu z industrijskimi forks are presented. Part of the research was done for project produkti. ROBKONCEL. The types of errors that are detected are mostly scratches and dents on smooth metal surfaces. First a computer vision approach is used and then method for detecting errors 2 PRISTOP RAČUNALNIŠKEGA VIDA from vibrations is discussed. Initial results are not encouraging, V tem pristopu se napake na izdelkih zaznavajo iz navadnih slik. but could possibly be improved with larger dataset for training. Podani so primeri brezhibnih izdelkov in primeri z napakami, tipično poškodbami na struženi površini. Algoritmi, ki zaznavajo KEYWORDS napake, temeljijo na pod-področju strojnega učenja, to je Error detection, computer vision, vibrations, industrial products globokega učenja. V zadnjih nekaj letih je področje globokega učenja doseglo izjemne rezultate na področju računalniškega vida, kot npr. detekcija objektov, segmentacija slik ter 1 UVOD klasifikacija slik. Pomanjkljivost globokega učenja je, da zahteva V zadnjem času so z napredkom strojnega učenja ter umetne velik nabor učnih podatkov. V naših poskusih smo, kot rečeno, inteligence napredovali tudi procesi kontrole kakovosti v uporabili dva (pod) pristopa, to sta, detekcija objektov (angl. industriji. Namen naše raziskave je razviti algoritem za »object detection«) ter segmentacija slike (angl. »image segmentation«). Nekaj primerov detekcije napak iz industrijskih Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 27 izdelkih z uporabo računalniškega vida je opisanih v [2], [3], [4] ter [5]. 2.1 Detekcija objektov V pristopu detekcije objektov tipično skušamo poiskati izbrani objekt (to je lahko npr. avto, pešec, kolo, prometni znak itd.). V našem problemu je izbrani objekt napaka na industrijskem odkovku. Za ta pristop smo imeli na razpolago 9 izdelkov, iz katerih smo naredili nabor 46 slik. Slika 2: Nevronska mreža za prepoznavanje objektov, vir: Nabor slik smo nato ločili na učno in testno množico. Delitev [9] je narejena tako, da se isti izdelek ne pojavi v različnih množicah. rezultatih na testni množici. Za boljše rezultate bi očitno Na vsaki sliki v učni množici je bilo potrebno ročno označiti potrebovali več slik in več različnih napak. napako/napake s pravokotniki. Ko imamo označene slike, jih lahko uporabimo za učenje globoke nevronske mreže, ki je sposobna prepoznavanja objektov (napak) v slikah. Nevronska mreža je na začetku sestavljena iz več t.i. konvolucijskih slojev (angl. »convolution layers«), na koncu pa imamo par polno povezanih slojev (angl. »fully connected layers«). Konvolucijski sloji so sposobni kreiranja uporabnih značilk (kot npr. razni robovi in oblike na sliki), ki so nato uporabljene v polno povezanih slojih (glej sliko 1 za primer). V primeru detekcije objektov nevronska mreža v prvem delu odkrije t.i. regije zanimanja (angl. »regions of interest«) na sliki, le te regije so v obliki pravokotnikov. Vsaka regija zanimanja je nato vhodni podatek v drugi del nevronske mreže, katere naloga je klasifikacija dane regije (glej sliko 2). V našem primeru smo uporabili že v naprej zgrajeno in naučeno nevronsko mrežo, ki Slika 3: Detekcija napak s prepoznavanjem objektov smo jo nato »naučili« prepoznavati naše objekte (napake). Nevronsko mrežo, ki smo jo uporabili, se imenuje »Faster RCNN inception« in je bila naučena na podatkovni množici imenovani 2.2 Segmentacija slike »COCO« [6]. Ta nevronska mreža je prosto dostopna ter podprta V segmentaciji slike klasificiramo vsako slikovno točko v s strani Python knjižnice Tensorflow [7]. določen razred (glej sliko 4 za primer). V našem primeru imamo Ko imamo naučeno nevronsko mrežo, klasificiramo določeno samo dva razreda, to sta, »napaka« in »ni-napake«. Tudi v tem sliko kot »napako«, v primeru da mreža zazna napako z več kot pristopu uporabimo (globoke) nevronske mreže za segmentacijo 40% verjetnostjo (glej sliko 3 za primer). V tabeli 1 in tabeli 2 in klasifikacijo. lahko vidimo rezultate mreže na učni množici oziroma na testni Za arhitekturo nevronske mreže smo uporabili arhitekturo, ki množici. je bila uporabljena za podoben problem (glej [5] za podrobnosti). Arhitektura je vidna sliki 5. Nevronska mreža je sestavljena iz Tabela 1: Učna množica: 27 slik, 26 z napako, 1 brez. dveh delov, in sicer, segmentacijskega dela ter klasifikacijskega Točnost: 81%, priklic: 81%, natančnost: 100%. dela. Vhodni podatek v segmentacijski del je črno-bela slika TP FP TN FN objekta, klasifikacijski del pa ima dva vhodna podatka (tenzorja) 21 0 1 5 in sicer gre za dva tenzorja iz segmentacijske mreže. Prvi tenzor je segmentacija (pomanjšane) slike objekta, (na sliki 5 je označen Tabela 2: Testna množica: 19 slik, 18 z napako, 1 brez. kot »segmentation ouput«) to je tenzor debeline 1, kjer vsak Točnost: 10%, priklic: 5%, natančnost: 100% element (ki se ga lahko predstavlja kot slikovno točko) TP FP TN FN predstavlja verjetnost napake. Drugi tenzor pa je predzadnji 1 0 1 17 tenzor v segmentacijski mreži. Izhodni tenzor za klasifikacijsko nevronsko mrežo je Opazimo, da na učni množici dobimo zadovoljivo natančnost, verjetnost, ali slika vsebuje izdelek z napako, za segmentacijsko vendar model ni sposoben generalizacije, kar se vidi v slabih nevronsko mrežo pa je segmentacija pomanjšane slike objekta. Segmentacijski del se uči ločeno od klasifikacijskega. In sicer, se uči iz ročno označenih slik segmentacije. Klasifikacijski del pa se uči iz binarnih oznak (1 pomeni, da ima objekt napako in 0 pomeni, da slika nima napake). V tem pristopu razdelimo podatke na učno, validacijsko ter testno množico (kjer noben izdelek ne more biti v dveh množicah). Nato vsako slikovno točko v sliki označimo, kot napako ali ni-napake. To naredimo za vsako sliko v učni in validacijski množici. Slika 1: Globoka nevronska mreža s konvolucijami, vir: [8] 28 Nevronska mreža nam poda segmentacijo slike ter 3 PRISTOP S TRESLJAJI klasifikacijo slike. Primer izhoda nevronske mreže za Eden izmed ' alternativnih' , vendar potencialno obetavnih segmentacijo je prikazan na sliki 6. pristopov je analiza na osnovi oscilatornega vzbujanja pomika. Na validacijski množici smo določili število epoh za učenje Eksperiment je potekal v laboratoriju odseka E2 na IJS. Pozitiv mreže in sicer smo za segmentacijsko mrežo uporabili 2900 epoh izdelka (dejanski odkovek) smo postavili v negativ (stojalo za in za klasifikacijsko nevronsko mrežo 200 epoh. Za treniranje odkovke – glej sliko 7) ter generirali oscilatorni pomik negativa mreže je bil uporabljen gradientni spust (angl. Gradient Descent) (stojala) s pomočjo generatorja vibracij. Zanimalo nas je, ali bi algoritem s parametrom hitrost učenja (angl. »learning rate«) utegnile poškodbe izdelka na naležni površini s stojalom 10-3. Posamezni rezultati so zbrani v tabelah 3,4 in 5. (negativom) kakorkoli vplivati na sklopitev med izdelkom in stojalom. V ta namen smo opazovali dva signala: vzbujevalni Tabela 3: Učna množica: 43 slik, 29 z napako, 14 brez signal pomika stojala in izmerjeni signal pomika izdelka ter napake. Točnost:100%, priklic: 100%, natančnost: 100% opazovali odnos med obema. Za vzbujanje pomika negativa TP FP TN FN (stojala) smo uporabili sinusni vzbujevalni signal. Meritve 29 0 14 0 pomika izdelka smo opravili z laserskim merilnikom razdalje z visoko natančnostjo. Merilnik kontinuirano meri razdaljo do izdelka, ter nato z numeričnim odvajanjem izračuna hitrost, ki je Tabela 4: Validacijska množica: 25 slik, 21 z napako, 4 brez izhodni signal. Za osnovni preizkus smiselnosti metode smo na napake. Točnost: 64%, priklic: 66,7%, natančnost: 87,5%. enem od izdelkov simulirali napako tako, da smo na naležno TP FP TN FN površino prilepili droben kos izolacijskega traku. Izkazalo se je, 14 2 2 7 da le-ta bistveno vpliva na sklop izdelek-negativ in to nam je dalo upanje, da bi utegnile tudi poškodbe naležne površine izdelka vplivati na sklopitev in s tem na relacijo med pomikom negativa Tabela 5: Testna množica: 28 slik, 21 slik z napako, 7 brez in izdelka. napake. Točnost: 71,4%, priklic: 81%, natančnost: 81% Posnetki meritve izhodnega signala so dolgi 10s. Meritve smo TP FP TN FN opravili pod 4 različnimi nastavitvami vhodnega signala, in sicer: 17 4 3 4 • Nastavitev 1: Amplituda: 0,389 Vpp frekvenca: 50Hz Vidimo, da se je nevronska mreža sposobna naučiti s 100% točnostjo, vendar ima, podobno kot prejšnji pristop, problem z • Nastavitev 2: Amplituda: 0,389 Vpp; frekvenca: 60Hz generalizacijo. • Nastavitev 3: Amplituda: 0,2026 Vpp; frekvenca: 60Hz • Nastavitev 4: Amplituda: 0,2026 Vpp; frekvenca 50Hz Nastavitve so bile izbrane na podlagi izhodnega signala, izkaže se, da za višje amplitude izhodni signal postane šumen. Za ta pristop imeli na voljo 24 izdelkov. Preizkusili smo sledeče možne pristope detekcije napak iz Slika 4: Primer segmentacije slike, vir: [10] signalov: • Ekspertno izbrane značilke ter uporaba klasičnih metod strojnega učenja. • Računalniško generirane značilke ter uporaba 2-slojne nevronske mreže Slika 5: Arhitektura Slika 7: Meritev vibracij Slika 6: Primer segmentacije slike. Levo: original, sredina: ročna segmentacija, desno: modelska segmentacija. 29 3.1 Ekspertno izbrane značilke ter uporaba vhodnega signala, kjer je bila amplituda 0,389 Vpp s frekvenco klasičnih metod strojnega učenja 60 Hz). Najboljše testne rezultate so v tabeli 8. V tem pristopu so značilke, uporabljane v algoritmih strojnega Tabela 8: Osnovni model: logistična regresija. Končni učenja, izbrane na podlagi dobrih izkušenj. Značilke, ki so bile model: AdaBoost izbrane, so se namreč izkazale kot dobre v drugi aplikaciji Točnost Priklic Natančnost F1 strojnega učenja. Izbranih značilk je 22 in uporabljajo osnovne 68 % značilke signala iz časovnega ter frekvenčnega spektra, npr. 3 85 % 76 % 73 % najvišji vrhovi spektralne gostote ter njihove frekvence, energija spektralne gostote, itd. 3.2 Računalniško generirane značilke ter Vsak posnetek odkovka je razdeljen na 10 kosov, kjer je vsak kos 1s dolg posnetek. Za vsak kos se nato izračuna ekspertno uporaba 2-slojne nevronske mreže izbrane značilke. Tako za vsak vzorec dobimo 10 podatkovnih Za avtomatsko generacijo značilk smo uporabili za to namenjeno točk z 22 značilkami. knjižnico. Pri nastavljenem parametru FDR (False Discovery Uporabljen model je sestavljen iz dveh modelov. In sicer iz Rate) na privzeto vrednost, ki je 0,05 po statističnem testu, nismo osnovnega ter končnega modela. Osnovni model za vsako dobili nobene značilke, ki bi bila relevantna za klasifikacijo. Ker podatkovno točko izračuna verjetnost, da ta točka pripada knjižnica uporablja statistično analizo za ocenjevanje produktu z napako. Ker imamo za vsak produkt 10 podatkovnih relevantnosti značilk, torej ni nujno, da niso pomembne pri točk, dobimo z osnovnim modelom 10 verjetnosti za vsak strojnem učenju, zato smo dvignili prag FDR na začetku na 0,5 produkt. Končni model potem klasificira produkt v »odkovek z in nato še na 0,99. Pri tem smo pri vrednosti 0,5 FDR dobili le napako« ali »odkovek brez napake«. Vhodni podatek v končni eno značilko. Ta je 50. Fourierev koeficient oziroma pri model je 10 verjetnosti, dobljenih iz osnovnega modela. nastavitvi 2 in 3 smo dobili 60. Fourierev koeficient. Slednja Preizkusili smo več možnih algoritmov, in sicer algoritem vrednost je seveda osnovni harmonik vzbujalnega signala. Pri podpornih vektorjev (angl. »support vector classifier«), nekaterih nastavitvah in pri večji vrednosti FDR smo dobili algoritem naključnih gozdov, logistično regresijo, algoritem nekatere Fouriereve koeficiente v okolici 50. in 60. koeficienta, »AdaBoost« ter algoritem »XGBoost«. Te algoritme smo kar je smiselno, ker je odziv odkovka različen glede na preizkušali tako za osnovni kot končni model. poškodbo. Zaradi tega smo sklenili, da izračunamo Fouriereve V prvem poskusu, so bili podatki razdeljeni na učno ter testno koeficiente v okolici 50. in 60. in jih uporabimo za klasifikacijo. množico. Na učni množici smo z 8 delnim prečnim preverjanjem Hevristično smo določili, da izračunamo prvih 256 koeficientov. izbrali optimalne parametre za osnovni ter končni model. Nato S tem smo zajeli vse koeficiente v okolici 50. in 60. Izračun smo celoten model testirali na testni množici. prevelikega števila koeficientov pomeni, da lahko porabimo vse Uporabljena je bila nastavitev 2 vhodnega signala, kjer je bila vire, ki so na voljo nevronski mreži, prav tako pa uradni viri [11] amplituda 0,389 Vpp s frekvenco 60 Hz. Rezultati so zbrani v v tem primeru navajajo 28 x 28 točk oziroma vhodnih nevronov. tabelah 6 in 7. Nevronska mreža je sestavljena iz vhodne plasti, ki ima 256 nevronov, nato sledita dve skriti plasti, prva z 16 nevroni, ter Osnovni model: XGBoost druga z 8. Zadnja izhodna plast je sestavljena iz 2 nevronov, ta Končni model: Naključni gozdovi predstavljata poškodovan ali nepoškodovan odkovek. Takšne nastavitve smo dobili od večkratnega testiranja modela Tabela 6: Učna množica: 19 produktov: 12 z napako, 7 brez (optimizacija hiperparametrov). Za razliko od prejšnjega napake. Točnost: 100%, priklic: 100%, natančnost: 100%. pristopa smo uporabili celoten 10-sekunden posnetek za izračun TP FP TN FN koeficientov. 7 0 12 0 Kot v predhodnem primeru smo na začetku uporabili optimizacijo hiperparametrov na učni množici. To pomeni, da Tabela 7: Testna množica: 5 produktov: 2 z napako, 3 brez smo z izbranimi parametri, ki so dosegli najvišjo točnost pri napake. Točnost: 100%, priklic: 100%, natančnost: 100%. modelu nevronske mreže uporabili za učenje modela. Vseh 24 TP FP TN FN učnih primerov smo razdelili na učno (19 primerov) in testno (5 3 primerov). Uporabili smo 5-delno prečno preverjanje kot v 0 2 0 prejšnjem primeru. Ker dobimo 5 vrednosti posameznih metrik, Da se izognemo naključnemu dobremu rezultatu na testni na koncu izračunamo povprečje. Rezultati so zbrani v tabeli 9. množici, uporabimo še drug poskus. In sicer, uporabimo metodo prečnega preverjanja za določanje učne in testne množice. Konkretno uporabimo 5-delno prečno preverjanje, kjer so Tabela 9: Točnost priklic in natančnost brez F1 metrike podatki razdeljeni na 5 delov. Naš postopek ima 5 iteracij, na Točnost Priklic Natančnost vsaki iteraciji je en del podatkov izbran kot testna množica, ostali 48 % 42 % 91 % štirje deli pa so izbrani kot učna množica. Na vsaki iteraciji na učni množici z 8 delnim prečnim preverjanjem izberemo optimalne parametre in naučimo model na učni množici, nato pa ocenimo model na testni množici. Ker uporabljamo 5 delov, 4 ZAKLJUČEK dobimo 5 ocen točnosti, priklica ter natančnosti, iz katerih nato V tem prispevku so opisani pristopi ter modeli za detekcijo napak izračunamo povprečje. (uporabljena je bila nastavitev 2 na industrijskih izdelkih - odkovkih. 30 Rezultati za detekcijo napak z uporabo računalniškega vida in [5] D. 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Review,“ Applied sciences, Izv. 8, št. 11, 2018. 31 Data Protection Impact Assessment - an Integral Component of a Successful Research Project From the GDPR Point of View Gizem Gültekin Várkonyi Anton Gradišek University of Szeged Jožef Stefan Institute Szeged, Hungary Ljubljana, Slovenia gizemgv@juris.u-szeged.hu anton.gradisek@ijs.si ABSTRACT Developing an AI-based service for a target population, for example people with diabetes, chronic heart failure, obesity, Artificial intelligence and algorithmic decision-making systems dementia, skin cancer, etc., typically starts with a research help generate new knowledge about diseases which then help project. One of the key components of such a project is collecting better manage it and assist people in clinical treatment needs. The substantial amounts of data in a pilot study, with participants that blood of such AI systems is personal data that is both used for resemble the target audience for the final service. When planning training or is already the output of the algorithmic assessments. the pilot study, researchers enter a slippery terrain of dealing with This work aims guiding the AI researchers to be familiar with the personal data, as the participants are providing their own data for legal rules binding them while processing personal data within the purpose of the study. For the illustration, we can imagine a their AI-based projects as indicated in the General Data Protection Regulation rules with a specific focus on why and how project where we collect medical data of three types; general to conduct a self-Data Protection Impact Assessment. The self- medical data provided by the medical doctor responsible for the assessment guideline presented throughout the work is an output participant, lifestyle data collected by either wearable or of the mutual experiences and collaboration between a lawyer stationary sensors, and self-reported data that is obtained via and an AI researcher on the topic. questionnaires that the participants fill. KEYWORDS The data provided by the participants fall under the scope of the data protection, impact assessment, GDPR, artificial intelligence, European Union’s General Data Protection Regulation (GDPR) medical data since it refers to identified or identifiable personal issues of them. The GDPR entered into force on the 25th of May 2018 with one of the aims of keeping up with the technological developments 1 Introduction challenging efficient protection of personal data [2]. The risk- It is possible to look out for artificial intelligence (AI) systems based approach embedded in the GDPR came along with several dealing with personal data from two different perspectives. On safeguards as one of them is the Data Protection Impact one hand, it offers great benefits for the users, developers, and Assessment (DPIA). The DPIA can help AI-researchers to researchers, if used correctly. For example, AI-enabled health comply with the GDPR requirements at an early stage of a new care technologies could predict the treatment of diseases 75% project. It can help reduce the risks arising from the use of AI better, and could reduce the clinical errors 2/3 at the clinics using technologies challenging the efficient protection of fundamental AI compared to the clinics that do not [1]. On the other hand, the rights and principles [3]. Several policy papers generated by the improper handling of personal data can quickly lead to abuse, EU institutions [4] [5] focusing on regulation of AI state that sharing sensitive information, or other problems (unwanted data legal compliance is a keyword for gaining user trust and DPIA is disclosure, complex and costly legal procedures, high fines, etc.), one way to reach user trust. However, there is no standard set for therefore it has to be handled with the utmost care. In this paper, conducting a DPIA that could guide the AI-researchers. In this we will focus on the legality of medical applications containing paper, we present some of the key points of conducting the DPIA personal data that is defined as sensitive data in legal documents, that could be useful for the AI-researchers. such as the analysis of sensor data to help patients with chronic diseases manage their condition and improve the quality of life, or to help the elderly with independent living by providing safety 2 Data Protection Impact Assessment in the features and improved communication channels. GDPR The term DPIA was not specifically described in the GDPR, however, was referred as it is a process to help managing the risks to the data subjects’ (participants of the research project, in this Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed case) rights and freedoms as a result of data processing. In other for profit or commercial advantage and that copies bear this notice and the full words, DPIA is a process consisting of several other sub- citation on the first page. Copyrights for third-party components of this work must processes to describe the risks and assess the legality of the be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia system in terms of data protection. These risks could be related © 2020 Copyright held by the owner/author(s). to system security, system design, implementation, 32 administration and development on a further run. The aim of the The Data Specific Assessment (DSA) is the procedure where DPIA is to take appropriate safeguards to minimize the risks, if the data to be used in the AI project should be introduced very impossible to eliminate all. DPIA is not a simple one-time specifically in order to comply with the basic rules of the GDPR, reporting activity, it is an ongoing process that should be mainly, the purpose limitation, transparency, accuracy, data continuously carried out during the lifetime of a project, minimization, and consent. It should be kept in mind that one of therefore DPIA should always be monitored and updated [6]. the requirements to be ensuring a valid consent is identifying the concrete data list, together with the planned processing activities It is the AI-researcher’s responsibility to convey a DPIA when of that data in the frame of a research project. Information the data processing activity is likely to constitute a “high risk” to serving to identify the persons involved with data processing are the rights and freedoms of natural persons (e.g. users of an AI the natural elements of the DSA. For example, AI-researchers in service who both benefit from the service and contribute to it the project should identify the data processing purposes specific with their data). How to decide whether a certain data processing to the project aims and present the list of purposes in a written activity would be resulting in a high risk is not an easy task, but form to the participants. The indicated purposes should follow there are several guidelines and list of processing requiring DPIA the related data to be processed listed again in a written form, published by the National Supervisory Authorities [7]. These followed by the clear identification of the AI-researchers and lists could be the first sources for the data controllers to decide other people involving the processing activity. about the necessity of the DPIA for a certain project [8]. Next, the Data Subject Specific Assessment should follow the Failure to conduct a right DPIA raises a risk for the AI- procedure where the focus is on explaining all the details about researchers; they may face several sanctions, especially financial how the AI-researchers will ensure the rights of the participants penalties. Apart from that, conducting a right DPIA would be by protecting their informational self-determination right. The beneficial for the data controllers not only from the legal and the key point in this assessment is to gain trust of the participants as financial point of view. A DPIA could help data controllers to required by law and ethics. One of the key aspects here is to make avoid implementing irrelevant solutions from the beginning of sure that the participants are introduced by the project team on the project which may refer to assessing the technical feasibility the ways their data will be used, as well as the possibility for of the system in parallel with the legal compliance [8]. Therefore, them to request removal of their data if so desired. The project the DPIA could help data controllers to save time and money. It team shall also ensure that the participants have a certain degree also prevents the companies from losing their reputation (or from of accession to the decisions made by the algorithm about them. the scandals, as such occurred with the Cambridge Analytica, Explaining an algorithmic decision relating the participants’ Equifax, Facebook, etc.). Finally, a DPIA document can prove personal assessment should be understandable to them since the the trustworthiness of the project team before the public, as well classification models based on decision trees are easily as the related authorities, since it is an evidence of the respect comprehensible to humans. On the other hand, models that are towards the right to data protection. based on complex multilayer neural networks are essentially black boxes where it is not possible to determine why a particular An AI project aiming to collect personal data and evaluate the decision was reached based on easily interpretable rules. Bearing data with an automated decision-making system with the help of in mind the black box nature of the algorithmic assessment, profiling tools such as surveys and hardware equipment must be choosing a model that is firstly understandable and explainable assessed from the risk point of view. Below, we present a step- to the AI-researchers is a suggested action in this sense. The by-step guideline on how to conduct a DPIA on AI-based social implications of choosing a black box algorithm is an research. emerging research field. Finally, the project team should ensure that the system offers tools for the participants to keep their data accurate and to block third party access. 3 Conducting a Data Protection Impact Assessment The Project Specific Assessment is the last part of the DPIA, In this section, we assume a project aiming at developing a presenting and explaining the legal basis for data processing, the medical software with the help of an algorithm that is going to external project partners involved with data processing activities, enable collecting and processing participants’ sensitive data and the security measures that will be implemented to safeguard based on profiling. Additionally, a large amount of data will be the data processed during the project. As the project likely deals collected for feeding the algorithm, meaning that the participants with sensitive medical data, security protocols have to be may lose a degree of control of their data stored and processed elaborated, which include proper hierarchy regarding the data by the AI system. Based on these inputs, the project may reveal access, encryption algorithms, regular security updates, and risks for rights and freedoms of the data subjects involved, if physical access to the hardware where the data is located. these are not mitigated. Therefore, we need to conduct a DPIA and identify the risk categories with the planned mitigations. The final but an ongoing phase of the DPIA is the monitoring phase. Whenever there is a new element embedded in the project, We identified three steps for conducting a successful DPIA in the and this element seems to change the balance of the risks that project: the Data Specific Assessment, the Data Subject Specific were assessed earlier, the DPIA should be reviewed. This Assessment, and the Project Specific Assessment. element could be involving a new data type in the algorithm or planning a commercial use of the algorithm. Bearing in mind the fact that machine learning techniques and algorithms are referred 33 to as entirely new technologies [3] and the growing amount of risks and find mitigation strategies for certain weak points. Last data together with a variety of hardware would raise risks to but not least, by conducting the DPIA, the project team fulfills persons’ right to data protection [9], we suggest the project team the legal requirements, ensures higher trust of people involved, to review the DPIA periodically, for instance, every year at least. and avoids unforeseeable problems that might later occur. ACKNOWLEDGMENTS 4 Conclusion This work was supported by the ERA PerMed project Data Protection Impact Assessment is an integral part of any BATMAN, which was financed on Slovenian side by the research project focusing on development of an AI algorithm Ministry of education, science, and sport (MIZŠ). An extended with personal data. Such data might be sensitive in nature, such version of this paper was submitted to journal Informatica. as medical data, to be used for developing an algorithm to detect diseases. Besides it is a legal requirement as provided for by the GDPR, a DPIA is a tool for the AI-researchers to assess the REFERENCES weaknesses in the system that may then risk the protection of fundamental rights of the persons participating in the research [1] “The AI effect: How artificial intelligence is making health care more project who contribute to the development of the project with human”, [Online], study conducted by MIT Technology Review Insights and GE Healthcare, 2019. Accessed from: their personal data. Since there are few guidelines on how to https://www.technologyreview.com/hub/ai-effect/ Last accessed: 20 conduct a DPIA for a research project specific to the topic, this April 2020. [2] EDPS (2012). “Opinion of the European Data Protection Supervisor on work initiates a step-by-step guideline for the AI-researchers. the data protection reform package”, (7 March 2012). [3] ICO (2018). Accountability and governance: Data Protection Impact The first step considers a Data Specific Assessment that the data Assessments (DPIAs). [4] European Commission (2018). Communication from the Commission to and the purposes of the data processing are clearly identified and the European Parliament, the European Council, the Council, the listed in a written form to be presented to the participants. It is European Economic and Social Committee and the Committee of the Regions, Artificial Intelligence for Europe. COM (2018) 237 final. followed by the Data Subject Specific Assessment which focuses [5] European Commission (2018) Communication from the Commission to on the ways the AI-researchers ensure the protection of the the European Parliament, the European Council, the Council, the participants’ right to data protection in line with the GDPR European Economic and Social Committee and the Committee of the Regions, Coordinated Plan on Artificial Intelligence. COM (2018) 795 requirements. Such requirements include providing explanation final. on the decisions reached as a result of algorithmic assessments. [6] Wright, David. (2012). The state of the art in privacy impact assessment. Computer Law & Security Review, 28(1), 54–61. The third step relates to the Project Specific Assessment and this https://doi.org/https://doi.org/10.1016/j.clsr.2011.11.007 step focuses mostly on the security measures planned to be taken [7] Hungarian National Authority for Data Protection and Freedom of Information (NAIH), List of Processing Operations Subject to DPIA 35(4) by the project team to mitigate the risks that appeared during the GDPR https://naih.hu/list-of-processing-operations-subject-to-dpia-35-4- previous two assessments. We would suggest the AI-researchers -gdpr.html review the DPIA at least once a year, otherwise revision is [8] Wright, David. (2011). Should Privacy Impact Assessments Be Mandatory? Commun. ACM, 54(8), 121–131. required whenever a new element is added to the system ending https://doi.org/10.1145/1978542.1978568 with a new data processing. [9] Chandra, Sudipta., Ray, Soumya., Goswami, R.T. (2017). Big Data Security: Survey on Frameworks and Algorithms, in 2017 IEEE 7th International Advance Computing Conference (IACC), Hyderabad, pp. From the planning stage of the project to the annual revisions, 48-54. doi: 10.1109/IACC.2017.0025 the DPIA could help the project team to identify the potential 34 Deep Transfer Learning for the Detection of Imperfections on Metallic Surfaces Stefan Kalabakov Primož Kocuvan Jani Bizjak stefan.kalabakov@ijs.si primoz.kocuvan@ijs.si jani.bizjak@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Mednarodna podiplomska šola Ljubljana, Slovenia Mednarodna podiplomska šola Jožefa Stefana Jožefa Stefana Ljubljana, Slovenia Ljubljana, Slovenia Samo Gazvoda Matjaž Gams samo.gazvoda@gorenje.com matjaz.gams@ijs.si Gorenje gospodinjski aparati, d.d. Jožef Stefan Institute Mednarodna podiplomska šola Jožefa Stefana Ljubljana, Slovenia ABSTRACT image processing for detecting imperfections in the manufac- In the last decade, consumers’ expectations have significantly turing processes [1]. However, these systems rely heavily on increased regarding the availability and quality of the products specialized lighting solutions in order to highlight imperfections they buy. To this end, manufacturers have focused on streamlin- on the surfaces of objects [6]. The systems are usually expensive ing their manufacturing lines by employing intelligent solutions and require close proximity to the object which is being investi- wherever possible. Since the field of quality control remains de- gated in order to provide good detection accuracy. Furthermore, pendent mainly on specialized workers, interest in incorporating methods which do not use any kind of learning require features artificial intelligence (AI) advances in this field has dramatically which are hand-crafted for each application specifically and re- increased. In this paper, we present a short exploration into a quire some degree of uniformity in size and shape of the errors computer vision system built to detect imperfections on metallic which might appear. This problem with hand-crafted features, for surfaces. In particular, we leverage deep transfer learning to build us, exists even when using classic machine learning models, as a model that can classify small segments of a bigger image while we were not provided with details regarding the size and shape of using a tiny dataset for training. In these initial experiments, we the errors. To solve this, we opted to use deep learning models, as show that layers trained on the ImageNet dataset can be used as they automatically extract features based on the training set and feature extractors when building a model for a vastly different have proved to produce state-of-the-art results in many areas problem. [3]. With this in mind, the aim of this paper is to investigate low cost state-of-the-art deep learning methods which work in KEYWORDS suboptimal lighting and which automatically extract features which are robust to the shape and size of the errors which appear deep transfer learning, computer vision, quality control on metallic surfaces. Finally, since our dataset is extremely small, we leveraged transfer learning in order to use the full potential 1 INTRODUCTION of deep models. Today, products are expected to be available fast, in vast quan- tities, and with exceptional quality. To this end, manufacturers have started streamlining their manufacturing lines by employing network-connected intelligent machines wherever possible [10]. This has created great interest in incorporating advances in arti- 2 PROBLEM DEFINITION ficial intelligence (AI) in the industry. In recent years industrial The ultimate goal of the ROBKONCEL project is to create a quality adoption of AI is becoming more and more feasible [7], mainly control process for the detection of several possible manufactur- thanks to the significant progress in hardware computational ing errors on both the inside and outside of ovens. In this work, resources. we focus on detecting scratches and dents, i.e., imperfections on In spite of this, quality control is one manufacturing process the oven faceplates’ metallic surface. We perform this quality which still remains highly dependent on expert human workers. check in the manufacturing process’s final phases, as almost fully This dependence, in some instances, makes it slower, more prone assembled ovens get transported on a conveyor belt. In order to to errors, and more expensive. To mitigate this, there has been produce a method that is least costly to implement, we chose a limited adoption of computer vision systems paired with classical simple RGB camera as the sensor in this application. The camera is positioned such that it can take a picture that contains the Permission to make digital or hard copies of part or all of this work for personal whole metallic surface while not interfering with other quality or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and control processes, thus improving efficiency. Finally, our method the full citation on the first page. Copyrights for third-party components of this is supposed to highlight the areas where dents and scratches work must be honored. For all other uses, contact the owner/author(s). are found so that an inspection of the algorithm’s work can be Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia done at any time. Figure 1 shows an example image used for the © 2020 Copyright held by the owner/author(s). purposes of this paper. 35 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Kalabakov, et al. Figure 1: An image taken by an RGB camera of the metal- lic surface of interest. Figure 3: Example of image segmentation. 2.1 Data Due to the frequency with which these imperfections occur, we Finally, since the newly constructed windows will be used to did not have a large dataset to include in this study. On the con- train a deep learning model, we need to assign a label to each trary, the number of faceplates we could use to get the necessary one of them. In this application, the labels are "0" and "1". If the number of images was only five. Of those five faceplates, one was label "0" is assigned to a window, it means that the window’s without imperfections, and the rest contained a varying number area does not include any scratches or dents on the surface. On of defects on the metallic surface. Since any deep learning re- the other hand, the label "1" means that the area covered by the quires a large amount of data and since the number of faceplates window includes a scratch or a dent. The labels are assigned to is small, using images that portray the whole area of one faceplate each window by examining the mask. For each window, we take as examples to a deep neural network (DNN) would be ineffective. the corresponding area it covers in the mask, and if it includes To combat this problem, we took images of the different front a certain number of pixels annotated as belonging to an imper- panels (five images in total) and segmented them into hundreds fection, then the window is assigned a label "1". Otherwise, it is of smaller examples, which we use as inputs to fine-tune several assigned the label "0". The number of pixels that are used as a models. Additionally, by performing class-invariant transforma- threshold for labeling the windows is: tions on these smaller images, we attempt to diversify the set of examples used to fine-tune the models. The segmentation of im- 𝑡 ℎ𝑟 𝑒𝑠ℎ𝑜𝑙𝑑 = 0.1 × 𝑛𝑢𝑚𝑃𝑖𝑥𝑒𝑙𝑠𝐼 𝑛𝑊 𝑖𝑛𝑑𝑜𝑤 ages into smaller examples and their augmentation are presented in subsection 3.1 and subsection 3.2, respectively. 3.2 Augmentation Augmentation of images in the data-space has been shown to 3 METHOD produce great results when it comes to improving the accuracy 3.1 Segmentation of classifiers [5]. Since after segmenting the image, the number In order to segment the images, we first created a hand-annotated of examples (windows) that do not contain an imperfection is set of binary images (masks). These masks complement the orig- largely greater than the number of examples that do, we apply inal set of five images by showing where in them, a scratch or a certain transformations to the windows that contain an error, and dent is visible on the metallic surface. In more detail, the masks we save each of those transformed windows as a new example. were produced by having humans mark the exact locations of It is important to emphasize that none of these transformations these imperfections. In the masks, pixels which are part of some affect the example’s label, meaning that if we apply them to an imperfection (in the RGB image) are marked with the color white, example containing an error, the transformed example will also while all others are represented in black. An image and its corre- contain the same error. The transformations we use are: sponding mask are shown on Figure 1 and Figure 2, respectively. • rotation • change of contrast • change of brightness • flipping After applying these transformations to a single example, 23 new samples are obtained. Figure 2: A mask constructed for the image in Figure 1. 3.3 Deep Transfer Learning For the task of classifying windows based on whether they con- The next step in the segmentation process is to divide the tain an imperfection or not, we tested four different model archi- image into chunks (windows). We do this by "sliding" a window tectures. One is a simple Convolutional Neural Network (CNN), with a fixed size across the whole image. Each of these windows and the other three are more complicated architectures that are covers a specific area of the image and will serve as a training or well established in the world of image recognition. testing instance when fine-tuning the models. Overlap between The simple CNN is used as a baseline for what an end-to-end several windows is allowed in fact, it is encouraged, seeing that model can achieve on this dataset. However, since the number some overlap means that we can generate more examples. The of examples is still relatively low, training an end-to-end deep size of the window is 200 by 200 pixels and the allowed overlap learning model was not expected to yield great results. between windows is 75%. On the other hand, the VGG16 [8], InceptionV3 [9] and ResNet101V2 However, since in this paper’s scope, we are only interested [2] architectures were used to leverage deep transfer learning [4]. in the faceplate’s metallic parts, we make sure that none of the To be more specific, all of these networks have been used in the windows cover an area that includes the display. In Figure 3 we ImageNet competition, and their internal parameters (weights), can see (in green) the windows produced by the segmentation from that competition, are openly available for use. By using step and how none of them overlap with the area of the display. their pretrained convolutional layers as feature extractors and 36 Deep Transfer Learning for the Detection of Imperfections on Metallic Surfaces Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia training our own set of fully connected layers, we can signifi- clusters. This dismissal is possible because finding the exact mar- cantly improve our performance and training time. Effectively, gins of the imperfections is not of great importance in our use we transfer the knowledge stored in their parameters (weights) case. from the ImageNet dataset to our quality control problem. To implement this, in every architecture, we disregard the fully connected layers included with these architectures and generate our own (with random weights). We then attach these fully con- nected layers to the output of the convolutional layers (provided as pretrained on ImageNet) and train only the fully connected layers while freezing the convolutional layers’ parameters. The number of fully connected layers we generate is four, and the number of neurons per layer is 512, 256, 128, and 64, respectively. The implementation and the weights of these models are ac- quired from the Keras package in TensorFlow. 4 EVALUATION Figure 4: Example of the custom visualisation metric. The 4.1 Experimental Setup top image has the colors of the windows selected based on We evaluated the performance of each model using Leave One the groundtruth, while the middle one has them selected Image Out (LOIO) cross-validation. This means that models are based on the predictions of the classifier. The bottom im- trained using examples (windows) from all images but one, and age represents a color-coded version of the difference be- are tested using the instances from the image excluded in the tween the top two images. training process. The process is repeated several times, and each time a different image is used to test the models’ performance. Since one of the faceplates did not have any errors on its surface, 5 RESULTS AND DISCUSSION windows from that image were never used to test models, instead Table 1 shows the average (macro) F1-scores that each of the they were always used for training. In summary, all the models models achieved when performing 4-fold LOIO cross-validation. are evaluated using a 4-fold LOIO cross-validation. 4.2 Evaluation Metric In this work, we use F1-score with macro averaging as the metric for the evaluation of the models. In particular, we use (macro) Table 1: Average model F1-score after 4-fold LOIO cross- F1-score to determine the model’s ability to classify segmented validation. windows. The choice to use (macro) F1-score rather than accu- racy was made because of the class imbalance in our data. A significant difference between accuracy and (macro) F1-score In all of our experiments, the Simple-CNN and VGG16 archi- comes from the fact that accuracy reports a higher value, even tectures produce very low results. It is our opinion that perhaps, in many false positives. For example, a high accuracy score will a simple stacking of convolutional layers is not enough for this be reported when a classifier predicts only positive values on particular use case, since both networks are unable to learn and a test set containing many positive examples, even though the instead predict every example as an example with an error. On the classifier completely misclassifies the negative instances. other hand, InceptionV3 and ResNet101V2 produce good results To fully understand the classification results, aside from the F1- in comparison to the other two architectures. A head to head score metrics, we also visually represent how the predictions look comparison of the per image F1-scores of the two best models once all windows have been rearranged in their initial positions. can be found in Table 2. This representation overlays windows in their original places but changes their pixels’ value to all white or black based on their predicted values. An example of this representation is shown in the middle image in the triplet on Figure 4. The top image in that same figure changes the pixels’ values based on the ground-truth rather than prediction value. Finally, the figure’s bottom image represents a color-coded version of the difference between the top two images. Windows in green represent windows which Table 2: Per image F1-scores for the InceptionV3 and have been predicted as containing a fault, when in fact they do ResNet101V2 models. contain a fault (True Positive - TP). Windows in red represent windows which have been predicted as not containing a fault, when in fact they do contain a fault (False Negative -FN). And Although there is only a small difference between the F1-scores finally, windows in blue, represent windows which have been of InceptionV3 and ResNet101V2, only 2% as seen on Table 1, predicted as containing a fault, when in fact they do not contain there is a large difference in how they predict the same images, a fault (False Positive - FP). as we can see in Figure 5 and Figure 6. This view is especially useful for our evaluation since it allows As is clearly visible, ResNet101V2 produces a lot more false us to filter out wrongly classified windows which surround green positives in comparison to InceptionV3. However, if we consider 37 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Kalabakov, et al. surfaces should be detected. Based on the results it seems that transfer learning is a suitable tool for use when the target dataset is really small, even in the case when the source and target prob- lems are vastly different. Furthermore, it seems like more complex architectures produce better results compared to more traditional ones. When more examples of faceplates with imperfections be- come available, we plan on exploring the effects of fine tuning some of the convolutional layers in these models rather than freezing all of them during training. Another possible path to take in the future includes using GANs in order to generate real- istic looking samples of windows with imperfections and further augmenting our training set. Finally, it is important to note that exploring more appropriate lighting solutions might produce better results. ACKNOWLEDGMENTS Figure 5: Visual representation of the predictions pro- Part of this research was done under and for ROBKONCEL project. duced by the InceptionV3 model. Additionally, this research was partly funded by the Slovene Hu- man Resources Development and Scholarship Fund (Ad futura). REFERENCES [1] Fernando Gayubo, José Luis Gonzalez, Eusebio de la Fuente, Felix Miguel, and Jose R Peran. 2006. On-line machine vision system for detect split defects in sheet-metal form- ing processes. In 18th International Conference on Pattern Recognition (ICPR’06). Volume 1. IEEE, 723–726. [2] Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Identity mappings in deep residual networks. In European conference on computer vision. Springer, 630– 645. [3] Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. nature, 521, 7553, 436–444. [4] Maxime Oquab, Leon Bottou, Ivan Laptev, and Josef Sivic. 2014. 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In this paper we presented a deep transfer learning approach to quality control in the case where imperfections on metallic 38 Fall Detection and Remote Monitoring of Elderly People Using a Safety Watch Ivana Kiprijanovska Jani Bizjak Matjaž Gams Department of Intelligent Department of Intelligent Department of Intelligent Systems Systems Systems Jožef Stefan Institute, Jožef Stefan Institute, Jožef Stefan Institute, Jožef Stefan International Jožef Stefan International Jožef Stefan International Postgraduate School Postgraduate School Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia ivana.kiprijanovska@ijs.si jani.bizjak@ijs.si matjaz.gams@ijs.si ABSTRACT puts a burden on the health-care system with over-crowded nursing homes and hospitals, and causes higher health-care As seniors age, the risk of unforeseen accidents that affect their expenditures [4]. Therefore, monitoring the day-to-day routine well-being increases. Therefore, monitoring the day-to-day of the elderly who live alone is an important precaution to routine of elderly people is an important precaution to undertake. undertake, especially when they are living alone. Due to the Remote health monitoring systems are essential for rapid demographic change and aging of the population, the enhancing care in a reliable manner and allow the elderly to development of remote monitoring systems has become the remain in their home environment rather than in expensive center of attention for both researchers and industries. In this nursing homes [5]. Such systems also allow communication paper, we present the design of a safety watch integrated in a with remote healthcare facilities and caregivers, thus allowing comprehensive health monitoring system capable of observing healthcare personnel to keep track of the elderly’s overall the elderly remotely. It integrates low-power hardware condition and respond, if necessary, from a distant centralized architecture and energy-efficient software configuration, which facility [6]. Due to the rapidly increasing aging population, such significantly extend the battery autonomy of the device. One of technologies have become a subject of interest for both the major modules running on the safety watch is the automatic researchers and industries. detection of falls and similar dangerous situations. For that One of the first remote monitoring systems presented in the purpose, several machine learning methods were tested, among literature are camera-based systems. They are capable of which the Random Forest method achieved the highest recognizing complex gait activities, but restrict the movement accuracy in detection of falls on data recorded from 17 of the user within a specific range. Apart from that, they are participants, and was implemented on the actual device. complex, expensive and often related to privacy concerns. A recent survey gives an insight to the studies carried out in KEYWORDS vision-based patient monitoring [7]. In the last few years, Safety watch, remote monitoring, energy efficiency, fall wearable motion sensors have gained in popularity for detection monitoring human activities in real time. They can monitor and record real-time information about one’s physiological condition and motion activities. Wearable sensor-based health 1 INTRODUCTION monitoring systems may comprise different types of sensors More than 90% of the elderly desire to live in their own homes that can be integrated into textile fiber, clothes, and elastic for as long as they possibly can [1]. However, as seniors age, bands or can be directly attached to the human body. One such the risk of unforeseen accidents that affect their well-being system in presented in [8], which uses mobile phone as an increases. For example, the lives of elderly people are very intermediary to get vital data from various sensors and transmit often affected by falls, which lead to not only physical injuries data to a server for further processing. The main limitation of but also psychological consequences that further reduce their this system is the fact that the analysis is not performed in the independence and decrease the quality of their life [2][3]. The place where the signal is acquired, and there may be a loss of lack of independence causes them to no longer feel comfortable efficiency in the wireless network when physiological signals with living alone, forcing them to move into nursing homes. It are sent. Another wearable personal healthcare system is presented in [9]. It employs a number of wearable sensors to continuously collect users’ vital signals and uses Bluetooth Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or devices to transmit the data to a mobile phone, which can distributed for profit or commercial advantage and that copies bear this notice and perform on-site vital data storage and processing. After local the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). data processing, the mobile phone periodically report users’ Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia health status to a healthcare centre. Apart from such systems, © 2020 Copyright held by the owner/author(s). various wearable commercial products are available on the 39 market, for example the biometric shirt by Hexoskin, and fitness trackers by Fitbit and Jawbone. However, many current solutions either provide insufficient functionalities at a reasonable price or are advanced but too expensive, too energy demanding or too invasive [10]. The aim of the HomeCare2020 project was to provide a comprehensive solution for a smart healthcare monitoring system, capable of observing the elderly remotely, while eliminating the problems mentioned before. The system aimed to enable the elderly to live home independently until later age and to make them feel safer and more confident in performing everyday tasks and activities. The developed system integrates two interconnected devices: advanced touch-screen care-phone (HomeTab) and a multifunctional safety watch. In this paper, Figure 2: Safety watch appearance the design of the safety watch is presented. From a software perspective, the design principle behind the 2 SAFETY WATCH DESIGN safety watch is to preserve the battery autonomy of the device. Therefore, the main processing unit is intended to sleep The safety watch is a custom-made wristband device meant to whenever possible and only wakes up when certain events be carried by seniors to provide 24/7 security, inside or outside happen, i.e., when there is an immediate danger for the user. of the home. The safety watch has two working modes, depending on Its core part, from a hardware perspective, is an ARM-based whether the user wears the watch or not. If the watch is not low-power Bluetooth module by Nordic [11]. The priority on worn, all working modes are disabled, since there is no need of choosing the processors and other hardware components was motion monitoring, and only the device status (worn or not given to how much energy they consume, since a device that worn) is checked in 1-minute intervals. If the watch is worn, it requires everyday charging is strongly undesirable, especially monitors motion, accumulates the number of steps, and sends for the elderly, who might have problems remembering when or data over Bluetooth to the HomeTab. Once the battery of the how to charge the device. The safety watch integrates a low- device drops to 30% or lower, the sleeping time of the main power LSM6DSL system-in-package featuring a 3D digital processor increases from 5 to 10 minutes and the user is accelerometer and a 3D digital gyroscope. As well as that, it notified about the low battery level. The software design of the contains a low-power Quecktel module that integrates NB-IoT safety watch is illustrated in Figure 3. and GPS functionality. Since GPS and NB-IoT consume a lot of The safety watch monitors users behaviour (activity levels), power, these two functionalities are disabled for most of the providing incentives to the users (through HomeTab) to move time and programmatically enabled only when needed (i.e., more and at the same time allow to determine unusually low when an emergency call is made and the device is out of activity (due to sickness). The integrated LSM6DSL step-count Bluetooth range of HomeTab). The Quecktel module is functionality enables the number of steps to be detected connected to a SIM card, which is required for NB-IoT throughout the day and to be sent in regular 15-minutes functionality. These components are connected to a intervals via Bluetooth to the HomeTab. This gives information rechargeable Li-ion battery, which can be recharged using a about the user’s activity levels, which the system later analyses wireless (induction) charger. The diagram of the safety watch to detect possible irregularities in the user’s behaviour (which circuit can be seen in Figure 1. can be caused by an undetected disease). For example, if a user is feeling ill (has a flue), he will likely stay in bed significantly longer than when healthy, so the lack of movement can be detected, and caregivers notified. 2.1 Fall Detection Automatic fall detection is one of the most important modules running on the safety watch. A machine learning method that can automatically detect falls and similar dangerous situations was developed and implemented in the final software of the safety watch. For training of machine learning models, we used a publicly Figure 1: Diagram of safety watch circuit available dataset that contained acceleration data from a wrist- worn device from 17 subjects [12]. It comprised 11 daily-life The outer side of the safety watch housing is comprised of a activities, including 5 types of falling, namely: walking, membrane keypad used for manual alarm triggering (e.g. if the standing, sitting, picking up an object, laying, jumping, falling individual is in a dangerous situation). The keypad also backwards, falling sideward, falling forwards using knees, integrates a small LED, used to provide a feedback to the users falling forwards using hands, and falling sitting in an empty (e.g., alarm triggered, low battery alerts). Its appearance is shown in Figure 2. 40 Figure 3: System software design chair. Since our aim was to only detect falls in general, we model, the kNN model and the DT model can be seen in Table grouped all fall-related activities as one class, and all other 1, Table 2, and Table 3, respectively. activities as another class. The non-fall activities were additionally under sampled, in order to adjust the class Table 1: Summed and normalized (per row) confusion distribution of the dataset. The data were further segmented matrix. LOSO evaluation with Random Forest model. using a sliding window technique, with a window size of 2 seconds and 50% overlap between consecutive windows. To Non-fall Fall train the machine learning models, several statistical features Non-fall 97 3 were extracted from the acceleration signals, including mean, Fall 2 98 standard deviation, median, maximum, minimum, mean absolute change, variance, kurtosis, skewness, and similar. The Table 2: Summed and normalized (per row) confusion window size and the optimal feature set was chosen based on matrix. LOSO evaluation with Decision Tree model. our previous work [13]. Various machine learning algorithms were tested – Decision Non-fall Fall Tree (DT), Random Forest (RF), k-nearest neighbors (kNN). Non-fall 91 9 The different algorithms performances were evaluated using the leave-one-subject-out cross-validation technique. With this Fall 8 92 technique, the data is divided into N-number of folds (where N is the number of subjects in the dataset). Each fold is comprised Table 3: Summed and normalized (per row) confusion of data from a single subject. In each iteration of the LOSO matrix. LOSO evaluation with kNN model. cross-validation, data from one subject is used for testing the method, and the training data is comprised of the remaining N-1 Non-fall Fall subjects. Among the tested algorithms, RF proved to have the Non-fall 87 13 best accuracies per watt of power consumed processing the data. Fall 17 83 RF is an ensemble classifier that fits a number of decision trees on various sub-samples of the dataset and outputs the majority Since the aim of the system is to offer a great degree of class label from the constructed trees. It utilizes two random accuracy in detecting actual fall, as well as in filtering false steps in the process of creating trees – a random sampling of the alarms, two metrics were analyzed: (i) sensitivity – capacity to training data points and a random choosing of a splitting feature, detect actual fall, defined as the ratio between the number of which make it robust to noise and outliers [14]. The results falls correctly detected (true positives) and the falls that actually achieved on the laboratory data with the best-performing RF happened; (ii) specificity – capacity to filter false alarms, 41 defined as the ratio between properly discarded activities (true Overall, the software design of the system is highly energy- negatives) and the total number of discarded activities. From efficient and significantly extends the service time of the the confusion matrix presented in Table 1, it can be seen that wearable device, which makes it convenient for use by elderly the model has a very high sensitivity score – 98%, and people. The system is easily operated and therefore shows great specificity score – 97%. They are both very important for a promise for providing long-term and continuous monitoring of real-life implementation of the model – it means that the model the elderly in an unobtrusive way. We believe that it can accurately detects falls, without triggering too many false efficiently contribute to improving remote healthcare services. alarms, which can be detrimental to users. The implementation of the fall detection functionality on the ACKNOWLEDGMENTS hardware was also properly managed to extend the battery life. The authors would like to thank everyone that helped in any The most significant battery saving is done by processing the way with producing this paper. The first author acknowledges acceleration data in batches. The accelerometer stores the financial support from the Slovene Human Resources acceleration values in its internal memory while the main Development and Scholarship Fund – Ad Futura. Part of this processor sleeps. The accelerometer’s buffer fills in 10 seconds, research was done under EIT Health HomeCare2020 project. and when it is full, it wakes the main processor, and the collected data is sent to it for further processing. The main REFERENCES processor stores for about 120 seconds of acceleration data [1] Roy, N.; Dubé, R.; Després, C.; Freitas, A.; Légaré, F. Choosing between before running the fall detection algorithm. Once the 120- staying at home or moving: A systematic review of factors influencing seconds of data is stored, the required features are calculated housing decisions among frail older adults. PLoS One 2018. [2] Institute of Medicine Falls in Older Persons: Risk Factors and from the acceleration signals, and the pre-trained RF model Prevention. In The Second Fifty Years: Promoting Health and Preventing (stored in the RAM of the safety watch) is run. If no fall is Disability; 1992 ISBN 978-0-309-04681-7. [3] Boyé, N. da; Van Lieshout, E. mm; Van Beeck, ed f.; Hartholt, K. a.; detected in the two-minute segment, the main processor goes Van Der Cammen, T. jm; Patka, P. The impact of falls in the elderly. back to sleep, otherwise, an alarm procedure is triggered. 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One of the most important modules running on [11] nRF5 SDK - nordicsemi.com Available online: the safety watch is fall detection, which makes the users able to https://www.nordicsemi.com/Software-and-tools/Software/nRF5-SDK call for emergency treatment in the case of a dangerous (accessed on Aug 26, 2020). [12] Martínez-Villaseñor, L.; Ponce, H.; Brieva, J.; Moya-Albor, E.; Núñez- situation. For this purpose, different machine learning models Martínez, J.; Peñafort-Asturiano, C. Up-fall detection dataset: A were tested and compared. Among them, RF classification multimodal approach. Sensors (Switzerland) 2019. [13] Gjoreski, H.; Stankoski, S.; Kiprijanovska, I.; Nikolovska, A.; model proved to have the highest performance per watt of Mladenovska, N.; Trajanoska, M.; Velichkovska, B.; Gjoreski, M.; power consumed processing the data, which makes it the most Luštrek, M.; Gams, M. Wearable Sensors Data-Fusion and Machine- suitable choice for implementation. Learning Method for Fall Detection and Activity Recognition. In Studies in Systems, Decision and Control; 2020. [14] Breiman, L. Random Forest. Mach. Learn. 2001, 45, 5–32. 42 Machine Vision System for Quality Control in Manufacturing Lines Ivana Kiprijanovska Jani Bizjak Samo Gazvoda Matjaž Gams Department of Intelligent Department of Intelligent Cooking Appliances Department of Intelligent Systems Systems Division Systems Jožef Stefan Institute, Jožef Stefan Institute, Gorenje Group Jožef Stefan Institute, Jožef Stefan International Jožef Stefan International samo.gazvoda@gorenje.com Jožef Stefan International Postgraduate School, Postgraduate School Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia ivana.kiprijanovska@ijs.si jani.bizjak@ijs.si matjaz.gams@ijs.si ABSTRACT industrial cameras with specialized optics to acquire images [3]. In manufacturing, quality control is a process that oversees the After an image is acquired, computer hardware and software aspects of production and ensures that only products that process, analyze, and measure various characteristics of the conform to industry standards and quality criteria leave the image for automated decision-making. production line. Automation of the quality control process Development of an integrated system for comprehensive significantly reduces the time spent on products’ testing, hence quality control in production with an intelligent process control reducing the overall manufacturing costs. In this paper, we system is the main aim of the ROBKONCEL project [4]. One present a brief overview of the algorithms adopted to the aim of of the objectives of this project is the detection of faults in the detection of one possible fault in the production of ovens – non- production of ovens. In this paper, we present the initial working oven fan. The detection is performed through visual experiments in the detection of one of the possible faults – non- data. In the initial experiments, several image processing working oven fan. algorithms were used, and the preliminary results are encouraging. 2 PROBLEM DEFINITION KEYWORDS The quality control of the ovens is intended to take place in a machine vision, image processing, fault detection factory environment, where products moving on a conveyor belt are visually observed, i.e., a machine vision system acquires videos of the ovens. These videos are segmented into 1 INTRODUCTION image frames (at a 30 fps rate), and the obtained image frames Quality control is becoming an increasingly important aspect of are further processed to detect if the fan is working or not. For today’s manufacturing processes [1]. For efficient and the initial experiments, we collected a few videos in a successful production, manufacturers rely on quality control laboratory setting, with various lightings and camera positions, systems integrated into the manufacturing process. The resulting in approximately 7200 images (~4000 working fan traditional quality control process requires vast capacities of and ~3200 non-working fan). Additionally, the visual data of specialized labor. High utilization of the specialists may lead to the ovens’ fans were acquired through a closed door, which human errors, low reliability of the process, and a negative makes the fault detection more challenging (Figure 1). This is impact on the quality of production. Compared to manual preferred as the process of opening and closing the door in a quality control, automated quality control systems offer a manufacturing environment would be too slow. reliable control process with various other advantages, including the ability to work 24 hours a day and, in some tasks, perform faster measurements with higher accuracy and consistency compared to humans [2]. Such systems are also a practical choice when the test cases need to run regularly over a significant amount of time. Machine vision quality control systems play a growing role in modern manufacturing quality control systems. These systems rely on digital sensors inside Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Figure 1: Image of an oven's fan acquired through a closed © 2020 Copyright held by the owner/author(s). oven door. 43 3 IMPLEMENTED TECHNIQUES 3.2 Glare Reduction The image processing steps for the oven fault detection, i.e., A common problem in image processing is the occurrence of non-working fan detection, are as following: specular reflections on the images. In our case, since the videos of the fan were recorded through a glass, a significant amount 1. Object detection of specular reflections, or glare, was produced during the 2. Glare reduction recording. To reduce the effects of the glare, a glare reduction 3. Image thresholding algorithm was applied. The basic glare reduction procedure consisted of 3 steps: (i) decomposition of the original image Each of these steps and the image processing algorithms into a color, saturation and brightness component (HSV); (ii) implemented in them are explained in the following sections. finding particularly bright areas in the image; (iii) inpainting of these areas with the values of the surrounding pixels. 3.1 Object Detection Each image was first converted into HSV color space, which In order to detect and isolate the circle area of the oven fan, we describes the image by its hue (H), saturation (S) and brightness made use of the Hough Gradient Method [5], which is an (V) component (Figure 3). extension to the standard Hough Transform technique [6] for isolating features of a particular shape within an image. The Hough Gradient Method is based on gradient information of edges and is used to improve the speed of the circle detection in order to meet real-time implementation requirements. The calculation steps of the Hough Gradient method are as follows: (i) detect edges in the image; (ii) calculate the local gradient for the edge points using a Sobel operator; (iii) use an accumulator to count the possible circle center on the normal direction of Figure 3: Image decomposition into hue, saturation and edge points’ tangent; (iv) choose the peak circle center and brightness component. circle radius for the general circle equation. The implementation of the Hough Gradient method in With such decomposition, a general rule for pixels that are OpenCV requires a single channel image, so the first step in the subject to specular reflections can be derived; namely, an image detection of circles was to convert the acquired images from the can only contain glare if its color is not saturated, and it has RGB color space to grayscale. Furthermore, two parameters of high brightness. Since light reflections are white, any pixel the circle detection function were tuned, namely: the minimum containing glare cannot have saturation (since white has no distance between the center coordinates of the detected circles color or saturation). Accordingly, we first filtered out the areas and the ratio of the resolution of the original image to the that have low saturation. Next, the area of the non-saturated accumulator resolution [5]. Before running the circle detection pixel was reduced by an erosion operation, and the brightness function, a simple median filter [7] was applied to the images values of the saturated pixels were set to 0. By filtering out the for noise reduction. This helped in reducing the effects of very bright pixels (e.g., all pixels that have a value larger than various reflections in the glass part of the oven door. In general, 130), we obtained the final glare mask (Figure 4). without blurring, the algorithm tended to extract too many circular features, resulting in false circles detection. Therefore, this preprocessing step was crucial for successful circle detection. The circled detection algorithm resulted in a single circle detected in every image; however, with a varying radius. Since the further analyses require images with the same dimensions, the mean value of the detected circles’ radius was calculated and used to isolate the fan area on the images. (Figure 2). Figure 4: Original image and the obtained glare mask. The glared pixels were then interpolated with an inpainting operation. This operation fills the masked pixels with the values that stem from the adjacent non-masked pixels. The original image and its corrected version after the reduction of the glare can be seen in Figure 5. There is a significant amount of glare on the original image, which was effectively removed in the corrected image. The corrected image is a good approximation of the original image when no glare is present. Figure 2: Detected oven's fan area. 44 helped in eliminating quick 1-frame changes from working to non-working, or vice versa. Eventually, the implemented image-processing method resulted in 95% of correctly classified images, on four different videos. The confusion matrix of the method is presented in Table 1. Table 1: Confusion matrix for the proposed method. Non-working Working Non-working 3117 82 Figure 5: Original image and its corrected version. Working 280 3720 3.3 Thresholding As the main purpose of the system is to offer a high accuracy in detection of oven faults, while filtering false alarms, If the two figures representing working and non-working fan in we additionally analysed two metrics: (i) sensitivity, i.e., Figure 6 are analyzed, it can be seen that lighting allows the method’s capacity to detect actual faults (non-working fans), oven fan parts to stand out and be clearly seen behind the grid defined as the ratio between the number of non-working fan when the fan is not working. On the other hand, when the fan is images correctly identified (true positives) and the total number working, the fan area behind the grid is blurred. Therefore, a of non-working fan images; (ii) specificity, i.e., method’s simple thresholding method was utilized to distinguish working capacity to filter false alarms, defined as the ratio between and non-working fan. properly discarded images (true negatives) and the total number of discarded images. The method has a very high sensitivity score of 97%, and specificity score of 93%. Figure 6: Working and non-working oven fan. Thresholding is one of the simplest methods for image segmentation and creation of binary images [6]. The main goal Figure 7: Non-working and working oven fan – thresholded of the utilized binary thresholding was to enhance the parts of images the oven fan when it is not working. For that purpose, the images were firstly converted from RGB color space to grayscale. Next, with the binary thresholding method, each 4 CONCLUSION pixel in the images was replaced with a black pixel if its In this paper, we presented an image processing pipeline intensity was less than a chosen constant (T=90), or a white adopted for the aim of detection of a possible fault in pixel if its intensity was greater than the chosen constant. This production of ovens – non-working oven fan. The image results in the illuminated parts of the oven fan becoming processing steps contain object detection (for isolating the oven completely white (when the fan is not working), while the grid fan area from the images), glare reduction (for reducing the and the moving fan become completely black, as can be seen in effects of specular reflections), and image thresholding (for the examples in Figure 7. final decision-making). The preliminary results show that a As a final step, the number of white pixels in the final quality control system that exploits image processing binary-threshold images, which present only the non-working algorithms could be used in an automated manufacturing fans, was calculated. Then, the 5th percentile of these values environment. In the future, we plan to employ reflection was calculated and set as a threshold value when deciding if a removal algorithms, which can significantly facilitate the object given image represents a working or non-working fan. detection process, such as Sparse Blind Separation with Basically, if the image contains more than X white pixels, Motions (SPBS-M) [8], Superimposed Image Decomposition where X is the previously calculated value of the 5th percentile, (SID) [9], Ghosting Cues [10] and similar. However, the it is classified as a non-working oven fan; otherwise, it is utilization of such algorithms may significantly impact the time classified as a working oven fan. performance of the method, so an acceptable trade-off between In the last post-processing step, the class for each image method’s accuracy and time performance should be explored in frame was taken as the majority class of the last 20 frames. It future analyses. 45 ACKNOWLEDGMENTS [4] ROBKONCEL Available online: http://www.smm.si/?post_id=4682&lang=en (accessed on Aug 28, The first author acknowledges the financial support from the 2020). Slovene Human Resources Development and Scholarship Fund [5] Yuen, H.K.; Princen, J.; Dlingworth, J.; Kittler, J. A Comparative Study of Hough Transform Methods for Circle Finding.; 2013. – Ad Futura. Part of this research was done under and for [6] Shapiro, L.; Stockman, G. Computer Vision 1st Edition; 2001; ISBN ROBKONCEL project. 9780130307965. [7] Huang, T.S.; Yang, G.J.; Tang, G.Y. A Fast Two-Dimensional Median Filtering Algorithm. IEEE Trans. Acoust. 1979. REFERENCES [8] Gai, K.; Shi, Z.; Zhang, C. Blind separation of superimposed moving images using image statistics. IEEE Trans. Pattern Anal. Mach. Intell. [1] Mohamad, H.; Jenal, R.; Genas, D. Quality Control Implementation in 2012. Manufacturing Companies: Motivating Factors and Challenges. In [9] Guo, X.; Cao, X.; Ma, Y. Robust separation of reflection from multiple Applications and Experiences of Quality Control; 2011. images. In Proceedings of the Proceedings of the IEEE Computer [2] Heleno, P.; Davies, R.; Brazio Correia, B.A.; Dinis, J. A machine vision Society Conference on Computer Vision and Pattern Recognition; 2014. quality control system for industrial acrylic fibre production. EURASIP [10] Shih, Y.; Krishnan, D.; Durand, F.; Freeman, W.T. Reflection removal J. Appl. Signal Processing 2002. using ghosting cues. In Proceedings of the Proceedings of the IEEE [3] Golnabi, H.; Asadpour, A. Design and application of industrial machine Computer Society Conference on Computer Vision and Pattern vision systems. Robot. Comput. Integr. Manuf. 2007. Recognition; 2015. 46 Abnormal Gait Detection Using Wrist-Worn Inertial Sensors Ivana Kiprijanovska Hristijan Gjoreski Matjaž Gams Department of Intelligent Faculty of Electrical Engineering Department of Intelligent Systems and Information Technologies Systems Jožef Stefan Institute, Skopje, N. Macedonia Jožef Stefan Institute, Jožef Stefan International hristijang@feit.ukim.edu.mk Jožef Stefan International Postgraduate School Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia ivana.kiprijanovska@ijs.si matjaz.gams@ijs.s ABSTRACT shown that these disorders carry a high risk for falls, with an annual fall rate of 60–80% in patients with Alzheimer's, Falls are a major health problem among elderly people and Parkinson's or similar diseases [4][5]. However, there is often lead to serious physical and psychological consequences. substantial evidence that falls can be prevented if individuals at Identification of elderly people who are at risk of falling helps increased risk of falling are identified and enrolled in targeted for the selection of effective preventative measures that fall prevention programmes [6]. Therefore, identification of minimize the likelihood of falls. The occurrence of gait balance impairment and gait abnormalities is an essential step abnormalities is one of the most significant fall precursors. in fall prevention. Wearable sensors enable continuous monitoring of gait during Camera-based 3D motion capture systems and instrumented daily routines, and therefore offer the possibility of early walkways are considered as the gold standard in gait analysis in detection of gait changes. In this paper, we analyze the ability terms of accuracy. However, these systems are only suitable for of machine learning models to detect gait abnormalities using hospitals or hospital-like settings, such as specialized gait data from inertial sensors integrated into a smartwatch and how analysis clinics, due to their size and the need for qualified they perform on the dominant and non-dominant wrist. professionals to operate them. Moreover, current clinical evaluation of gait is costly and time-consuming, and thus KEYWORDS cannot be performed frequently. Even though the completeness Gait analysis, abnormal gait, fall risk assessment, smartwatch, and the accuracy of the clinical measurements are wearable sensors unquestionable, a mobile and pervasive gait analysis alternative suitable for non-hospital settings is a necessity. Recent technological advancements in wearable sensors offer means 1 INTRODUCTION for analyzing gait during everyday-life living. Among wearable Falls present a major health problem among elderly people. devices, wristbands and smartwatches are increasingly popular One-third of the population aged over 65 years experience at because people find the wrist placement one of the least least one fall per year [1]. Falls greatly affect the quality of life intrusive placements to wear a device. and restrict the independence of those affected. They not only In this paper, we analyzed the ability of inertial sensors lead to severe physical consequences but also result in high integrated into smartwatches to detect human gait abnormalities health care costs. Due to the rapid aging of the population, this that are related to fall risk. Moreover, we studied how the problem will further increase in the near future [2]. Therefore, performance of machine learning models on the non-dominant there is an urgent need for reliable screening tools to identify wrist compares to the performance on the dominant wrist. those at risk and to target effective fall prevention strategies. Falls are a consequence of several intrinsic and extrinsic fall risk factors, among which balance and gait disorders are the 2 RELATED WORK most common ones [3]. Gait is a sensitive indicator of an The recent advancements in sensor technology have led to individual's overall health status, so the occurrence of abnormal applications of wearable sensor devices in gait analysis for fall gait patterns usually represents an early indication of an risk assessment. Several studies have been carried out by underlying neurodegenerative disorder. Clinical research has combining wearable devices with inertial sensors and machine learning methods. The general pipeline in these studies consists Permission to make digital or hard copies of part or all of this work for personal or of signal acquisition while the person performs everyday-life classroom use is granted without fee provided that copies are not made or activities or pre-defined functional tests, signal processing and distributed for profit or commercial advantage and that copies bear this notice and feature engineering, and lastly training a machine learning the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). classifier that produces an output that depends on the Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia application. © 2020 Copyright held by the owner/author(s). 47 Howcroft et al. [7] have presented insightful accounts of peripheral vision, visual distortion, balance deficit, and similar. features, classification models and validation strategies related These effects alter the gait and are highly correlated with an to sensor-based fall-risk assessment. They have found large increased risk of falls [3]. Both scenarios (normal and abnormal heterogeneity in terms of sensor-based features and sensor walk) were repeated by each subject five times, resulting in ten placement. Regarding the features, the existing studies most walking sessions per subject. An example of two motion often use features from the time and frequency domain, which samples from the sensors in the smartwatch worn on the right include mean, variance and energy of the windowed inertial wrist of one subject is shown in Figure 2. data, as well as spectral components such as dominant frequency and harmonic ratio [8]. As well as that, some biomechanical gait features, such as stride length, clearance, stance and swing time for each stride, cycle time, cadence and similar, have been revealed as effective predictors of falls [9]. In terms of the location of the sensors, the most exploited body positions are the shanks, waist, pelvis, and feet. In [10], the authors made use of wearable devices incorporating accelerometer and gyroscopes, worn on the shanks and waist. Figure 1: Equipment for data collection They proposed a general probabilistic modeling approach for classification of different pathological types of gait through the estimation of spatiotemporal features. They showed that a 4 METHOD Support Vector Machine (SVM) classifier can identify mobility The machine learning method that we developed for this study impairment in elderly people, with an accuracy of 90.5%. In consists of several steps: preprocessing of the acquired sensor [11], the authors showed that with assessment of walking signals – filtering and data segmentation, feature engineering quality during a six-minute walk test with accelerometers and extraction from signal segments, and training of a attached to their lower leg and pelvis, prospective fallers and classification model. In the first step, the raw IMU signals were non-fallers can be successfully differentiated with a Random filtered with a band-pass filter with cut-off frequencies in the Forest (RF) classificator. Similar findings were confirmed also range of 0.5 to 3.5 Hz [14], which allowed for reducing the for inertial sensors attached at the sternum, in [12]. However, frequencies outside of the range of frequencies related to human these body locations may be found obtrusive for wearing a walking activity [15]. After the filtering step, the sensor signals device for longer periods of time. On the other hand, the wrist is were segmented using a sliding window. Since window size and considered as the most unobtrusive and widely accepted the sliding parameter have to be tuned correctly for the task at position to wear a device, which does not affect everyday-life hand, the windowing parameters were determined empirically. activities of the user. Still, sensors worn on the wrist are Eventually, we chose a window size of 8 seconds, with 50% affected by frequent movements, as the hand is generally the overlap between consecutive windows. most active part of the body. It makes the analysis of the gait To train a classification model, we extracted several features very challenging, and thus wrist-worn devices have not yet been from the time and frequency domain, for each sensor signal. utilized for gait abnormalities detect for fall risk assessment. The tsfresh python package [16] allows general-purpose time- Considering the lack of evidence supporting the feasibility of series feature extraction, which we exploited in generating more fall risk assessment with sensors worn on the wrist, in this paper than 100 features per sensor stream. These features included the we analyze the performance of several machine learning minimum, maximum, mean, variance, the correlation between methods that utilize inertial sensor data from a wrist-worn axes, their covariance, skewness, kurtosis, the number of times device. the signal is above/below its mean, the signal’s mean change, and its different autocorrelations, among others. Additional subset of frequency-domain features was also calculated using 3 DATASET the signal’s power spectral density (PSD), which is based on the For this study, we collected a dataset comprised of recordings fast Fourier transform (FFT), and included PSD energy, entropy, from 18 subjects (8 males, 10 females, aged 19-54). Each and binned distribution, the largest magnitude from the PSD (of subject wore two smartwatches Mobvoi TicWatch E [13], one the dominant frequency in the signal), and first four statistical on the left, and one on the right wrist (Figure 1). The two moments of the PSD (mean, standard deviation, skewness, and smartwatches had an Android application that collected data kurtosis) [17][18]. from the inertial sensors integrated into the devices, namely: We compared several different ML models that have all accelerometer, gyroscope, and magnetometer, at a sampling previously been proven suitable for human activities analysis: frequency of 100 Hz. 1) Decision tree (DT) [19] is an algorithm that learns a The subjects were walking back and forth along a 15-meters model in the form of a tree structure with decision nodes with straight line and performed two scenarios – normal walk and two or more branches, each representing values for a tested simulated abnormal walk. In the normal gait scenario, subjects feature, and leaf nodes which represent a decision on the target walked at a comfortable pace and performed a natural gait, class. In other words, it predicts the target class by learning while in the simulated abnormal walk scenario, subjects walked decision rules from the training features. while wearing impairment glasses [8]. The glasses were used to 2) Random forest (RF) [20] is an ensemble of decision tree simulate the effects of impairment, including reduction of classifiers. It creates multiple decision trees, each trained on a 48 Figure 2: IMU sensors signals from normal walking session (left) and abnormal walking session (right) bootstrapped sample of the original training data, and searches on the left wrist (L - L), training on the right wrist and testing only across a randomly selected subset of features to determine on the left wrist (R - L), and training on both wrists and testing a split. For the decision on the target class, each tree outputs a on the left wrist ((L+R) - L). With these combinations, we want prediction, and the final prediction of the classifier is to see if training a model with data from only a particular wrist determined by a majority vote of the trees. or both wrists combined leads to higher accuracy. Moreover, 3) Support vector machine (SVM) [21] is an algorithm that another challenge that we took into account is a device with a is characterized by the use of kernel functions. They are used to model developed for the right (left) wrist to be worn on the left transform feature vectors into higher dimensional space, in (right) wrist, hence the “switching wrists” combinations [23]. which a separation hyper-plane is learned to best fit the training The results from these experiments can be seen in Table 1. The data. performance of the machine learning models is additionally 4) K-nearest neighbors (kNN) [22] is an algorithm that uses compared with the performance of a baseline method - majority feature-vector similarity, i.e., for each feature vector in the test vote classifier. data, it finds the k-nearest neighbors in the training set. The From the presented results, it can be seen that the RF final prediction of the classifier is determined by a majority algorithm significantly outperforms the other algorithms for vote of the chosen neighbors. each train-test combination, while the kNN achieves the lowest To estimate the generalization accuracy of the models, we accuracy in detection of gait abnormalities. Moreover, the utilized the leave-one-subject-out cross-validation technique. results show that the right-left combination achieves 72.2% With this approach, the data is repeatedly split according to the accuracy, which is significantly lower than the left-left number of subjects in the dataset. In each iteration, one subject combination, which achieves 83.9% with the RF model. On the is selected for testing purposes, while the other subjects are other hand, the difference between the left-right and right-right used for training the model. This procedure is repeated until combinations is minor – only 1.5 percentage point. These data from all subjects have been used as test data. results suggest that models trained with data from the left wrist could perform well on both wrist, but the data acquired from the right wrist does not bring enough information to train a reliable 5 EXPERIMENTAL RESULTS model that could perform well on the left wrist, as well. To observe the performance of the models in real-life scenarios, However, the problem of “switching wrists” could be we carried out several experiment. In fact, we observe the overcome if the models are trained with data from both wrists. performance of the models on the left and right wrist separately, In fact, the models trained with data from the left and right to see if they achieve similar result on both wrists. wrist combined, outperform the other two combinations for Since real-life poses many challenges that should be taken both wrists, achieving the highest accuracy of 84.3% for the left into account, we considered three different training scenarios wrist, and 82.3% for the right wrist with the RF model. for each wrist. Namely, we test the accuracy of the models for Overall, the results suggest that the models perform better six train-test combinations: training on the left wrist and testing for the left wrist. Since all subjects included in the dataset were on the right wrist (L - R), training on the right wrist and testing right-handed, we can conclude that the non-dominant hand on the right wrist (R - R), training on both wrists and testing on brings more information regarding the walking patterns of the the right wrist ((L+R) - R), training on the left wrist and testing subjects. 49 Table 1: Gait abnormality detection accuracy of individual classifiers. Classifier L - L R - L (L + R) - L R - R L-R (L + R) - R Baseline – Majority 61.4 61.4 61.4 61.4 61.4 61.4 Classifier DT 75.1 51.2 78.0 74.5 65.6 76.6 RF 83.9 72.2 84.3 82.8 81.3 84.3 SVM 68.3 61.0 72.4 64.4 66.4 71.4 kNN 63.2 57.3 63.8 61.2 62.6 63.0 6 CONCLUSION [6] Institute of Medicine Falls in Older Persons: Risk Factors and In this paper, we analyzed the ability of machine learning Prevention. In The Second Fifty Years: Promoting Health and Preventing algorithms to detect gait abnormalities using data from inertial Disability; 1992 ISBN 978-0-309-04681-7. sensors integrated into a smartwatch. Among the compared [7] Howcroft, J.; Kofman, J.; Lemaire, E.D. Review of fall risk assessment in geriatric populations using inertial sensors. J. Neuroeng. Rehabil. machine learning algorithms, Random Forest achieved the 2013. highest accuracy. The analysis of the performance of the [8] Riva, F.; Toebes, M.J.P.; Pijnappels, M.; Stagni, R.; van Dieën, J.H. Estimating fall risk with inertial sensors using gait stability measures that models on the left and right wrist showed that they perform do not require step detection. Gait Posture 2013. better on the left wrist, which was the non-dominant for the [9] Tunca, C.; Pehlivan, N.; Ak, N.; Arnrich, B.; Salur, G.; Ersoy, C. Inertial sensor-based robust gait analysis in non-hospital settings for neurological subjects included in the dataset. The experiments with the disorders. Sensors (Switzerland) 2017. “switching wrist”, i.e., training the models with data collected [10] Mannini, A.; Trojaniello, D.; Cereatti, A.; Sabatini, A.M. A machine from one wrist and testing on the other showed that the learning framework for gait classification using inertial sensors: Application to elderly, post-stroke and huntington’s disease patients. accuracy of the models significantly drops. However, when the Sensors (Switzerland) 2016, 16. models were trained with data from both wrists and applied on [11] Drover, D.; Howcroft, J.; Kofman, J.; Lemaire, E.D. Faller classification in older adults using wearable sensors based on turn and straight-walking each wrist individually, the accuracy increased, outperforming accelerometer-based features. Sensors (Switzerland) 2017. even the models that were trained and tested on the same wrist. [12] Brodie, M.A.; Lord, S.R.; Coppens, M.J.; Annegarn, J.; Delbaere, K. Therefore, the best practical solution is to deploy a model Eight-week remote monitoring using a freely worn device reveals unstable gait patterns in older fallers. IEEE Trans. Biomed. Eng. 2015. trained with data from both wrists. Overall, the results are [13] TicWatch S&E - A smartwatch powered by Wear OS by Google satisfactory and show that data generated by wrist-worn inertial Available online: https://www.mobvoi.com/eu/pages/ticwatchse (accessed on Aug 30, 2020). sensors is sufficient for gait abnormalities detection and can be [14] Dehzangi, O.; Taherisadr, M.; ChangalVala, R. IMU-based gait used for fall risk assessment in non-clinical environments. recognition using convolutional neural networks and multi-sensor fusion. Sensors (Switzerland) 2017. [15] Antonsson, E.K.; Mann, R.W. The frequency content of gait. J. Biomech. ACKNOWLEDGMENTS 1985. [16] Overview on extracted features — tsfresh 0.16.1.dev65+gd190be5 documentation Available online: The authors would like to thank all the participants that took https://tsfresh.readthedocs.io/en/latest/text/list_of_features.html part in the dataset collection. The first author acknowledges the (accessed on Aug 30, 2020). financial support from the Slovene Human Resources [17] Su, X.; Tong, H.; Ji, P. Activity recognition with smartphone sensors. Tsinghua Sci. Technol. 2014. Development and Scholarship Fund – Ad Futura. [18] Gjoreski, M.; Janko, V.; Slapničar, G.; Mlakar, M.; Reščič, N.; Bizjak, J.; Drobnič, V.; Marinko, M.; Mlakar, N.; Luštrek, M.; et al. Classical REFERENCES and deep learning methods for recognizing human activities and modes of transportation with smartphone sensors. Inf. Fusion 2020. [1] Dionyssiotis, Y. Analyzing the problem of falls among older people. Int. [19] Gordon, A.D.; Breiman, L.; Friedman, J.H.; Olshen, R.A.; Stone, C.J. J. Gen. Med. 2012. Classification and Regression Trees. Biometrics 1984. [2] Ageing and health Available online: https://www.who.int/news- [20] Breiman, L. Random Forest. Mach. Learn. 2001, 45, 5–32. room/fact-sheets/detail/ageing-and-health (accessed on Aug 30, 2020). [21] Cortes, C.; Vapnik, V. Support-Vector Networks. Mach. Learn. 1995. [3] Salzman, B. Gait and balance disorders in older adults. Am. Fam. [22] Aha, D.W.; Kibler, D.; Albert, M.K. Instance-Based Learning Physician 2011. Algorithms. Mach. Learn. 1991. [4] Horikawa, E.; Matsui, T.; Arai, H.; Seki, T.; Iwasaki, K.; Sasaki, H. Risk [23] Gjoreski, M.; Gjoreski, H.; Luštrek, M.; Gams, M. How accurately can of falls in Alzheimer’s disease: A prospective study. Intern. Med. 2005. your wrist device recognize daily activities and detect falls? Sensors [5] Allen, N.E.; Schwarzel, A.K.; Canning, C.G. Recurrent falls in (Switzerland) 2016. parkinson’s disease: A systematic review. Parkinsons. Dis. 2013. 50 Avtomatska detekcija obrabe posnemalnih igel Automatic Wear Detection of Broaches Primož Kocuvan Jani Bizjak primoz.kocuvan@ijs.si jani.bizjak@ijs.si Institut "Jožef Stefan" Institut "Jožef Stefan" Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenija Ljubljana, Slovenija Stefan Kalabakov Matjaž Gams stefan.kalabakov@ijs.si matjaz.gams@ijs.si Institut "Jožef Stefan" Institut "Jožef Stefan" Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenija Ljubljana, Slovenija Slika 1: Odčitki signala posnemalne igle POVZETEK najboljše metode je 27 posnemanj oz. 1,8% glede na povprečno Posnemanje materiala je ena izmed metod strojnega obdelovanja število posnemanj, ki se opravijo pred menjavo. izdelkov, ki jih dosežemo s t.i posnemalno iglo. V grobem ločimo zunanje posnemanje in notranje posnemanje materiala. V pri- KLJUČNE BESEDE spevku se posvečamo notranjemu posnemanju, pri katerem se Posnemalne igle, avtomatsko zaznavanje, regresija, strojno uče- v začetku naredi manjšo luknjo v obdelovanec, nato pa posto- nje poma oblikuje profil. To se doseže z različnimi premeri rezil tako, da je na začetku premer manjši, nato pa se postopno povečuje. ABSTRACT Tako se lahko oblikuje poljuben krožni ali n-kotni profil. Zaradi obrabe rezil pri posnemanju se morajo le-ta redno menjati. V Broaching is one of the methods in metalworking, which is per- prispevku je opisan pristop napovedovanja obrabe posnemalne formed with the so-called broach. We distinguish between exter- igle glede na cikel posnemanja. Glavna značilka, uporabljena za nal broaching and internal broaching. In this paper, an internal napovedovanje, je t.i mikroraztezanje (ang. microstrain), ki pove, broaching is presented, where a small hole is initially made in za koliko se spremeni obremenitev na merilnem mestu v delcih the workpiece, and then the broach gradually forms a profile. na milijon. V prispevku je predstavljenih več metod strojnega This is achieved with different blade diameters so that initially učenja za reševanje omenjenega problema. Povprečna napaka the diameter is smaller and then it gradually increases. Thus, any circular or polygon shape can be formed. Due to the wear during Permission to make digital or hard copies of part or all of this work for personal broaching, the blades must be replaced regularly. In this paper, or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and an approach for predicting how many broaching processes or the full citation on the first page. Copyrights for third-party components of this the number of work cycles can still be done before replacing the work must be honored. For all other uses, contact the owner/author(s). broach are presented. We did this by measuring and monitoring Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia the microstrain parameter by the cut time, which tells how much © 2020 Copyright held by the owner/author(s). the strain changes in parts per million. Thus, with regression 51 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Primož Kocuvan, et al. machine learning procedures, we learned a model that missed an average of 27 cycles or 1.8 %. KEYWORDS Broaches, automatic detection, regression, machine learning Slika 4: Primerjava raztezkov med obrabljeno in novo po- 1 UVOD snemalno iglo Posnemanje materiala je zelo natančen postopek obdelovanja kovinskih izdelkov. Cena posnemalnih igel je relativno visoka (nekaj tisoč EUR), zato se posnemanje v industriji uporablja le v primerih, ko imamo dovolj veliko število obdelovancev. Upo- raba obrabljene ali uničene posnemalne igle zaradi množične proizvodnje privede do visokih stroškov za proizvajalca, zato se igle trenutno menjajo po 1500 posnemanjih, ne glede na nji- hovo obrabo. S pomočjo strojnega učenja je mogoče natančneje napovedati, kdaj bo določena igla preveč obrabljena, s tem pa pri- dobimo boljši izkoristek igel ter takojšnje zaznavanje morebitne okvare igle. Avtorji prispevka so za razne industrijske aplikacije dobili več nagrad (prof. dr. Matjaž Gams [1]), medtem ko se je prvi avtor ukvarjal s procesiranjem časovnih signalov v svoji diplomski nalogi [2]. Nekateri raziskovalci so se lotili obdelave Slika 3: Primer posnemalne igle [9] s pomočjo kombinacije strojnega vida in učenja [3], [4], [5] ter merjenja sil [6], [7]. Na sliki 2 je primer signala posnemanja enega cikla oziroma enega obdelovanca. Na abcisni osi je čas, 2 DEFINICIJA PROBLEMA medtem ko je na ordinatni osi obremenitev oziroma raztezek Rezila se med uporabo obrabljajo (postanejo topa), zaradi česar je na distančni plošči (angl. microstrain) [8]. Distančna plošča je potrebna večja sila za posamezen rez. S povečevanjem sile se veča kovinska plošča, ki zagotavlja ustrezen odmik med kovinskim verjetnost, da bo rez nepravilen, oz. se bo rezilo poškodovalo (npr. izdelkom in posnemalno iglo. Tu merimo naš raztezek. odlomil rezilni zob). Ko so rezila preveč obrabljena, jih je mogoče nabrusiti, kar je veliko ceneje od nakupa novega rezila v primeru nepopravljivih poškodb (npr. zloma zoba). Trenutno je postopek v proizvodnji tak, da se vsa rezila po 1500 posnemanjih zamenjajo, saj je verjetnost za napako po tem številu posnemanj previsoka. Problem je, da se rezilo zaradi različnih zunanjih dejavnikov (npr. mazivne tekočine, temperature itd.) obrablja hitreje ali počasneje, kar privede do okvar na izdelku ali slabšega izkoristka rezila. Na sliki 4 je prikazana primerjava signala iz nove igle (modra) ter obrabljene igle (rdeča). Vidimo lahko, da ima posnemalna igla predstavljena z rdečim signalom v splošnem večji integral (površino pod krivuljo), to pomeni, da je sila večja. Razlikuje se tudi po številu ter jakosti posameznih vrhov, npr. v nekaterih primerih določeni vrhovi manjkajo (rezilo (nož) je popolnoma izrabljen). Slika 2: Primer povečave enega reza igle poljubnega si- 3 REŠEVANJE PROBLEMA gnala Iz slike 4 lahko vidimo, da sta število in višina (integral) vrhov eden pomembnejših faktorjev pri prepoznavi okvare, sekundarni faktor pa je oblika vrhov. Avtomatskega prepoznavanja vrhov smo se lotili tako, da smo zaznali, kdaj se signal dvigne od stan- dardne deviacije (šuma) signala. Med posameznimi rezi je igla v mirovanju, kar je razvidno iz slike 1. Na ta način smo dobili Opazimo, kako se raztezek (ki ga lahko interpretiramo kot okno, ki vsebuje le signal, ki nastane med rezanjem. Poiskali smo silo) na distančni plošči spreminja, ko se spreminja premer zob okrog 1000 različnih atributov, ki opisujejo signal s pomočjo knji- posnemalne igle. Na sliki 3 je primer posnemalne igle (splošno), žnice Tsfresh [10]. Ti atributi so npr. minimalna in maksimalna z rdečo barvo je označen obdelovanec. Smer puščice nakazuje vrednost signala, frekvence in vzorci, ki se pojavljajo v signalu. pomik. Nato smo atribute filtrirali z ozirom na relevantnost (prav tako 52 Avtomatska detekcija obrabe posnemalnih Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Slika 5: Primerjava odčitkov raztezka z leve in desne po- Slika 6: Integral signala glede na število rezanj posne- snemalne igle malne igle z omenjeno knjižnico), ki za vsak atribut izračuna p-vrednost oz. statistično stopnjo značilnosti. V zadnji fazi se nad množico p-vrednosti požene Benjamini-Yekutieli algoritem, ki se odloči katere značilke obdržimo in katere izločimo. Izkazalo se je, da so najpomembnejši atributi ploščina, maksimalna vrednost ter število vrhov, torej le trije atributi. Z izbranimi atributi smo s pomočjo strojnega učenja napovedali, v kakšnem ciklu oz. kako blizu okvari je določena igla. Uporabili smo naslednje pristope z učnim okoljem Sci-kit learn [11], [12]: • linearno regresijo (Linear Regression) [13], • gradientno ojačitev za regresijo (Gradient Boosting) [14], • klasifikator AdaBoost (AdaBoost Classifier) [15], • K najbližjih sosedov (K Nearest Neighbours) [16]. Obdelovalni oz. posnemalni stroj, s katerega smo pridobili me- ritve, ima levo in desno posnemalno iglo, pri čemer obe delujeta istočasno, torej obe posnemata (režeta) material hkrati. Na sliki 5 je primer meritev leve in desne posnemalne igle za posnema- nje ob določenem času. Opazimo, da ima ena igla večji integral, Slika 7: Maksimalne vrednosti signala glede na število re- kar pomeni, da bi morali na začetku merilnega cikla kalibrirati zanj posnemalne igle iglo/senzor. S tem bi zagotovili enako izhodišče za nadaljnjo sta- tistično obdelavo podatkov. Da bi se izognili tej težavi smo v tem prispevku primerjali le posnemalne igle, ki so na isti strani (leva ali desna). 4 REZULTATI Za napovedovanje zvezne vrednosti ciljne spremenljivke (re- Na sliki 6 je prikazana primerjava integralov signala po določe- gresija) uporabljamo metriko MAE (angl. Mean Absolute Error) nem številu rezov (ordinata). Vidimo lahko (še posebej na desni in RMSE (angl. Root Mean Squared Error). Razlika je v tem, da igli), da se z večanjem števila rezov vrednosti integralov pove- metrika absolutne napake vrne le razliko absolutne napake, med- čujejo, kar je skladno s pričakovanji, da je za enak rez s topim tem ko RMSE vrne kvadrat te napake, s čimer kaznujemo večje nožem potrebna večja sila. razlike, torej primere, ko se napaka razlikuje za večje število Podobno, čeprav manj izrazito, lahko ugotovimo za maksi- ciklov. V našem primeru smo uporabili le vrednost MAE, ki je malno silo, ki nastane med rezom, kar je razvidno iz slike 7. definirana z enačbo (1). Na sliki 8 je prikazano število vrhov, ki jih algoritem prepozna. Po pričakovanjih je število vrhov obratno sorazmerno s številom rezov. Rezila na posameznih iglah se obrabljajo, zato te igle ne 𝑛 1 Õ režejo več, torej je sila na rezilu nizka, saj igla ne postruži nič 𝑀 𝐴𝐸 = |𝑦 − 𝑥 | (1) 𝑖 𝑖 𝑛 materiala. Nato sledi naslednja igla, ki ni obrabljena, ker pred- 𝑖 =1 hodna igla ni opravila svojega dela, mora ta igla odstraniti večjo količino materiala, kar privede do večje sile ter obrabe na tem V tabeli 1 so prikazani rezulati napovedovanja cikla za posa- igli. mezno metodo strojnega učenja. 53 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Primož Kocuvan, et al. [4] S.Kurada in C.Bradley. [n. d.] A machine vision system for tool wear assessment. 30, 295–304. [5] S.Damodarasamy in Shivakumar Raman. [n. d.] An ine- xpensive system for classifying tool wear states using pattern recognition. 170, 149–160. [6] Dongfeng Shi in Nabil N.Gindy. [n. d.] Tool wear predic- tive model based on least squares support vector machines. 21, 1799–1814. [7] S. Rangwala in D. Dornfeld. [n. d.] Sensor integration using neural networks for intelligent tool condition monitoring. 112, 219–228. [8] Anderson Langone Silva, Marcus Varanis, Arthur Guil- herme Mereles, Clivaldo Oliveira in José Manoel Balthazar. [n. d.] A study of strain and deformation measurement using the arduino microcontroller and strain gauges devi- ces. 41. [9] Srednja šola Koper. 2020. Posnemanje materiala. http : Slika 8: Število vrhov signala glede na število rezanj posne- / / www2 . sts . si / arhiv / tehno / projekt3 / Posnemanje / malne igle posnemanje.htm. [10] Ts fresh library. 2020. Tsfresh. https://tsfresh.readthedocs. Tabela 1: Regresorji in njihove pripadajoče metrike MAE io/en/latest/. [11] Aurélien Géron. 2017. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Tech- Regresor MAE niques to Build Intelligent Systems. O’Reilly Media; 1st Linearna regresija 101,25 Edition, 574. Gradient boost 27,58 [12] Andreas C. Müller in Sarah Guido. 2016. Introduction to AdaBoost 165,44 Machine Learning with Python: A Guide for Data Scientists. KNN 74,16 O’Reilly Media; 1st Edition, 400. [13] Sci kit learn. 2020. Regression - linear regression. https: / / scikit - learn . org / stable / modules / generated / sklearn . linear_model.LinearRegression.html. 5 ZAKLJUČEK [14] Sci kit learn. 2020. Regression - gradient boost. https : Način merjenja mikroraztezka na distančni plošči ter analize / / scikit - learn . org / stable / modules / generated / sklearn . časovnega signala s pomočjo strojnega učenja je naš prispevek ensemble.GradientBoostingClassifier.html. na tem področju. Z navedenimi pristopi smo dobili povprečno [15] Sci kit learn. 2020. Regression - adaboost. https://scikit- absolutno napako (MAE) 27,58 kar pomeni, da se naš model v pov- learn.org/stable/modules/generated/sklearn.ensemble. prečju zmoti za 27,58, pri napovedovanju cikla trenutnega reza. AdaBoostRegressor.html. Vrednosti (število ciklov) gre od 0 do 1500 1. To pomeni, da model [16] Sci kit learn. 2020. Regression k-nearest-neighbour. https: s točnostjo 98,16 % napoveduje v katerem ciklu je posnemalna / / scikit - learn . org / stable / modules / generated / sklearn . igla, oz. kdaj je iglo potrebno zamenjati. V nadaljevanju raziskave, neighbors.KNeighborsRegressor.html#sklearn.neighbors. se je potrebno osredotočiti na optimizacijo hiperparametrov po- KNeighborsRegressor. sameznega regresorja. Končni cilj raziskave je implementacija tovrstnega primerjanja na podlagi signala v proizvodni proces. ACKNOWLEDGMENTS Ta raziskava je bila delno financirana s strani projekta ROB- KONCEL s šifro OP20.03530 in ARRS. Zahvaljujemo se podjetju UNIOR (Jože Ravničan in Tomaž Hohler). LITERATURA [1] 2011. Ventil - revija za fluidno tehniko, avtomatizacijo in mehatroniko. V Ljubljana. [2] Primož Kocuvan. 2015. Zaznavanje srčnega šuma v fono- kardiogramih. Diplomsko delo - Univerza v Ljubljani, 50. [3] Wenmeng Tian, Lee J. Wells in Jaime Camelio. 2016. Broa- ching tool degradation characterization based on functio- nal descriptors. V (MSEC). 11th Manufacturing Science in Engineering Conference (MSEC2016), USA. 1Model privzame, da je iglo potrebno zamenjati, ko signal izgleda, kot izgleda na igli s 1500 rezi. Če bi želeli točno izvedeti, kdaj je "točka preloma", torej ko je igla okvarjena, bi bilo potrebno izvesti še nekaj meritev/posnetkov, kjer bi se igla uporabljala dokler ne bi prišlo do napak na izdelku. 54 Povečevanje enakosti (oskrbe duševnega zdravja) s prepričljivo tehnologijo Increasing Equality (in Mental Health Care) with Persuasive Technology Tine Kolenik† Matjaž Gams Odsek za inteligentne sisteme Odsek za inteligentne sisteme Institut “Jožef Stefan” in Institut “Jožef Stefan” Mednarodna podiplomska šola Ljubljana, Slovenija Jožefa Stefana matjaz.gams@ijs.si Ljubljana, Slovenija tine.kolenik@ijs.si POVZETEK of people with mental health issues. This paper presents such systems with a brief overview of the field, with the main Neuspešno spopadanje z naraščajočimi težavami z duševnim contribution being an analysis of potential problems and zdravjem močno ovira blaginjo posameznika in družbe. Kljub solutions that persuasive technology offers in the field of mental temu so ovire do dostopa in enakosti v oskrbi na področju health care. Persuasive technology seems to be able to duševnega zdravja, ki jih je veliko, znane, obsegajo pa od complement existing mental health care solutions, thereby osebnih stigm do socialno-ekonomske neenakosti. Tehnologija, reducing unequal access to and inequality in mental health care predvsem pa umetna inteligenca, ima ob takšnem stanju as well as reducing inequality in general. priložnost, da s svojim razvojem poskuša ublažiti obstoječi položaj z edinstvenimi rešitvami. Multi- in interdisciplinarne KEYWORDS raziskave na področju prepričljive tehnologije, katere cilj je Digital mental health, persuasive technology, artificial spreminjanje vedenja ali mentalnega stanja brez zavajanja in prisile, kažejo uspeh pri izboljšanju počutja pri ljudeh s intelligence, mental health care access, equality. tovrstnimi težavami. V prispevku so predstavljeni takšni sistemi s kratkim pregledom področja, glavni doprinos pa je analiza 1 UVOD potencialnih težav in rešitev, ki jih prepričljiva tehnologija nudi na področju oskrbe duševnega zdravja. Zdi se, da prepričljiva Težave na področju duševnega zdravja so že desetletja v porastu, tehnologija lahko dopolni obstoječe rešitve za pomoč pri uničujoč učinek tega pa so pripoznali tudi svetovni odločevalci, duševnem zdravju, s tem pa zmanjša težave v dostopnosti in saj so Združeni narodi izboljšanje na tem področju uvrstili med enakosti zdravstvene oskrbe kot tudi v enakosti nasploh. svoje cilje trajnostnega razvoja [42]. Med temi težavami izstopajo predvsem stres, anksioznost in depresija (SAD). KLJUČNE BESEDE Beležijo, da se v nekaterih skupinah z akutnim stresom spopada 74% ljudi [24], z anksiozno motnjo 28% ljudi [5] in z depresijo Digitalno duševno zdravje, prepričljiva tehnologija, umetna 48% ljudi [36]. Kar se zdi še bolj problematično, je dejstvo, da v inteligenca, dostopnost in enakost zdravstvene oskrbe. državah z nizkim in srednjim dohodkom okoli 80% ljudi ni ABSTRACT deležno zdravljenja zaradi svojih duševnih težav, v državah z visokim dohodkom pa ta številka dosega okoli 35% [33]. Težave The inability to cope with increasing mental health issues among z duševnim zdravjem povzročijo daljnosežne in večplastne the populace severely hampers the well-being of both the posledice, ki jih občutijo bolniki, njihova neposredna okolica individual and society. Barriers to access and equality in mental (družina, skrbniki) in širša družba [41]. Bolniki se soočajo s health care, many of which are well known, range from personal slabšo kakovostjo življenja, nižjimi izobraževalnimi rezultati, stigmas to socio-economic inequality. This offers technology, nižjo produktivnostjo, potencialno revščino, socialnimi težavami especially artificial intelligence, the opportunity to try to in dodatnimi zdravstvenimi težavami. Skrbniki se soočajo z alleviate the existing situation with unique solutions. Multi- and večjimi čustvenimi in fizičnimi izzivi, pa tudi z zmanjšanim interdisciplinary research in the field of persuasive technology, dohodkom in povečanimi finančnimi stroški. Družba se vsako which aims to change behavior or mental states without leto sooča z izgubo več odstotnih točk BDP in milijardami deception and coercion, shows success in improving well-being dolarjev na državo skupaj s poslabšanjem zaupanja v inštitucije javnega zdravja in s krhanjem socialne kohezije. Vse to vodi v čed alje močnejšo pozitivno povratno zanko – SAD ohranja in Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed krepi SAD. Težave z duševnim zdravjem prepogosto vodijo tudi for profit or commercial advantage and that copies bear this notice and the full v izgubo človeškega življenja, saj se številne države spopadajo z citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). visoko stopnjo samomorov [8]. Razlogi za višanje simptomov Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia SAD vključujejo močno pomanjkanje strokovnjakov in © 2020 Copyright held by the owner/author(s). predpisov za duševno zdravje [39] ter neenak dostop do oskrbe 55 na področju duševnega zdravja [9]. Zato se zdi, da tehnološke in duševno zdravje). Osebnost se meri na različnih dimenzijah druge znanstvene terapevtske intervencije lahko pomagajo pri (odprtost, vestnost, ekstravertnost, sprejemljivost, nevroticizem), izboljšanju trenutnega stanja sistema, zlasti ker imajo ki poskušajo opisati posameznikove tendence, povezane z posamezniki z duševnimi težavami terapije raje kot zdravila [2]. njegovimi psihološkimi lastnostmi, kot so duševna stanja in Zaradi napredka vedenjskih ved na področju človekovega odločanje. Prepričevanje na področju duševnega zdravja je hkrati odločanja in sorodnih pojavov [34] ter prihodom digitalnih bolj uspešno, če PT dostopa do podatkov o posameznikovem tehnologij, umetne inteligence in velikega podatkovja se je duševnem zdravju. V ta namen lahko uporabimo vprašalnike razvoj usmeril v ustvarjanje tehnologij, ki bi pomagale, SAD [21] za kategorizacijo ljudi s simptomi SAD. motivirale in usmerjale ljudi, da izboljšajo sebe in svet. Okvirji prepričevanja so lahko implementirani v različne Prepričljiva tehnologija (PT) je eden izmed rezultatov tovrstnih tehnološke platforme. Nedavni pregledni članek PT za zdravje in prizadevanj. Gre za tehnologijo, ki "spreminja stališča ali dobro počutje [27] je ugotovil, da so najpogosteje uporabljene vedenja ali oboje (brez uporabe prisile ali zavajanja)" [12, str. platforme mobilne naprave (28%), sledijo igre (17%), spletna in 20]. Sprememba vedenja velja za pojav začasnega ali trajnega socialna omrežja (14%) ter druge specializirane naprave (13%), učinka na vedenje, odnos in druga duševna stanja posameznika v namizne aplikacije (12%), senzorji in nosljive naprave (9%) ter primerjavi s preteklostjo [12]. PT se že uporablja za pomoč pri zasloni v javnem prostoru (5%). Vrst aplikacij, ki delujejo kot duševnem zdravju [25, 27], kar prispeva k enakosti in omogoča PT, je na tem področju več, inteligentni kognitivni asistenti lažji dostop do zdravstvene oskrbe [37]. (IKA; znani tudi kot pogovorni roboti ali pogovorna umetna Prispevek ima sledečo strukturo: poglavje 2 nudi pregled inteligenca) pa so najbolj napredni in razširjeni [4, 18, 26, 27, 30, področje PT za pomoč pri duševnem zdravju, poglavje 3 37, 44]. IKA izkazujejo številne človeku podobne sposobnosti, analizira težave in rešitve, ki jih nudi PT, poglavje 4 pa poda saj lahko do neke mere razumejo kontekst, se prilagajajo, se nekaj zaključnih misli in idej za prihodnje delo. učijo, komunicirajo, sodelujejo, napovedujejo, zaznavajo, razlagajo in utemeljujejo. Najpomembneje je, da se IKA lahko pogovarjajo v naravnem jeziku in jih je zato mogoče ustvariti 2 PREGLED PODROČJA tako, da nudijo terapevtsko pomoč. Rezultati različnih Pričujoče poglavje vsebuje pregled področja PT in področja preglednih člankov [4, 18, 26, 27, 30, 37] kažejo, da so IKA sprememb vedenja. učinkovito sredstvo za lajšanje simptomov SAD. Izvedli smo Sprememba vedenja je pojav, za katerega velja, da pri kratek pregled prispevkov o najsodobnejših IKA za duševno posamezniku povzroči začasen ali trajen učinek na njegovo zdravje in tri na kratko predstavljamo za ponazoritev tovrstne vedenje v primerjavi s tem, kako se je vedel v preteklosti [12]. tehnologije. Vsi trije IKA [11, 14, 43] delujejo podobno, tako da Ne vključuje le vedenja, temveč tudi duševna stanja. Intervencije z uporabo skriptiranih pogovorov in osnovnih sposobnosti za spremembo vedenja so velik del PT, ki se že pogosto uporablja procesiranja naravnega jezika nudijo pomoč. Ta je odvisna od na zdravstvenih področjih. Obstoječi sistemi s pomočjo umetne uporabniškega modela, ki vsebuje podatke o čustvih inteligence spremljajo vedenje ljudi ter njihova fiziološka in uporabnikov in ravni SAD. Vsi IKA se v eksperimentih izkažejo duševna stanja z namenom, da jih motivirajo in vplivajo na za 15–20% uspešnejše pri lajšanju SAD od uradno priporočenega njihovo počutje, vse to pa lahko počnejo v naravnem jeziku [27]. gradiva za samopomoč. Eden najpogosteje uporabljenih okvirjev prepričevanja in Takšna tehnologija nudi številne prednosti na področju sprememb vedenja, ki jih uporabljajo takšne tehnologije, so duševnega zdravja: lahko je brezplačna in omogoča pomoč Cialdinijeva načela prepričevanja (CPP) [6]. Obstajajo tudi drugi socialno-ekonomsko prikrajšanim ljudem; na voljo je 24 ur na okviri [25, 27], vendar je za namene tega dela opisan samo CPP. dan, 7 dni v tednu, kar pomeni, da bolnikom ni treba čakati na Njegova glavna ideja je, da ne obstaja splošna strategija naslednjo terapijo; veliko ljudi s simptomi SAD lažje zaupajo prepričevanja, ki bi delovala na vse ljudi. CPP zato opiše več računalniku kot osebi [10, 22]; tehnologija je na voljo na strategij prepričevanja, saj so različni ljudje različno dovzetni za oddaljenih lokacijah itd. Tehnologija lahko tako zmanjša različne strategije. obremenitev zdravstvenega sistema in njegovih izvajalcev ter CPP predvideva 7 strateških podlag za prepričevanje: 1) zmanjša ovire za dostop do oskrbe duševnega zdravja na splošno. avtoriteta, ki cilja na ljudi, ki so bolj nagnjeni k temu, da jih Pomembno je poudariti, da tehnologija deluje komplementarno motivira legitimna avtoriteta; 2) zavezanost in doslednost, ki sta in ne nadomešča strokovnjakov [16, 18, 37]. Prednosti rabe namenjena ljudem, ki se bolj pogosto zavežejo k nečemu, če so tovrstne tehnologije in morebitne težave so podrobneje se tako vedli že prej; 3) družbeni dokazi, ki ciljajo na ljudi, ki se obravnavane v naslednjem poglavju. ponavadi vedejo tako, kot se vedejo drugi; 4) všečnost, ki cilja na ljudi, za katere je bolj verjetno, da jih motivira nekdo, ki jim je všeč; 5) recipročnost, ki cilja na ljudi, ki so nagnjeni k vračanju 3 PREDNOSTI IN MOREBITNE TEŽAVE uslug; 6) pomanjkanje, ki cilja na ljudi, ki menijo, da so redke Pričujoče poglavje obravnava posledice uporabe PT za stvari bolj dragocene; 7) enotnost, ki vpliva na ljudi, na katere duševno zdravje na področju spodbujanja enakosti in dostopnosti vplivajo pozivi, ki se tičejo njihove skupinske identitete. Na oskrbe duševnega zdravja, dotakne pa se tudi posledic na različne ljudi vplivajo različne strategije, interaktivna splošno. Posledice so razdeljene na tiste, ki ponujajo potencialne tehnologija pa nudi orodje za učinkovitejšo izbiro tistih strategij, rešitve obstoječih težav in ovir za enakost in dostopnost, in tiste, ki delujejo za določene ljudi. ki se kažejo kot problemi te tehnologije pri doseganju enakosti. Za izbiranje najučinkovitejše strategije se PT pogosto opira Na koncu poglavja so na kratko obravnavani tudi drugi problemi, na osebnostne modele, kot je velikih pet faktorjev osebnosti [31], ki na videz niso povezani z enakostjo, a so ključnega pomena, da in vprašalnike za posamezne domene, kjer se PT uporablja (npr. PT doseže svoj potencial. 56 Kategorije, v katerih PT ponuja potencialne rešitve: ker se ne bojijo, da bi jih obsojali, pridobijo pa zasebnost za Stroški: Cena storitev, ki jih nudijo strokovnjaki za duševno razkrivanje svojih občutkov in misli na splošno. To pomeni, da zdravje (od psihoterapevtov do kliničnih psihologov in se lahko število ljudi, ki se izogibajo stikom s strokovnjaki, psihiatrov) se od države do države razlikujejo in so predvsem zmanjša z uvedbo terapevtskih možnosti, za katere bolniki odvisni od državnih predpisov in subvencij. Neposredni stroški menijo, da so zanje varnejše in brez stigme. za bolnika so večinoma odvisni od števila strokovnjakov, ki so Vendar pa takšna tehnologija potencialno prinaša tudi težave, na voljo v določeni državi. Neodvisno od njihove višine pa ki jih je potrebno izpostaviti in resno obravnavati, da bi PT stroški velikokrat ovirajo dostopnost do oskrbe ljudi iz nižjih dosegel potencial, ki ga ima na področju duševnega zdravja: socialno-ekonomskih okolij [23]. Dostop do PT za duševno Izključitev ranljivih skupin: Tehnološko usmerjene rešitve zdravje je lahko brezplačen (in velikokrat je [11]) zaradi veliko oskrbe duševnega zdravlja lahko vodijo v izključevanje nižjih stroškov, povezanih z izdelavo. K temu prispevajo trije nekaterih ranljivih skupin. Mednje spadajo starostniki, najnižji glavni dejavniki: 1) razširljivost, kar pomeni, da lahko en sistem socialno-ekonomski razred in kulturno specifične skupine. Zdi PT teoretično nudi pomoč neomejenemu številu ljudi (edini se, da je skupina, ki jo je uvedba tehnologije najbolj prizadela, strošek, ki ga prinaša razširljivost, so stroški strežnika, ki so skupina starostnikov [1]. Njihova nižja sposobnost vključevanja obrobni v primerjavi s človeškim delom) – nasprotno pa je en tehnologije v vsakdanje življenje lahko vodi v globlje razlike strokovnjak za duševno zdravje omejen na določeno število ljudi; med njimi in drugimi generacijskimi skupinami. Druga skupina 2) zmožnost, da učinkovit PT lahko ustvari veliko ljudi, ljudi, ki je lahko izključena iz koristi PT za duševno zdravje, so predvsem zaradi obstoječih raziskav, ki temeljito poročajo o ljudje iz najnižjega socialno-ekonomskega razreda, kjer jim PT učinkovitih sistemih; in 3) količina ljudi, ki je sposobna morda sploh ne bo na voljo [28]. Poglabljanje že tako velikih proizvajati takšne sisteme, je veliko večja, kot je strokovnjakov, razlik bi skupini povzročilo še bolj katastrofalne socialno- ki lahko ponudijo psihoterapevtsko in podobno pomoč. ekonomske življenjske razmere. Skupine, ki jih posvojitev Razpoložljivost: Problem razpoložljivosti lahko ločimo v tri tehnologije prizadene zaradi kulturnih razlik, so ključnega podkategorije: 1) razpoložljivost na podlagi lokacije, 2) pomena pri razmisleku o napredku enakosti. Raziskave kažejo, razpoložljivost na podlagi časa in 3) razpoložljivost na podlagi da kulture z manj sodobnimi družbenopolitičnimi nagnjenji stroškov. Razpoložljivost na podlagi lokacije se nanaša na ljudi kažejo manjšo tendenco po posvajanju tehnologije [19]. Vseeno s težavami v duševnem zdravju na lokacijah, ki nimajo se zdi, da se večja prisotnost področja raziskovanja PT pojavlja neposrednega dostopa do strokovnjakov za duševno zdravje (ali tudi v nekaterih državah z nizkimi dohodki [40]. pa celo nimajo računalniškega dostopa do terapije na daljavo) Pristranost v raziskovanju: Zaradi pomanjkanja standardov [15]. Uporaba PT za duševno zdravje je ena redkih potencialnih evalvacije PT za duševno zdravje je raziskovalno področje bolj rešitev v takih primerih. Razpoložljivost na podlagi časa se dovzetno za pristranost v raziskovanju. Možnih težav je veliko: nanaša na ljudi z duševnimi težavami, ki potrebujejo terapevtsko 1) sistemov PT, za katere se trdi, da so uspešni, ne preučujejo pomoč v času, ko njihov izbrani strokovnjak ni na voljo. PT za vedno v empiričnih poskusih (npr. randomizirana kontrolirana duševno zdravje je na voljo 24 ur na dan, zato se njihova uporaba raziskava), temveč v kvazi eksperimentih [43] ali sploh ne; 2) dopolnjuje z izbranim strokovnjakom za duševno zdravje. metrika, na podlagi katere bi lahko ocenili takšne sisteme, ni Bolniki nenehno poročajo o teh potrebah in take dopolnilne jasna (običajno izhaja posredno iz njihove učinkovitosti v uporabe že obstajajo [29]. Razpoložljivost, ki temelji na stroških, raziskavi, kjer je cilj lajšanje simptomov SAD [37]); 3) ni se nanaša na ljudi z duševnimi težavami, ki potrebujejo soglasja o tem, kateri podatki so potrebni, da sistem razume terapevtsko pomoč, vendar nimajo sredstev za dostop, ki bi bil uporabnika in mu s tem nudi učinkovito pomoč, s čimer je izbira obsežnejši od najmanjše priporočene količine ur na teden [13] – vrste podatkov zaenkrat večkrat odvisna od predpostavk ta se ocenjuje na eno uro na teden. Raziskave [13, 32] kažejo, da raziskovalcev kot pa od obstoječih spoznanj. pogostejše terapije prinašajo boljše rezultate, dopolnilna uporaba Uporaba PT za duševno zdravje ima tudi težave, ki se ne PT za duševno zdravje pa lahko premosti to vrzel pri ljudeh, ki nanašajo samo na doseganje enakosti in dostopnosti. Čeprav so si ne morejo privoščiti več terapije. Razpoložljivost na podlagi izjemno pomembni, je njihova poglobljena analiza izven stroškov je hkrati tesno povezana s širšim problemom stroškov, okvirjev tega dela. Vseeno jih nekaj omenimo: 1.) problem omenjenim v prejšnji kategoriji. varstva osebnih podatkov [3]; 2) problem pomanjkanja Stigma: Samostigma, predsodki, ki jih ljudje z duševnimi longitudinalnih raziskav o spremembah vedenja s PT [20]; 3) težavami imajo o sebi zaradi svojih težav, in javna stigma, odziv etičnost uporabe osebnih podatkov za prepričevanje [17]; in 4) splošne populacije na ljudi z duševnimi boleznimi, predstavljata potencialni problem avtomatizacije in izgube zaposlitve eno poglavitnih težav v boju proti duševnim težavam [7]. Težava strokovnjakov za duševno zdravje. Zagotovo obstajajo tudi druge je dvojna: zaradi javne stigme se posamezniki bojijo, kaj si bo težave in pomisleki, vendar smo želeli, da je ta seznam kratek in družba mislila o njih, če bodo iskali zdravljenje, medtem ko se da z njim pokažemo, da obstajajo tudi druge težave s PT in da se zaradi samostigme bojijo interakcije s strokovnjakom in jih zavedamo. dvomov, da si njihove težave pomoč sploh zaslužijo. 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October 3–6, (2009). http://poluks.ijs.si:12345/. 58 Analiza glasu kot diagnostična metoda za odkrivanje Parkinsonove bolezni Speech Anlysis as a Diagnostic Method for the Detection of Parkinson’s Disease Andraž Levstek Darja Silan Aljoša Vodopija Gimnazija Jožeta Plečnika Gimnazija Jožeta Plečnika Institut “Jožef Stefan” Šubičeva ulica 1 Šubičeva ulica 1 Jamova cesta 39 Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija levstek.andraz@gmail.com darja.silan@gjp.si aljosa.vodopija@ijs.si POVZETEK KEYWORDS Parkinsonova bolezen je nevrodegenerativna bolezen, ki pov- Parkinson’s disease, speech analysis, machine learning, random zroča težave v delovanju mišic zaradi pomanjkanja dopamina v forest, feature importance možganskem deblu, poleg tega vpliva tudi na glas. Slednji po- stane bolj monoton, hripav in šibek. Zaradi naštetih sprememb se 1 UVOD za diagnosticiranje Parkinsonove bolezni vse pogosteje uporablja Parkinsonova bolezen je nevrodegenerativno in izčrpavajoče bo- analiza glasu z metodami umetne inteligence. V tej raziskavi smo lezensko stanje, ki vpliva na osrednje živčevje. Bolezen prizadene s pomočjo metod strojnega učenja primerjali zvočne posnetke približno 1 % ljudi, starejših od 60 let. Bolnik s Parkinsonovo bole- glasu zdravih oseb in bolnikov s Parkinsonovo boleznijo. Za iz- znijo se pogosto trese, ima težave s hojo in ravnotežjem, njegovo boljšavo klasifikacijske točnosti smo dodatno uporabili pristop gibanje postane počasno, pojavi se rigidnost. Pojavijo se lahko zmanjševanja razsežnosti. Najbolj točen klasifikator smo zgradili tudi duševne motnje, kot so anksioznost, depresija ter težave s z uporabo metode naključnih gozdov, s katerim smo dosegli 73 % spanjem, razmišljanjem in obnašanjem. točnost. Dobljeni rezultati nakazuje na povezavo med Parkin- Parkinsonova bolezen vpliva tudi na glas. Večina bolnikov ima sonovo boleznijo in karakteristično spremembo glasu. Ocenili govorne težave, kot so šibek, zadihan, hripav, višji in monoton smo pomembnost posameznih zvočnih posnetkov in pripadajočih glas. Za bolnika so značilne hripavost, zmanjšana jakost glasu, atributov. Izsledke raziskave lahko uporabimo za nadgradnjo ob- težava s pravilno artikulacijo fonemov in brbljanje [5]. stoječe metodologije s predlogi za dodatne posnetke, ki vsebujejo Diagnostične metode, ki bi stoodstotno dokazala prisotnost več informacij o prisotnosti Parkinsonove bolezni. Parkinsonove bolezni, še ne poznamo. Diagnoza temelji na vidnih in razpoznavnih simptomih, preteklem zdravstvenem stanju, fi- KLJUČNE BESEDE zičnem ter nevrološkem pregledu in bolnikovi anamnezi [13]. Parkinsonova bolezen, analiza glasu, strojno učenje, naključni Po kriterijih mora biti za dokaz Parkinsonove bolezni prisotna gozdovi, pomembnost atributov akineza ter še vsaj ena druga lastnost (npr. tremor rok pri mi- rovanju, rigidnost ali posturalne motnje). Po teh kriterijih se ABSTRACT Parkinsonovo bolezen lahko identificira z 90 % točnostjo, vendar diagnoza lahko traja več let [12]. Pri diagnosticiranju se upora- Parkinson’s disease is a neurodegenerative disorder that causes blja tudi slikanje možganov z magnetno resonanco, pozitronsko impaired muscle function because of a lack of dopamine in the emisijsko tomografijo in računalniško tomografijo. Vse naštete brain stem. Parkinson’s disease also affects speech ability. The diagnostične metode so drage ter zahtevne, zato se išče cenejše voice becomes monotone, hoarse and feeble. For this reason, one in preprostejše metode [13]. of the emerging ways to diagnose Parkinson’s disease is speech V diagnostične namene se vse pogosteje uporablja analiza analysis using artificial intelligence. In this paper, we use machine zvočnih posnetkov glasu z uporabo metod umetne inteligence learning to connect voice samples to the presence of Parkinson’s (npr. strojno učenje, procesiranje signalov itd.). Tovrsten način disease. To improve the classification accuracy, we additionally diagnostike je povsem varen, preprost, hiter in ne zahteva dra- use a dimensionality reduction approach. The most accurate clas- gocenih namenskih naprav [8], vendar je to področje v primeru sifier was built with random forest, with an accuracy of 73 %. Parkinsonove bolezni še v razvoju. Večina raziskovalcev se na- The experimental results indicate the correlation between the mreč ukvarja le z doseganjem čim večje klasifikacijske točnosti [1, voice changes and the presence of Parkinson’s disease. Addition- 7, 10, 11], pri tem pa zanemarjajo pomemben vidik analize, in si- ally, we estimate the importance of individual voice samples and cer da bi skušali identificirati pomembne posnetke in pripadajoče corresponding features. The results can be used to improve the glasovne atribute. Taka dognanja bi pripomogla k boljšemu ra- current methodology by proposing additional voice samples, that zumevanju problematike in omogočila oblikovanje natančnejših contain more information on the presence of Parkinson’s disease. testov. V tem prispevku poročamo o testiranju uporabnost analize glasu z metodami strojnega učenja za diagnosticiranje Parkinso- Permission to make digital or hard copies of part or all of this work for personal nove bolezni. Opravljena študija temelji na zvočnih posnetkih 40 or classroom use is granted without fee provided that copies are not made or oseb (20 bolnikov s Parkinsonovo boleznijo) pridobljenih v razi- distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this skavi [10]. Na teh podatkih smo testirali pet različnih algoritmov work must be honored. For all other uses, contact the owner /author(s). strojnega učenja. Za izboljšanje rezultatov smo dodatno uporabili Information society 2020, October 5–9, 2020, Ljubljana, Slovenia metodo za zmanjšanje razsežnosti in izboljšamo klasifikacijsko © 2020 Copyright held by the owner/author(s). točnost za približno 5 %. 59 Information society 2020, October 5–9, 2020, Ljubljana, Slovenia Levstek et al. Tabela 1: Glasovni atributi, uporabljeni za strojno učenje: V nasprotju z večino sorodnega dela smo ocenili tudi pomemb- frekvenčni, pulzni, amplitudni, glasovni ter harmonični. nost posameznih posnetkov in pripadajočih atributov. V ta namen smo uporabili metodo naključnih gozdov, saj ta dosega najvišjo točnost. Na ta način lahko ugotovimo, kateri atributi in posnetki Skupina Atribut vsebujejo več informacij o prisotnosti Parkinsonove bolezni. Jitter (local) Prispevek je organiziran na sledeči način. V drugem poglavju Jitter (local, absolute) predstavimo podatke, v tretjem poglavju opišemo metodologijo. Frekvenčni Jitter (rap) V četrtem in petem poglavju predstavimo rezultate in pridobljena Jitter (ppq5) dognanja. V zadnjem poglavju naredimo zaključek in orišemo Jitter (ddp) nadaljnje delo. Število glasovnih pulzov 2 PODATKI Število nihalnih dob Pulzni Povprečna perioda Podatki so bili zbrani na Istanbulski fakulteti za medicino (Is- Standardna deviacija period tanbul Faculty of Medicine, Istanbul University) leta 2014 [10]. Shimmer (local) Zbrali so zvočne posnetke 40 ljudi, 6 žensk ter 14 moških s Par- Shimmer (local, dB) kinsonovo boleznijo in 10 zdravih žensk ter 10 zdravih moških. Shimmer (apq3) Vsaka oseba je posnela 26 posnetkov, ki vključujejo samoglasnike, Amplitudni Shimmer (apq5) kratke stavke in besede. Natančneje, posnetki 1–3 predstavljajo Shimmer (apq11) trajajoče samoglasnike “a”, “o” in “u”, posnetki 4–13 predstavljajo Shimmer (dda) števila od 1 do 10, posnetki 14–17 predstavljajo krajše stavke in Delež nezvenečih časovnih oken posnetki 18–26 predstavljajo besede. Vsi posnetki so v turščini, Glasovni Število lomljenj glasu 1 posneti so bili z mikrofonom Trust MC-1500 . Delež lomljenj glasu Vsaki osebi pripada 26 zvočnih posnetkov in vsakemu po- Srednja vrednost višine glasu snetku 26 linearnih ter frekvenčnih atributov, zgrajenih z uporabo Povprečna višina glasu programske opreme za akustično analizo Praat [2]. Vsi atributi Standardna deviacija višine glasu so numerični in se jih običajno izračuna za analizo glasu [2, 10]. Najvišja višina tona Povzeti so v Tabeli 1. Skupno je v množici podatkov 676 atribu- Harmonični Najnižja višina tona tov in ciljni razred. Slednji je binaren in predstavlja prisotnost Avtokorelacija tona (pozitiven = 1) oziroma odsotnost (negativen = 0) Parkinsonove Razmerje šum-harmonik bolezni. Imena nekaterih atributov uporabljamo v angleščini, saj Razmerje harmonik-šum pripadajoči slovenski izrazi ne obstajajo. 3 METODOLOGIJA Tabela 2: Rezultati klasifikatorjev v obliki točnosti, senzi- Klasifikatorje smo gradili s petimi algoritmi za strojno učenje: tivnosti in specifičnosti. Najvišja vrednost posamezne me- odločitveno drevo (C4.5), naivni Bayes (NB), metoda najbližjih trike je odebeljena. sosedov (𝑘 NN), metoda podpornih vektorjev (SVM) ter metoda naključnih gozdov (RF). Za vse navedene algoritme smo uporabili Algoritem Točnost Senzitivnost Specifičnost privzete vrednosti parametrov, saj uglaševanje ni signifikantno izboljšalo klasifikacijske točnosti. C4.5 0,63 0,65 0,60 Število atributov močno presega število primerkov, zato smo NB 0,63 0,80 0,45 se odločili za uporabo metode zmanjševanja razsežnosti in s tem 𝑘 NN 0,48 0,55 0,40 uspešno izboljšali klasifikacijsko točnost za 5 %. Za izbor atribu- SVM 0,68 0,70 0,65 tov smo uporabili široko poznano metodo, imenovano rekurzivna RF 0,73 0,75 0,70 odstranitev atributov (ang. recursive feature elimination, RFE) [4], ki temelji na vzvratni odstranitvi nepomembnih atributov. Me- Tabela 3: Matrika zamenjav za klasifikator, zgrajen z me- toda RFE spada med metode po principu ovojnice (ang. wrapper ) todo RF. in smo jo uporabili v kombinaciji z zgoraj naštetimi algoritmi za strojno učenje. Končno število atributov, ki v RFE nastopa kot parameter, smo ocenili z 10-kratnim prečnim preverjanjem. Napoved / Pravi Negativen (0) Pozitiven (1) Za strojno učenje smo uporabili knjižnico caret [6], implemen- Negativen (0) 14 5 tirano v programskem jeziku R [9]. Pozitiven (1) 6 15 4 REZULTATI Za evalvacijo in izbor najboljšega algoritma smo uporabili pristop V Tabeli 2 so prikazani rezultati v obliki povprečne točnosti, po metodi “izpusti enega” (ang. leave one subject out, LOSO). povprečne senzitivnosti in povprečne specifičnosti. Vidimo, da je Najprej smo na učni množici z 10-kratnim prečnim preverjanjem najbolj točen klasifikator, zgrajen z metodo RF, najmanj točen pa z ocenili končno število atributov, ki nastopa kot parameter metode metodo 𝑘 NN. Najvišjo senzitivnost je dosegel klasifikator, zgrajen RFE. Nato smo z uglašeno metodo RFE izbrali najboljše atribute z metodo NB, specifičnost pa klasifikator, zgrajen z metodo RF. V in pripadajoči klasifikator. S slednjim smo klasificirali izpuščen Tabeli 3 so prikazani rezultati za klasifikator, zgrajen z metodo primerek in opisan postopek ponovili za vse primerke. RF v obliki matrike zamenjav. Klasifikator je pravilno klasificiral 1 https://www.trust.com/en/product/14896-design-microphone-mc-1500 29 primerkov, zmotil pa se je v 11 primerih. 60 Analiza glasu kot diagnostična metoda za odkrivanje Parkinsonove bolezni Information society 2020, October 5–9, 2020, Ljubljana, Slovenia Zanimala nas je pomembnost posameznih posnetkov in pri- 5 DISKUSIJA padajočih atributov. V ta namen smo postopek izbora atributov Podobno kot sorodne raziskave [1, 7, 10, 11] tudi naši rezultati ponovili za RF, a tokrat na celotnih podatkih brez izpusta primer- nakazujejo na povezavo med glasovnimi atributi in prisotnostjo kov. Pomembnost izbranih posnetkov in atributov smo izraču- Parkinsonove bolezni. Najbolj točen klasifikator zgradimo z upo- nali s postopkom, imenovanim permutacijska pomembnost (ang. rabo metode RF, s katerim dosežemo 73 % točnost. Za primerjavo permutation importance), ki ga lahko neposredno vključimo v nekatera sorodna dela poročajo o točnosti okoli 80 %. metodo RF [3]. Za vsako drevo posebej izračunamo točnost na Pri tem so najpomembnejši in pogosti frekvenčni atributi izpuščenih primerkih (naključno izpuščenih za gradnjo drevesa). (Slika 1 in Slika 3). Sklepamo, da zaradi karakteristične deviacije Nato ponovimo izračun točnosti po permutaciji določenega atri-frekvence glasu pri Parkinsonovi bolezni. Med posnetki izstopajo buta. Pomembnost tega atributa je povprečje razlik v točnosti števila in kratki stavki (Slika 2 in Slika 4). O prisotnosti bolezni pred in po njegovi permutaciji. Pri tem poudarimo, da pri metodi nam več povedo zahtevni ter daljši posnetki. RF ni težav s koreliranimi atributi, saj postopek uporabimo na Kljub temu je tak način diagnoze nezadosten. Najbolj točna posameznem drevesu, ki je po načinu izgradnje nekoreliran. metoda zgreši 25 % bolnikov, kar je za medicinsko prakso nespre- Na ta način izberemo 27 izmed 676 atributov. Med njimi se jemljivo [13]. Pri tem moramo poudariti, da smo imeli opravka najpogosteje pojavljajo frekvenčni atributi (Slika 1), medtem ko z omejenim številom primerkov (posnetih je bilo le 40 oseb). V so ostale skupine atributov podobno zastopane. Med posnetki primeru, da bi zbrali več zvočnih posnetkov obolelih in zdravih se najpogosteje pojavljajo števila, nato kratki stavki. Najslabše oseb, bi lahko klasifikator izboljšali z uporabo naprednejših me- zastopani so trajajoči samoglasniki (Slika 2). tod strojnega učenja, ki jih na tako malem številu primerkov ni Slika 3 in Slika 4 predstavljata zaporedoma pomembnost izbra- bilo moč uporabiti. nih atributov (agregirano čez posnetke) in pomembnost posnet- Morda ne bo nikoli moč stoodstotno določiti prisotnost Par- kov (agregirano čez atribute) za metodo RF. Atributi in posnetki kinsonove bolezni iz analize glasu z uporabo metod strojnega so razvrščeni od manj pomembnih do bolj pomembnih. Iz rezulta- učenja, vendar bi tovrstne metode lahko uporabili bodisi komple- tov je razvidno, da so za metodo RF najpomembnejši frekvenčni mentarno za nadgradnjo obstoječih metod bodisi kot presejalni atributi. Najmanj pomembni pa so harmonični atributi in atributi, test. Pri tem poudarimo, da je analiza glasu poceni in za bolnika izpeljani iz tona glasu. Najpomembnejši posnetek je število “4”. povsem nemoteča ter varna preiskava. Opazimo, da števila in kratki stavki vsebujejo več informacij od ostalih posnetkov. 6 ZAKLJUČEK V prispevku smo z metodami strojnega učenja primerjali zvočne posnetke zdravih oseb in bolnikov s Parkinsonovo boleznijo. Na- men študije je bil preveriti, ali lahko iz analize glasu sklepamo o prisotnosti Parkinsonove bolezni in ali je možno zgraditi klasifi- kator za uporabo v praksi. Dodatno smo tudi ocenili pomembnost posameznih posnetkov in pripadajočih glasovnih atributov. Rezultati nakazujejo, da pri bolnikih s Parkinsonovo boleznijo pride do poslabšanja zvočne artikulacije, saj smo s klasifikatorjem, zgrajenim z metodo naključnih gozdov, uspešno zaznali 73 % bolnikov. Ne glede na to klasifikator še ni primeren za uporabo v praksi, saj je njegova točnost prenizka. Sedanji klasifikator lahko uporabimo kot komplementarni test že obstoječim. Za najpomembnejše zvočne posnetke se izkažejo števila in kratki stavki. Pri tem so najmanj pomembni trajajoči samoglasniki in besede. Med atributi izstopajo frekvenčni in amplitudni. Slika 1: Število izbranih atributov za posamezne skupine Trenutno raziskujemo možnost, da bi zbrali več sorodnih zvoč- po uporabi metode RFE v kombinaciji z metodo RF. nih posnetkov. Na ta način bi lahko uporabili kompleksnejše metode, ki omogočajo odkrivanje zagonetnih zakonitosti, ki jih na tako majhnem naboru primerkov ni bilo mogoče odkriti. Naš dolgoročni cilj je izgradnja klasifikatorja, ki bi uspešno identificiral večino bolnikov tudi za ceno nekoliko nižje točnosti (nekatere zdrave osebe bi klasificiral za bolne). Klasifikator bi lahko uporabili kot presejalni test in na ta način olajšali sedanjo diagnostiko Parkinsonove bolezni. Poskusili bomo tudi razbrati, zakaj so ravno posnetki števil vsebovali več informacij o pri- sotnosti Parkinsonove bolezni, in z dobljenim znanjem skušali predlagati celovitejši nabor izrazov, besed in fonemov. ZAHVALA Avtorji se zahvaljujejo gospe Ireni Hočevar Boltežar za razlago glasovnih atributov in slovenske prevode. A. Vodopija se doda- tno zahvaljuje finančni podpori Javne agencije za raziskovalno Slika 2: Število izbranih posnetkov za posamezne skupine dejavnost Republike Slovenije (program usposabljanja mladega po uporabi metodo RFE v kombinaciji z metodo RF. raziskovalca). 61 Information society 2020, October 5–9, 2020, Ljubljana, Slovenia Levstek et al. Slika 3: Pomembnost izbranih atributov za klasifikator, Slika 4: Pomembnost izbranih posnetkov za klasifikator, zgrajen z metodo RF. Pomembnost posamezne skupine je zgrajen z metodo RF. Pomembnost posamezne skupine je agregirana pomembnost pripadajočih atributov. agregirana pomembnost pripadajočih posnetkov. 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IEEE Transactions on Biomedical Engineering doi: 10.1016/S1474- 4422(05)70285- 4. , 56, 4, 1015–1022. doi: 10.1109/ TBME.2008.2005954. 62 STRAW Application for Collecting Context Data and Ecological Momentary Assessment Junoš Lukan Marko Katrašnik Larissa Bolliger Jožef Stefan Institute Jožef Stefan Institute Department of Public Health Jožef Stefan International Jamova cesta 39 Ghent University Postgraduate School Ljubljana, Slovenia Ghent, Belgium Jamova cesta 39 marko.katrasnik@gmail.com larissa.bolliger@ugent.be Ljubljana, Slovenia junos.lukan@ijs.si Els Clays Mitja Luštrek Department of Public Health Jožef Stefan Institute Ghent University Jamova cesta 39 Ghent, Belgium Ljubljana, Slovenia els.clays@ugent.be mitja.lustrek@ijs.si ABSTRACT phone use and location) is monitored without user intervention To study stress at the workplace and relate it to user context and or interaction. The second mode of operation are prompts or self-reports, we developed an application based on the AWARE questions for the user, where some information about the context framework, a mobile instrumentation toolkit. The application and the participant’s mental state is gathered by asking for it serves two purposes: of passively collecting data about user’s explicitly. environment and offering questionnaires as means of ecological As a starting point for writing the STRAW application, we momentary assessment. We implemented methods to import used AWARE, a mobile instrumentation toolkit which had the the questionnaires into the phone’s database and trigger them initial purpose of inferring users’ context [5]. It enables logging at the right times. We also considered privacy implications of of data as reported by the phone’s operating system and a wide collecting such data and took additional measures to conceal the variety of hardware sensors. At several points, this toolkit was identity of our study’s participants wherever we evaluated it was adapted to better suit our needs, and additional capabilities were under the risk of exposure. Finally, we had to establish a server added on top of it. application to handle receiving and storage of collected data and We also developed two modular functionalities of the applica- implemented a rudimentary login process to additionally secure tion: Bluetooth integration with an Empatica E4 wristband [23] our servers. to enable simultaneous collection of physiological data and voice detection and speaker diarization capabilities [15]. We already KEYWORDS reported on these developments elsewhere, whereas in this paper, we give an overview of the app’s capabilities. context detection, application development, privacy, ecological momentary assessment 1 APPLICATION OVERVIEW The best machine learning models for stress detection and affect recognition are multimodal [1, 17]. Combining data from different 1.1 Data Types modalities is especially effective, such as using physiological, An important aspect of the STRAW application are prompts, behavioural or contextual, and psychological (self-reported) data. called EMAs. The users can be prompted to make a diary entry Collecting such data in the real-world setting presents a challenge, at a specific time which is called Experience Sampling Method however. [ESM; 3] or, more broadly (when data other than experience In the project called Stress at work (STRAW), the main object- are noted), Ecological Momentary Assessment [EMA; 20]. Diary ive is to analyse the relationship between psychosocial stress methods increase the reliability of collected self-reports as they experiences in the workplace, work activities and events, and are less prone to recall bias [14]. peripheral physiology. To facilitate integration of various data EMAs are the main mode of user interaction in the STRAW sources, an application was designed to run continuously and application. The content of specific questions is beyond the scope monitor their environment and specific phone-related events. of this paper, but in general, the questions are based on existing The application’s purpose is two-fold. The primary mode of psychological questionnaires measuring stressors, stress, and operation is silent and continuous: the user context (such as their related responses. The implementation of EMAs is described in Section 2. Permission to make digital or hard copies of part or all of this work for personal In addition to this, we selected a subset of data that might help or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and us determine users’ context. Below is a list of sensors that are the full citation on the first page. Copyrights for third-party components of this used in the STRAW application together with the description of work must be honored. For all other uses, contact the owner/author(s). data they collect. Data availability from some of these sensors Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). is dependent on phone’s hardware and the version of operating system. 63 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Junoš Lukan, Marko Katrašnik, Larissa Bolliger, Els Clays, and Mitja Luštrek – Acceleration: There are several sources (i.e. virtual sensors) version and phone manufacturer which tries to close applications of acceleration data in a smartphone. Accelerometers meas- for energy efficiency. We attempted to whitelist this application ure acceleration magnitude in various directions and re- in the most common battery-saving software. port either linear acceleration (without gravity effects), gravity, or combined acceleration. This is used further in 2 ECOLOGICAL MOMENTARY Google’s activity recognition API [10]. ASSESSMENT – Barometer: Ambient air pressure. As mentioned, one of the main functions of the STRAW applica- – Light: Luminance of the ambient light captured by the light tion is to collect users’ answers to questionnaires. AWARE already sensor. implements a ‘sensor’ for experience sampling method, which – Temperature: Temperature of the phone’s hardware sensor. shows DialogFragments as the one in Figure 1, but it was too – Bluetooth: This sensor logs surrounding Bluetooth-enabled rudimentary for our study protocol. The main upgrades we had to and visible devices, specifically their hashed MAC ad- make were the mechanism of triggering EMAs and management dresses, and received signal strength indicator (RSSI) in of the database of available questions (items) to include in the decibels. questionnaires. – Location: Device’s current location (latitude, longitude, and altitude, which are masked as described in Section 3) and its velocity (speed and bearing). This uses various methods, such as GPS and known Wi-Fis in vicinity resulting in different degrees of accuracy. Location category is also acquired with Foursquare API. – Network: Network availability (e.g. none or aeroplane mode, Wi-Fi, Bluetooth, GPS, mobile) and traffic data (received and sent packets and bytes over either Wi-Fi or mobile data). – Proximity: Uses the sensor by the device’s display to detect nearby objects. It can either be a binary indicator of an object’s presence or the distance to the object. – Timezone: Device’s current time zone. – Wi-Fi: Logs of surrounding Wi-Fi access points, specifically their hashed MAC addresses, received signal strength in- dicator (RSSI) in decibels, security protocols, and band frequency. The information on the currently connected access point is also included. – Applications: This includes the category of the application currently in use (i.e. running in the foreground) and data related to notifications that any application sends. No- tification header text (but not content), the category of the application that triggered the notification and delivery modes (such as sound, vibration and LED light) are logged. – Battery: Battery information, such as current battery per- Figure 1: An example of an ecological momentary assess- centage level, voltage, and temperature, and its health, as ment prompt. well as power-related events, such as charging and dis- charging times are monitored. – Communication: Information about calls and messages sent or received by the user. This includes the call or message 2.1 EMA Triggering type (i.e. incoming, outgoing, or missed), length of the Originally, AWARE provides a couple of ways to trigger EMAs: call session, and trace, a SHA-1 encrypted phone number at a specific time, by a certain context (i.e. taking into account that was contacted. The phone numbers themselves or the values from other sensors) or on demand (manually). In our study, contents of messages and calls are not logged. time is the most important trigger of EMAs, but we needed finer – Processor: Processor load in CPU ticks and the percentage control. of load dedicated to user and system processes or idle load. The EMAs in our studies are divided into three types: a) morn- – Screen: Screen status: turned on or off and locked or un- ing EMAs with questions about sleep quality, b) work-hour EMAs locked. with questions about momentary affect, job characteristics, work – Voice activity: A classifier, trained using Weka [7]. The activities, and similar, and c) evening EMAs with questions about features are calculated using openSMILE [4] and the out- the whole workday and after-work activities. The first EMA is put is an indicator of human voice activity [15]. triggered in the first hour after the start of the workday as set by the user. The rest of the EMAs during work hours trigger ap- The data described in the list above are collected automatically proximately every 90 minutes, but not closer than 30 min apart. and continuously. The application is run as a foreground service, The time is dependent on the last answered EMA rather than set which means that the data collection continues even while the in advance, and additional reminders are scheduled in the case application is not actively used (i.e. it is minimized). Despite of user inactivity. The final EMA of the day is triggered in the this, there exists software that is specific to the operating system evening at a time set by the user. 64 STRAW Application for Collecting Context Data and Ecological Momentary Assessment Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Each of these types of EMA is implemented as a separate The MAC addresses of detected WiFi and Bluetooth devices are IntentService [11] and handled by a JobScheduler [18]. This hashed in the same way. enabled us to enforce the requirements outlined above such as The location data in their raw form are highly revealing of setting the minimum latency with which the job can start and a user’s identity [2]. Instead of storing the actual geographic making use of periodic jobs. coordinates provided by this sensor, the Foursquare Places API [6] is used to extract the category (venue) of a location. This 2.2 Question Database API enables saving general categories such as ‘bookstore’ or ‘gas station’ near the user’s location. But since we wanted to keep In the original AWARE implementation, questions are queued the option to analyse users’ movements, we also implemented into a questionnaire directly in the code of the application by a transformation of coordinates. We converted longitude and using their custom ESMFactory class. For our study, we use a latitude into spherical coordinates, applied a stochastic rotation pool of more than 200 questions per language from which a (but constant within a specific user) and converted these back subset is sampled for every EMA. We therefore needed a more to transformed longitude and latitude. This enabled us to keep systematic way of storing them within the application. the distances between the locations faithful to original data, but To ease the insertion of individual items, we prepared a spread- transformed to another place on Earth. sheet template which is meant to be human-readable and filled As described in our previous work [15], voice activity recog- out manually. Individual items from this spreadsheet are later nition is performed on the phone in its entirety. This means that converted into JavaScript Object Notation (JSON) and stored raw audio recordings can be discarded immediately after pro- in an SQLite database [13] in phone’s internal storage. This im- cessing and only the calculated features are saved to the database. plementation enabled us to adapt the content of EMAs without Alternatively, only the final binary prediction of human voice touching the source code of the application. It also simplified presence can be retained, but this makes any post-hoc analysis the final selection of questions, such as selecting one language (such as speaker diarization) impossible. (English, Dutch, or Slovenian) and grammatical gender. 3 PRIVACY ENHANCEMENTS 4 SERVER APPLICATION The data collected by the STRAW application have different For the purpose of storing the data on a server, a Python applica- degrees of risk to the users’ privacy. Their privacy would be tion was implemented in Flask [21], which accepts the data in a threatened if an outsider gained unauthorized access to the data. JSON format and saves it in a PostgreSQL [22] database. In addi- These possible external threats are considered in Section 5. tion to receiving the data and managing credentials (as described Even when the data are safely communicated and stored, how- in Section 5), it also performs a couple of additional functions. ever, an involuntary exposure of users’ identity might still be As mentioned in Section 3, instead of saving application names possible. Assuming the data are well protected from unauthor- we only log their category as classified in Google Play Store. To ized external access, these risks will in turn be treated as internal reduce the number of queries, we implemented this as a part of the in this section. server application. As part of the upload process, the application Some of the data collected by the STRAW application are name is received in plain text, but only retained until query personal data, so even when storing them securely and after returns its category. After that, the application name is hashed to pseudonymization, some risk of a privacy breach remains. Since enable comparisons with later records and the name in plain text AWARE is widely used in scientific studies it already implements is discarded. In this way, we could build a database of application some privacy enhancing mechanisms. We performed a thorough name hashes and their corresponding categories on the server, application vulnerability analysis and identified several further while not keeping a record of what applications individual users threats to privacy that we wished to address. While the data use. are safely communicated and stored, an involuntary exposure of The server application also provides a simple UI for admin- users’ identity might still be possible. The types of data that de- istrators, where some metadata about the data collection itself serve special attention are applications, communication, location, are shown in forms of tables and charts. We can access data on and voice activity. last upload, number of days of participation, and number of data As mentioned in Section 1, the notifications that other applica- points for each individual user. This enables us to detect any tions send are monitored in the STRAW application. The content problems with data collection and troubleshoot them early. of the notification, such as that of an instant messaging applica- tion or calendar notification, is never actually stored. We deemed 5 CLIENT-SERVER COMMUNICATION AND even the application names to be sensitive, so we chose to only LOGIN save application categories. This process is further described in The STRAW application and other sensing applications are not Section 4. special in the degree they could be subject to external attacks The content of calls or messages is never logged, but the phone [2]. An attacker might want to expose identity of a user or try to numbers tied to them can be. Since we wanted to keep track of reveal their personal data such as location. There are three points recurring contact with the same person, but not reveal their real of entry for an external attacker: local storage, transmission of phone number, we decided to encrypt them using the SHA-1 data, and the servers. algorithm. While it would be possible to decrypt a phone number While the data reside on the device they are saved locally in by a brute-force attack, the AWARE implementation offers the the phone’s storage. According to Android’s documentation, this option of adding a salt. Thus by using the username (further de- database is exclusive to the STRAW application [9]: scribed in Section 5) as a salt, the phone numbers are sufficiently protected from inadvertent disclosure risk, while the hashed Other applications cannot access files stored within value is retained even across different application installations. internal storage. This makes internal storage a good 65 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Junoš Lukan, Marko Katrašnik, Larissa Bolliger, Els Clays, and Mitja Luštrek place for application data that other applications [2] Delphine Christin. 2016. Privacy in mobile participatory shouldn’t access. sensing. Current trends and future challenges. Journal of Additionally, once the data are transmitted to the server, the local Systems and Software, 116, 57–68. doi: 10.1016/j.jss.2015. database is periodically deleted. This reduces the privacy risk 03.067. of the database being exposed, while also decreasing the local [3] Mihaly Csikszentmihalyi, Reed Larson and Suzanne Prescott. storage requirements. 1977. The ecology of adolescent activity and experience. It is therefore the transmission of data where we had to secure Journal of Youth and Adolescence, 6, 3, (September 1977), the data. They are transmitted over encrypted HTTPS connection, 281–294. doi: 10.1007/bf02138940. which eliminates the risk of exposure during this part of commu- [4] Florian Eyben, Felix Weninger, Florian Gross and Björn nication. The data are received by an application server residing Schuller. 2013. Recent developments in openSMILE, the at Jožef Stefan Institute (JSI), with a dedicated port listening for Munich open-source multimedia feature extractor. In Pro- incoming transmissions. ceedings of the 21st ACM international conference on Multi- The application server communicates with another, database media - MM '13. ACM Press. doi: 10.1145/2502081.2502224. server, also residing at JSI. This second server can only be accessed [5] Denzil Ferreira, Vassilis Kostakos and Anind K. Dey. 2015. from within the JSI local area network. The database itself is AWARE: Mobile context instrumentation framework. Fron- also protected with a password and the user accessing it via the tiers in ICT, 2, 6, 1–9. issn: 2297-198X. doi: 10.3389/fict. application server does not have administrator privileges. 2015.00006. https://www.frontiersin.org/article/10.3389/ Since the STRAW application is a part of a wider study, it is fict.2015.00006. disseminated to recruited participants only. In addition to the data [6] Foursquare. [n. d.] Places SDK. Venue search. Retrieved from this application, other data are collected, such as responses 26/08/2020 from https://developer.foursquare.com/docs/ to questionnaires in baseline screening and physiological data api-reference/venues/search/. from wristbands. It was therefore necessary that the data can be [7] Eibe Frank, Mark A. Hall and Ian H. Witten. 2016. The linked back to an individual in order to join the data from various WEKA workbench. (4th edition). Morgan Kaufmann. sources. We developed a login method to enable this. [8] Martin Gjoreski, Mitja Luštrek, Matjaž Gams and Hristijan Using OkHttp [19] client-side and Flask-HTTPAuth [12] server- Gjoreski. 2017. Monitoring stress with a wrist device using side, we implemented basic access authentication and token au- context. Journal of Biomedical Informatics, 73, 159–170. thentication [16]. The login credentials are disseminated to re- issn: 1532-0464. doi: 10.1016/j.jbi.2017.08.006. gistered participants in our study and are input upon the install- [9] Google. [n. d.] Access app-specific files. Access from in- ation of the STRAW application. This serves multiple purposes: ternal storage. Retrieved 26/08/2020 from https://developer. by requiring login, we only accept data from actual participants android.com/training/data-storage/app-specific. of our study, while we can also use the assigned username to [10] Google. [n. d.] Adapt your app by understanding what pseudoanonymously link data from various sources. users are doing. Retrieved 26/08/2020 from https://developers. google.com/location-context/activity-recognition. 6 CONCLUSION [11] Google. [n. d.] IntentService. Retrieved 26/08/2020 from The application used in the STRAW project serves a dual pur- https://developer.android.com/reference/android/app/ pose: to collect users’ answers to questionnaires and passively IntentService.html. collect data about their environment and phone usage. While the [12] Miguel Grinberg. [n. d.] Flask-HTTPAuth. Retrieved 26/08/2020 application was tailored to requirements of our study, this paper from https://flask-httpauth.readthedocs.io/en/latest/. outlined the main issues and possible solutions when developing [13] D. Richard Hipp, Dan Kennedy and Joe Mistachkin. 2019. an application for research purposes. SQLite. Computer software. (2019). https : / / sqlite . org / The AWARE framework provided a solid foundation and espe- index.html. cially eased sensor data collection, there are additional challenges [14] Gillian H. Ice and Gary D. James, editors. 2006. Measur- that researchers need to face when trying to use an application ing emotional and behavioral response. General principles. like this in a scientific study. The data gathered using this applic- Measuring Stress in Humans. A Practical Guide for the Field. ation will help us develop improved models of stress recognition .Part II –Measuring stress responses. Cambridge Univer- [8], which will help us integrate physiological data with more sity Press, Cambridge, UK, (December 2006). Chapter 3, detailed contextual data and more reliable self-reports. 60–93. isbn: 978-0-521-84479-6. [15] Marko Katrašnik, Junoš Lukan, Mitja Luštrek and Vitomir ACKNOWLEDGMENTS Štruc. 2019. Razvoj postopka diarizacije govorcev z al- goritmi strojnega učenja. In Proceedings of the 22nd In- The authors acknowledge the STRAW project was financially ternational Multiconference INFORMATION SOCIETY – IS supported by the Slovenian Research Agency (ARRS, project ID 2019. Slovenian Conference on Artificial Intelligence. Mitja N2-0081) and by the Research Foundation – Flanders, Belgium Luštrek, Matjaž Gams and Rok Piltaver, editors. Volume A, (FWO, project no. G.0318.18N). 57–60. https://is.ijs.si/archive/proceedings/2018/files/ REFERENCES Zbornik%20-%20A.pdf. [16] Chris Schmidt. 2001. Token based authentication. In Ac- [1] Ane Alberdi, Asier Aztiria and Adrian Basarab. 2016. To- cepted papers for FOAF-Galway. 1st Workshop on Friend wards an automatic early stress recognition system for of a Friend, Social Networking and the Semantic Web. office environments based on multimodal measurements. https : / / www . w3 . org / 2001 / sw / Europe / events / foaf - A review. Journal of Biomedical Informatics, 59, (February galway/papers/fp/token_based_authentication/. 2016), 49–75. doi: 10.1016/j.jbi.2015.11.007. 66 STRAW Application for Collecting Context Data and Ecological Momentary Assessment Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia [17] Philip Schmidt, Attila Reiss, Robert Duerichen and Kristof [21] The Pallets team. 2010. Flask. Computer software. (2010). Van Laerhoven. Wearable affect and stress recognition: a http://flask.pocoo.org/. review. (21st November 2018). [22] The PostgreSQL Global Development Group. 2019. Postgr- [18] Joanna Smith. 2016. Scheduling jobs like a pro with Job- eSQL 11.3 Documentation. Version 11.3. Scheduler. https : / / medium . com / google - developers / [23] Marija Trajanoska, Marko Katrašnik, Junoš Lukan, Mar- scheduling-jobs-like-a-pro-with-jobscheduler-286ef8510129. tin Gjoreski, Hristijan Gjoreski and Mitja Luštrek. 2018. [19] Square, Inc. 2019. OkHttp. Computer software. (2019). https: Context-aware stress detection in the aware framework. //square.github.io/okhttp/. In Proceedings of the 21st International Multiconference IN- [20] Arthur A. Stone and Saul Shiffman. 1994. Ecological mo- FORMATION SOCIETY – IS 2018. Slovenian Conference mentary assessment (EMA) in behavioral medicine. Annals on Artificial Intelligence. Mitja Luštrek, Rok Piltaver and of Behavioral Medicine, 16, 3, 199–202. doi: 10.1093/abm/ Matjaž Gams, editors. Volume A, 25–28. https://is.ijs.si/ 16.3.199. archive/proceedings/2018/files/Zbornik%20-%20A.pdf. 67 URBANITE H2020 Project Algorithms and Simulation Techniques for Decision - Makers Alina Machidon Maj Smerkol Matjaž Gams alina.machidon@ijs.si maj.smerkol@ijs.si matjaz.gams@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT on case-specific models. The goal of the activities will be to imple- ment novel tools and services in order to enable policy-makers URBANITE (Supporting the decision-making in URBAN trans- to use advanced data analysis and machine learning methods formation with the use of dIsruptive TEchnologies) is a H2020 during the design of novel policies for a specific city project with the goal to provide an ecosystem model that artic- URBANITE will allow the analysis of the traffic flows that are ulates the expectations, trust and attitude from civil servants, currently happening and have happened up until that moment. In citizens and other stakeholders in the use of disruptive technolo- addition to the visualization of the traffic, usage of economy shar- gies. This model will be supported with the provision of a data ing vehicles and other aspects, URBANITE will analyse which management platform and algorithms for data – driven decision are the bottlenecks and critical points, based on a set of parame- – making in the field of urban transformation. One of the main ters to be determined by the civil servants. Due to the fact that output of the project will be a Decision-Support System includ- historic data is stored, trends can be determined by URBANITE ing (AI based) predictive algorithms and simulation models for by big data algorithms. These trend analyses can entail the un- mobility that support the decision–making process by analyzing derstanding of, for instance, the use of a certain transportation the current situation, the trends that occurred in a certain time system (e.g. bikes) in a certain neighbourhood of the municipality, frame and allowing to predict future situations, when changing or the peak hours in which a street is blocked. URBANITE will one or more variables. URBANITE will analyze the impact, trust also provide means to simulate the effect of different situations and attitudes of civil servants, citizens and other stakeholders such as opening a pedestrian street at certain times, location of with respect to the integration of disruptive technologies such electric charging stations, or bike sharing points through the as Artificial Intelligence (AI), Decision Support Systems (DSS), implementation of artificial intelligence algorithms. To achieve big data analytics and predictive algorithms in a data–driven that, URBANITE will build first generic models from the data decision-making process. The results of the project will be val- across all the cities and then provide adaptation mechanisms to idated in four real use cases: Amsterdam, Bilbao, Helsinki and apply these models to the different use cases. From the data avail- Messina. This paper overviews the current state of the project’s able, URBANITE will extract and formalize knowledge and then, progress. through a combination of classification, regression, clustering, KEYWORDS and frequent pattern mining algorithms, conclude into some de- cisions and actionable models that will enable city policy-makers AI, Big Data, DSS, disruptive technologies, URBANITE project to simulate and assess the outcomes and implications of new 1 INTRODUCTION policies. In recent times, the cities and urban environments are facing 2 SYSTEM’S ARCHITECTURE a revolution in urban mobility, bringing up unforeseen conse- The URBANITE project will combine various data sources, algo- quences that public administrations need to manage. It is in this rithms, libraries and tools that provide the best solutions to the new context that public administrations and policy makers need scope of the project. The technical "core" of the project has to means to help them understand this new scenario, supporting fulfill the following objectives: them in making policy–related decisions and predicting eventu- alities. The traditional technological solutions are no longer valid • Deploy tools for big data exploration with the active in- for this situation and therefore, disruptive technologies such as volvement of policy-makers. big data analytics, predictive algorithms as well as decision sup- • Design methods for the detection of important events that port systems profiting from artificial intelligence techniques to need to be addressed. support policy – makers come into place. In order to provide the desired functionalities, several state-of- The main technical objective of the URBANITE project is the-art technologies are currently examined and tested in order the development of advanced AI algorithms for analysis of big to be adapted, customized and integrated into the platform. A data on mobility. The developed methods and tools will provide simplified preliminary architecture is presented in Figure 1. substantial support for policy-makers to tackle complex policy problems on the mobility domain and will enable their validation 2.1 Data Analysis Module Permission to make digital or hard copies of part or all of this work for personal One of the first tasks involves the development of various meth- or classroom use is granted without fee provided that copies are not made or ods for exploratory data analysis and user interaction. Multi- distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this modal methods, tools and services for big data on urban mobility work must be honored. For all other uses, contact the owner /author(s). will be implemented that will provide exploratory analysis capa- Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia bilities and enable the policy-makers to actively search for causal © 2020 Copyright held by the owner/author(s). relations in the data will be provided by the platform. 68 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Machidon, Smerkol and Gams Figure 1: High Level Architecture of the URBANITE Platform. The methods to be included in the platform can be segmented The URBANITE recommendation engine will identify and in four main groups: predict important or problematic events related to mobility and will provide suggestions to tackle the issue. The policy support • clustering, where the main goal is to reduce the amount system will provide support to the policy-makers for identifying of data by grouping together similar instances. The im- possible policies that tackle events based on specific criteria. The plemented method will provide mechanisms to group inputs will have to be aggregated for effective decision-making instances based on GIS data or any subset of attributes using hierarchical multi-criteria decision models. that users will define. For example, platform users might choose to cluster all instances based on the type of trans- portation used (shared bikes, electric cars, etc.) 2.3 Policy Simulation and Validation Engine • projection methods that will be used to reduce the dimen- Simulation transparency is a vital feature of the decision making sionality of the data items. The goal of these methods is process when quantitative computer tools are used to justify to represent the data in a lower dimensional space in such some strategies [10]. Simulation predictions can play a catalytic a way that the key relations of the data structures are role in the development of public policies, in the elaboration of preserved. The results of the methods can be used to more safety procedures, and in establishing legal liability. Hence, given clearly visualize the data or use the transformed data in the impact that modelling and simulation predictions are known the next rounds of analysis • to have, the credibility of the computational results is of crucial self-organizing map involves the use of a type of artificial importance to engineering designers and managers but also to neural network, trained in an unsupervised manner. The public servants, and to all citizens affected by the decisions that method can at the same time reduce the amount of data are based on these predictions [10]. (similar to clustering) and nonlinearly projects the data To create trust and increase the model’s credibility and the into lower dimensionalities • simulation results delivered, it is crucial to deal with a validation prediction/regression methods, or classification models, strategy in which non-simulation-trained end-users could feel that will allow to exploit the data comfortable and trust the simulation model [10]. In the URBANITE project, the policy simulation and validation 2.2 Recommendation Engine module will provide methods and tools to simulate the efficiency Recommendation engines (also known as recommender systems) of specific policies in the target domain. Given a new policy, ur- are information filtering systems that deal with the problem of in- ban mobility model and the target parameters, the system can formation overload [6] by filtering key information "chunks" out evaluate the performance of the new policy based on the observed of large amount of dynamically generated information accord- parameters. The implementation of credible traffic simulations ing to user’s preferences, interest, or observed behavior about for the entire city has been addressed by various project; however, item [8][5]. Recommendation engines have the ability to pre- it is not yet adequately solved, due to its complexity. In URBAN- dict whether a particular user would prefer an item or not based ITE ,the constructed model will be used to predict and classify on the user’s profile [5]. Recommendation engine is defined as traffic flow changes based on the provided changes in the new a decision making strategy for users under complex informa- policies. Policy-makers will select the defined KPI’s that need to tion environments [4]. Recently, various approaches for building be evaluated by the validation engine and based on the scores recommendation engines were developed, based on either collab- the new policies achieve, policy-makers will be able to make an orative filtering, content-based filtering or hybrid filtering [12], informed decision about which policies should be deployed in [11], [9]. the city. 69 URBANITE H2020 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia 2.4 Advanced Visualization Methods social media data [13]. The involvement of the municipalities of Bilbao, Helsinki, Amsterdam and Messina will provide a wide Another important task will be the implementation of advanced range of data sources related to the urban mobility, along with visualizations for mobility patterns, highlighting important events, the public, open-source ones. and results of policy validations. The main visualization func- Several types of data sources were identified for the URBAN- tionalities will present the information on a combination of map ITE project: layers, describing where in the city specific events or a sequence 1 of events occurred. Visualizations will involve the use of heat • geospatial data, e.g. maps (Open Street Maps , but also maps, traffic flow graphics, and other transportation clusters. proprietary maps of the cities) Users will be able to change and interact with the visualization • additional info such as: car and lorry registration, infor- parameters. For example, select specific time ranges, zoom, high- mation on parking lots, dynamic parking data, cadastre light, display additional information, etc. Considering the variety information, commercial register, care services, tourism and characteristics of the data, one concern is regarding the de- accommodation picting multidimensional data in a human-perceivable manner. • demographics: statistical information on the number of Several graphical methods are customarily used for a preliminary inhabitants of different city districts, the number of house- analysis of generic multivariate datasets [2]: scatter plots, pie holds, population’s age brackets, city boundaries, etc. charts and bar plots, histograms, box plots, violin and bean plots, • public transportation: tram and metro lines, static and dy- spider/radar/star/polar plots, glyph plots, mosaic and spine plots, namic information about the public bus transport service, treemaps, and others. the GPS position of the buses Traffic datasets are generally high-dimensional or spatial- • traffic data: the count of car traffic and speeds, traffic status temporal [3], thus visualizing traffic data mostly employs in- in real time, vehicle counts on the ring roads, etc. formation visualization and visual analytics. • bicycle information: bike counters, bicycle collection points, Traffic data contain multiple variables, of which the most calculated number of bikes in specific road segments, City- 2 important ones are time and space. Several different types of Bikes visualisation are currently used for traffic data, among them: • pedestrian: manual counts of pedestrians visualization of time, visualization of spatial properties and spatio- • electric charging stations temporal visualization. • taxi stops available Location is the main spatial property of traffic data. Based on • harbour transport data, ferry traffic statistics the aggregation level of location information, visualization of • geographic airport information 3 spatial properties can be categorized into three classes: point- • air quality (OpenAQ ) based visualization (no aggregation) , line-based visualization • noise maps 4 (first-order aggregation), and region-based visualization (second- • wheather data (OpenWeatherMap ) order aggregation) [3]. The format of this datasets varies from JSON, XML, CSV, XLSX, Heatmaps are the most used visualisation tools to show the WMS , GEOJSO or GML. The main issue with the mobility related integrated quantity of a large scale of objects in a map. data sources it is related to the high level of heterogeneity, both A preliminary user interface prototype is depicted in Figure 2. in terms of data format and data availability. Most of the cities involved on the project have some data related to the traffic in the city, for example, but the format of the data, the level of granularity (how often is the data updated) and the availability of historical data (for how long does the city store historical data) varies greatly from one case to another. Another special aspect that needs to be addressed is the im- pact of the COVID-19 on the mobility sector. Since COVID-19 has disrupted all of the social, economic and political aspects of life, the urban mobility area was also affected. Some analysis [1] revealed that the overall mobility fall was up to 76%, public trans- port users dropped by up to 93%, NO2 emissions were reduced by up to 60%, and traffic accidents were reduced by up to 67% in relative terms. This phenomenon of experiencing unexpected change of concepts or data characteristics over time is referred to as concept drift [7] and is one of the key challenges that the URBANITE project will need to deal with when choosing the best way to proceed for making the most appropriate predictions regarding the impact of various traffic policies. The algorithms developed should take into consideration the stability-plasticity Figure 2: User Interface Mock up of the URBANITE Plat- dilemma as a reference. Especially since it’s still difficult to pre- form. dict how the crisis derived from the pandemic will evolve and how the urban mobility will be afterwards. 3 DATA SOURCES 1 https://www.openstreetmap.org/ 2 https://api.citybik.es/v2/ There are several collection procedures of the traffic related data 3 https://openaq.org/ and they range from sensor readings to airborne imagery and 4 https://openweathermap.org/ 70 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Machidon, Smerkol and Gams Figure 3: Data Sources for the URBANITE Platform. 4 CONCLUSIONS social and context-aware mobile recommendation system for tourism. Pervasive and Mobile Computing, 38, 505–515. The technical core in the URBANITE project focuses on the de- [5] F.O. Isinkaye, Y.O. Folajimi, and B.A. Ojokoh. 2015. Recom- velopment of advanced AI algorithms for analysis of big data on mendation systems: principles, methods and evaluation. mobility. The developed methods and tools will provide substan- Egyptian Informatics Journal, 16, 3, 261 –273. issn: 1110- tial support for policy-makers to tackle complex policy problems 8665. doi: https://doi.org/10.1016/j.eij.2015.06.005. on the mobility domain and will enable their validation on case- [6] Joseph A Konstan and John Riedl. 2012. Recommender sys- specific models. The goal of the activities is to implement novel tems: from algorithms to user experience. User modeling tools and services in order to enable policy-makers to use ad- and user-adapted interaction, 22, 1-2, 101–123. vanced data analysis and machine learning methods during the [7] Jesus L Lobo, Javier Del Ser, Miren Nekane Bilbao, Ibai design of novel policies for a specific city. Lana, and Sancho Salcedo-Sanz. 2016. A probabilistic sam- One underlining factor in URBANITE is the adaptation of ple matchmaking strategy for imbalanced data streams everything that it is created to civil servants, citizens and inter- with concept drift. In International Symposium on Intelli- esting parties that may or not be digitally literate. The use of gent and Distributed Computing. Springer, 237–246. big data techniques and artificial intelligence algorithms, up till [8] Chenguang Pan and Wenxin Li. 2010. Research paper rec- now, is not a common skill among public servants and this is ommendation with topic analysis. In 2010 International one of the reasons the data analysis processes and user interac- Conference On Computer Design and Applications. Vol- tion mechanisms described in this work are developed with the ume 4. IEEE, V4–264. abilities of the non-experts in mind too. [9] Nymphia Pereira and Satishkumar L Varma. 2019. Finan- ACKNOWLEDGMENTS cial planning recommendation system using content-based collaborative and demographic filtering. In Smart Inno- This paper is supported by European Union’s Horizon 2020 Re- vations in Communication and Computational Sciences. search and Innovation Programme, URBANITE project under Springer, 141–151. Grant Agreement No.870338. [10] Miquel Angel Piera, Roman Buil, and Egils Ginters. 2013. REFERENCES Validation of agent-based urban policy models by means of state space analysis. In 2013 8th EUROSIM Congress on [1] Alfredo Aloi, Borja Alonso, Juan Benavente, Rubén Cordera, Modelling and Simulation. IEEE, 403–408. Eneko Echániz, Felipe González, Claudio Ladisa, Raquel [11] Tomasz Rutkowski, Jakub Romanowski, Piotr Woldan, Lezama-Romanelli, Álvaro López-Parra, Vittorio Mazzei, Paweł Staszewski, Radosław Nielek, and Leszek Rutkowski. et al. 2020. Effects of the covid-19 lockdown on urban 2018. 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MIT Press, Cambridge, MA. [4] Ricardo Colomo-Palacios, Francisco José García-Peñalvo, Vladimir Stantchev, and Sanjay Misra. 2017. Towards a 71 Towards End-to-end Text to Speech Synthesis in Macedonian Language Marija Neceva, Emilija Stoilkovska, Hristijan Gjoreski mneceva@gmail.com, emi.stoilkovska@gmail.com, hristijang@feit.ukim.edu.mk Faculty of Electrical Engineering and Information Technologies Ss. Cyril and Methodius University Skopje, N. Macedonia ABSTRACT unlike end-to-end speech recognition [4] or machine translation [5], TTS outputs are continuous, and much longer A text-to-speech (TTS) synthesis system typically consists of than input sequences. Mainly referring to the advantages of multiple stages: text analysis frontend, an acoustic model and end-to-end systems, this paper proposes an implementation an audio synthesis module. Building these components often of Google’s Tacotron model as a TTS system for Macedonian requires extensive domain expertise and may contain brittle language. Tacotron is an end-to-end generative TTS model design choices. The paper presents an end-to-end deep based on the sequence-to-sequence model (seq2seq) [6] learning approach to speech synthesis in Macedonian with attention paradigm [7]. This model takes characters as language. The developed model uses the Google’s Tacotron input and outputs raw spectrogram. We implemented our architecture and is able to generate speech out of text from own version of Tacotron, based on few published articles. What we kept is their deep learning architecture, but made multiple speakers using attention mechanism. It consists of some changes in model’s hyper parameters and other three parts: an encoder, an attention-based decoder and a utilities (like known symbols, numbers etc.). That way the post-processing network. The model was trained on a model was adapted to work with Cyrillic. Given dataset recorded by five, mixed gender speakers, resulting in pairs, our Tacotron model was trained completely from 25.5 hours of data, or 13,101 pairs of text-speech segments. scratch only on our dataset. It does not require phoneme- The results show that the model successfully generates level alignment, so it can easily scale to using large amounts speech from text data, which was empirically shown using a of acoustic data with transcripts. quantitative questionnaire answered by 42 subjects. 2 RELATED WORK KEYWORDS WaveNet [8] is a powerful, non end-to-end, generative audio text-to-speech, deep learning, tacotron, multi-speaker, model which works well for TTS synthesis. It is used as a replacement of the vocoder and acoustic model of the system. seq2seq, text, audio, attention It can be slow due to its sample-level autoregressive nature. 1 It also requires conditioning on linguistic features from an INTRODUCTION existing TTS frontend. Modern TTS pipelines are complex [1]. For example, statistical parametric ones have a text frontend, extracting Deep Voice [9] is a neural model which replaces every various linguistic features, a duration model, an acoustic component in a typical TTS pipeline by a corresponding feature prediction model and a complex signal-processing- neural network. However, each component is independently based vocoder [2][3]. These components usually require trained, and it’s nontrivial to change the system to train in an extensive domain expertise, are laborious to design and must end-to-end fashion. be trained independently. Consequently, errors from each Wang et. al [10] presents one of the first studies of end-to- component may compound. Otherwise, implementing an end TTS using seq2seq with attention. However, it requires a integrated end-to-end TTS system offers many advantages. pre-trained hidden Markov model (HMM) aligner to help the First, it can be trained on pairs with minimal seq2seq model learn the alignment and a vocoder due to human annotation. It also alleviates the need for laborious predicting vocoder parameters. Furthermore, the model is feature engineering. Further, it allows rich conditioning on trained on phoneme inputs with possibilities of hurting the various attributes, such as speaker or language, or high-level prosody and producing limited experimental results. features like sentiment. Similarly, adaptation to new data might also be easier. Finally, a single model is likely to be Char2Wav [11] is an independently developed end-to-end more robust than a multi-stage. All these advantages imply model that can be trained on characters. However, it still that an end-to-end system allows training on huge amounts predicts vocoder parameters before using a SampleRNN real world data. But knowing that TTS is a large-scale inverse neural vocoder [12] and their seq2seq and SampleRNN problem and due to existence of different pronunciations or models need to be separately pre-trained. speaking styles, decompressing a highly compressed source MAIKA [26] is a Macedonian TTS project that was made text into audio may cause difficulties in the learning task of public few months ago. However, there is no documentation an end-to-end model. The main problem is coping with large of how it works. Therefore, it is technically challenging to variations at the signal level for a given input. Moreover, 72 compare with a system that only has web interface which 3.3 Decoder generates sound. Tacotron model uses a content-based tanh attention decoder eSpeak [27] is an open source TTS project that also supports [18], where a stateful recurrent layer produces the attention Macedonian language. The documentation states that the query at each decoder time step. The input of decoder’s RNN Macedonian model is based on the Croatian - which has its is formed by concatenating the context vector and the limitations since the Macedonian language is quite different, attention RNN cell output. Decoder’s internal structure is a especially the pronunciation and the grammar. stack of GRUs with vertical residual connections [5], used for 3 speeding up convergence. A simple fully-connected output MODEL ARCHITECTURE layer is used to predict the decoder targets. Its target is 80- The backbone of Tacotron is a seq2seq model with attention band mel-scale spectrogram, later converted to waveform by [7][13]. Figure 1 illustrates the model, which includes an a post-processing network. It predicts multiple, non- encoder, an attention-based decoder, and a post-processing overlapping, output frames at each decoder step. Predicting net. At a high-level, this model takes characters as input and r frames at once divides the total number of decoder steps by produces spectrogram frames, which are later converted to r, which reduces model size, training and inference time and waveforms. These components are described below. increases convergence speed. This is likely because neighboring speech frames are correlated and each character usually corresponds to multiple frames, plus emitting multiple frames allows the attention to move forward early in training. For defining the input of the next decoding step “teacher forcing” mechanism is used, pointing that on each time step, decoder’s input is the ground-truth value of the previous predicted decoder output. 3.4 Attention Mechanism Attention mechanism is applied in order to “learn” mappings between input and output sequences through gradient descent and back-propagation. It is used as a way for the decoder to learn at which time step, which internal state of Figure 1: Model architecture the encoder deserves more attention when generating its 3.1 current output. The whole process of calculating the CBHG Module attention weights and using them to form the decoder input CBHG is a module for extracting representations from has been illustrated in Figure 2. sequences. It consists of bank of 1-D convolutional filters, followed by highway networks [14] and a bidirectional gated recurrent unit (GRU) [15]. The input sequence is first convolved with k sets of 1-D convolutional filters. These filters explicitly model local and contextual information (creating unigrams, bigrams, up to k-grams). Next the convolution outputs are stacked together and max pooled along time to increase local invariances. Further the processed sequence is passed to a few fixed-width 1-D convolutions, whose outputs are added with the original input sequence via residual connections [16]. Batch normalization [17] is used for all convolutional layers. Moreover, the fixed-width convolution outputs are fed into a multi-layer highway network to extract high-level features. Finally, a bidirectional GRU RNN has been stacked on top, extracting sequential features from both forward and backward context. Figure 2: What is behind the attention mechanism 3.2 Encoder 3.5 Post-processing Net and Waveform Synthesis The encoder extracts robust sequential representations of text. The input to the encoder is a character sequence, with The post-processing net is converting the seq2seq target to a each character represented as a one-hot vector and form that can be synthesized into waveforms [20][21]. Since embedded into a continuous vector. Onto each embedding is Griffin-Lim has been used as a synthesizer, the post- applied a set of non-linear transformations, known as “pre- processing net learns to predict spectral magnitude, sampled net”. The “pre-net” is represented as a bottleneck layer with on a linear-frequency scale. The Griffin – Lim algorithm dropout, helping convergence and improving generalization. allows convergence towards estimated phase layer. Phase’s A CBHG module transforms the “pre-net” outputs into the quality depends on the number of iterations applied. final encoder representation used by the attention module. Although more iterations may lead to overfitting, better Moreover, CBHG-based encoder reduces overfitting and audio is produced. Within our setup, Griffin-Lim converges makes fewer mispronunciations than a standard multi-layer after 50 iterations even though 30 iterations seems to be RNN encoder. enough. 73 3.6 Model Parameters information about the model formed up to that step, while the other two are an alignment plot and an audio file The log magnitude spectrogram is obtained using Hann synthesized by that mode. The synthesized audio file is used windowing with 50 ms frame length, 12.5 ms frame shift, and for checking the quality of the current model. The alignment 2048-point FT. 24 kHz sampling rate has been used for all plot shows if the decoder has learned which input state of the experiments. For both seq2seq decoder (mel-scale encoder is important for producing its current output. That spectrogram) and post-processing net (linear-scale means if there is an “A” on input, “A” should be produced as spectrogram) a simple L1 loss with equal weight has been sound for output. As a good alignment plot is considered the used. The model has been trained using a batch size of 4, one who looks like a diagonal line. This system was trained where all sequences are padded to a max length. for 5 days, reached 412 000 steps and got 412 different 4 models. The system started showing a good alignment on 63 DATASET 000th step. The last model was chosen as referent one. Its There is no public dataset of audio data in Macedonian training and test results sound much better and were more language, therefore we had to create one. We used publicly understandable than those generated from the other models. available books in Macedonian from the website of the National Association of the Blind of the Republic of North 5.2 Evaluation Macedonia. The books have been recorded by 5 speakers, 3 To estimate the model’s performance, we used 10, out of 14 male and 2 female. They are segmented using an algorithm random sentences as test examples. The results show that which separates input audio based on silence length and more than half of the synthesized audio files [22] were threshold. Silence length varies between 700 – 1000 ms. The successfully representing the input sequence of the model. audio clips were additionally padded with 700 ms at both This was empirically shown using a quantitative beginning and end to avoid sudden cut offs. questionnaire [23] answered by 42 subjects, 10 IT experts Next, the audio files were transcribed manually, aided by the and 32 general public volunteers. The questionnaire was written version of the audio book. The transcriptions are made up of 10 stages, for each of the 10 audio files. The void of any punctuation, capitalization, or any special reason for choosing 10 test examples was to make the characters, including numbers. They include only the 31 questionnaire more compact, smaller and quicker for the letters from the Macedonian alphabet and the space evaluators. Each stage contains 3 sub questions for the character to separate between words. The reason for this is currently observed audio file. The Mean Opinion Score (MOS) that the initial dataset was also used for another task (Speech [24] was used as a measure for answering i.e. scoring each Recognition) and the researchers removed the punctuations. one of it. MOS is a measure of audio quality. It is a subjective In this phase we could not retrieve the original raw data that measurement used to test the listener’s perception of the includes the punctuation. The final dataset contains 13,101 audio quality and clarity. A group of 42 subjects were asked audio files and transcripts in Macedonian language [25]. to do the questionnaire. Each audio file required to be scored Additional statistics about the dataset are listed in Table 1. with a score from 1-5 in terms of three criterions: naturalness, intelligibility and accuracy. Where naturalness To be mentioned, the goal of the dataset is not the dataset stands for the similarity of produced audio file with the itself, but how we can develop a deep learning, end to end, natural human speech, intelligibility or clarity of spoken multi-speaker TTS for Macedonian language. Detailed words and accuracy or how much the spoken sequence language analysis of the dataset is planned for another study, corresponds with the original, required to be spoken text. in which the focus will be more on the linguistically part of the dataset. The results from the questionnaire are shown in Table 2. Table 1: Dataset statistics Each row of the table represents the MOS for one of the three criterions, calculated separately for experts and volunteers. Total Clips 13 101 The calculations are done by summing the scores for each criterion and consequently averaging it. By analyzing the Total Words 188 521 results for each criterion is clear that, the experts score the model’s performance better compared to the volunteers. Distinct Words 28 791 Looking at the total score, experts evaluated the model’s performance for 0.265 better than the volunteers. We Total duration 25:36:20 speculate that the reason for this might be that when the experts are evaluating the model they also take into account Mean Clip Duration 7.04 sec the technical challenges and aspects of such system. On the other hand the volunteers simply evaluate the sound and its Min Clip Duration 0.73 sec quality. Additionally, in Figure 3 and Figure 4 we show the box-plots Max Clip Duration 97.6 sec (1.37 min) for the answers given by the experts and the volunteers respectively. The figures show that the accuracy is the 5 TRAINING AND EVALUATION characteristic that achieves the highest score, and the 5.1 naturalness is the characteristic that achieved the lowest Training score. We speculate that the reason for low naturalness score During the training phase there is an output produced on is the presence of sudden pauses when words should be every 1000th step. It takes few seconds for an output to be spoken or existence of mumbling instead of clear produced. Each output contains five files, three of which give pronunciation. There are only few such occurrences. 74 Table 2: MOS Score results will not be able to properly pronounce them. Note that this is not the case with all of the words not being present in the MOS Score training data, but in very rare occasions. Normally, the model will still generate speech even though a word is not present Experts Volunteers in the dataset. Accuracy 4.8 4.6 ACKNOWLEDGEMENT Intelligibility 4.5 4.2 We are thankful for the support of the NVIDIA Corporation and their generous donation of a Titan XP GPU. Naturalness 4.1 3.9 Total 4.5 4.2 REFERENCES [1] P.Taylor. Text-to-speech synthesis. Cambridge university press, 2009. [2] H. Zen, K.Tokuda,А.W.Black. Statistical parametric speech synthesis. Speech Communication, 51(11):1039–1064, 2009. [3] Y.Agiomyrgiannakis. Vocaine the vocoder and applications in speech synthesis. In Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on, pp. 4230–4234. IEEE, 2015. [4] W.Chan, N.Jaitly, Q.Le, and O.Vinyals. Listen, attend and spell: A neural network for large vocabulary conversational speech recognition. In Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on, pp. 4960– 4964. IEEE, 2016. [5] Y.Wu, M.Schuster, Z.Chen, Q.V.Le, M.Norouzi,W.Macherey, M.Krikun, Y.Cao, Figure 3: Box plot of all grades given by the volunteers Q.Gao, K.Macherey. Google’s neural machine translation system: Bridging the gap between human and machine translation. arXiv:1609.08144, 2016. [6] I.Sutskever, O.Vinyals,Q.V.Le. Sequence to sequence learning with neural networks. 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If those [27] eSpeak: http://espeak.sourceforge.net/ embeddings have never been seen during training, the model 75 Improving Mammogram Classification by Generating Artificial Images Ana Peterka† Zoran Bosnić Evgeny Osipov University of Ljubljana, University of Ljubljana, Luleå University of Technology, Faculty of Computer and Faculty of Computer and Department of Computer Science, Information Science, Information Science, Electrical and Space Engineering, Ljubljana, Slovenia Ljubljana, Slovenia Luleå, Sweden anapeterka1151@gmail.com zoran.bosnic@fri.uni-lj.si evgeny.osipov@ltu.se ABSTRACT imaging field due privacy concerns of the patients and the time consuming expert annotations. Furthermore, the data is often Training a deep convolutional neural network (DCNN) from the imbalanced, meaning that pathologic findings are relatively very scratch is difficult, because it requires large amounts of labeled rare. This can result in overfitting the model and bad training data. This is a big problem especially in the medical generalization ability. domain, since datasets are scarce and data is often imbalanced. So far, this problem has been addressed with transfer learning This can result in overfitting the model. Fine-tuning a model that and data augmentation techniques. In this paper, we evaluate has been pre-trained on a large dataset shows promising results. these techniques on the CBIS-DDSM dataset, which is a publicly Another approach is to augment the dataset with artificially available dataset that contains benign and malignant generated learning examples. In this paper, we augment the mammograms. We propose a novel approach of generating new learning set with artificially generated images that are produced images with Generative Adversarial Networks (GANs) by conditional infilling GAN. The results that we obtained show combined with traditional data augmentation, such as horizontal that we can relatively easily generate realistically looking flipping, rotations etc., and evaluate if increasing the dataset mammograms that improve the classification of benign and helped to achieve better classification. We also test if fine tuning malignant mammograms. a ResNet-50 model helps improve the results. The paper is structured as follows. Section 2 presents the KEYWORDS related work, Section 3 describes the data augmentation data augmentation, transfer learning, CNN, ResNet-50, GAN, techniques used, Section 4 the training process, Section 5 the ciGAN evaluation metrics used and the results, and in Section 6 we state our conclusions and discuss the prospective future work. 1 INTRODUCTION Breast cancer is a cancer that is found in the tissue of the breast, 2 RELATED WORK when abnormal cells grow in an uncontrolled way. It can affect This section provides a brief review of past work that falls down both women and men, though it is prevalent in women. Statistics to three categories: show that it has the highest mortality rate of any cancer in women 1. improved classification with traditional data worldwide and that 1 in 8 women in the EU will develop breast augmentation, cancer before the age of 851. Screening mammography helps 2. improved classification with generating synthetic images diagnose cancer at an early stage, which significantly increases using generative adversarial network, the survival rates. However, the evaluation of mammograms 3. transfer learning and fine tuning. performed by doctors and radiologists is tedious, lengthy and error prone, as it results in a high number of false positives. The problem with small datasets, especially in the medical New approaches in deep learning (DL), in particular domain, is that models that are trained on them tend to overfit the convolutional neural networks (CNNs), have proven their data. There are a lot of approaches to reduce it, like batch potential for medical imaging classification tasks. This could normalization, dropout, data augmentation and also transfer relieve radiologists and give patients quicker and more accurate learning. Traditional data augmentation based on affine diagnosis. However, the performance of CNNs are dependent on transformations, such as translation, rotation, shearing, flipping large labeled datasets, which are hard to obtain in the medical and scaling, is the most widely used and very easy to implement. They are ubiquitous in computer vision tasks and show very pro mising results [1]. However, they do not bring any new visual Permission to make digital or hard copies of part or all of this work for personal or features that could additionally improve the generalization of the classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full CNN. citation on the first page. Copyrights for third-party components of this work must Synthetic image generation with GANs enables more be honored. For all other uses, contact the owner/author(s). variability to the dataset and further improves robustness of the Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 1 https://www.europadonna.org/breast-cancer-facs/ 76 classification network. GANs were inspired by game theory, Images are in DICOM format, which is the standard for medical where two neural networks are pitted against each other using a imaging information. The data is already split in the training and minmax strategy. They were first introduced in [2], and they have testing set. We used a part of the testing set as a validation set for recently been applied to many different medical imaging the classification network. applications, mostly for image to image translation and image inpainting. In [3], the authors used conditional infilling GAN to 3.2 Traditional data augmentation synthesize lesions on mammograms. To compensate for the lack of training images, we used classical Transfer learning and fine tuning for mammography medical data augmentation techniques, in particular horizontal flipping, images was the main topic in [4] and [5]. In [4], they rotations of up to 30°, and zoom range from 0.75 to 1.25 and test demonstrated that a whole image model trained on DDSM can if this improved the performance of the CNN. be easily transferred to INbreast without using its lesion annotations and using only a small amount of training data. In 3.3 Data augmentation with GANs [5], the authors showed that fine tuning ResNet-50 model pre- To further augment and balance the dataset, we use a GAN trained on ImageNet can be used to perform tumor classification variant, called conditional infilling GAN (ciGAN) [3]. GANs are in CBIS-DDSM dataset. a type of generative models, which means they are able to In this paper, we will first use traditional data augmentation produce novel examples, based on the training data. They consist techniques and later additionally augment the dataset with of two neural networks, a generator and a discriminator, which applying the ciGAN (conditional infilling GAN). We will are pitted against each other. Generator tries to capture the data's evaluate the improvements with a fine tuned ResNet-50 model. distribution while the discriminator tries to distinguish real and generated examples. By training them simultaneously, the 3 AUGMENTING THE DATASET generator will get better at generating realistic data, while the discriminator gets better at distinguishing real and fake data. In In this section, we first describe the dataset, then we explain the the case of ciGAN, the generator is based on a cascaded traditional data augmentation methods used and a GAN method refinement network (CRN) [8], where features are generated at for synthesizing new images. multiple scales before being concatenated, which yields a more realistic image synthesis. 3.1 The CBIS-DDSM dataset In our approach, we apply the ciGAN to sample a location on CBIS-DDSM [6] is a publicly available dataset that contains a healthy mammogram and then synthesize a lesion in its digitized images from scanned films of mammogram images and location, as shown in Figure 1. The input is a concatenated stack it is a subset of the DDSM dataset that consists of only benign of: and malign cases, while the DDSM also contains normal. The  a corrupted image (one channel grayscale image with data was acquired from 1566 patients and it contains both lesion replaced by uniform distribution of values between mediolateral oblique (MLO) and craniocaudal (CC) views of 0 and 1), each breast. Images are grayscale, and they have corresponding  a binary mask that marks lesion (1 representing the binary masks that indicate mass and ROI images of that mass. location of the lesion, and the zeros elsewhere), and Figure 1: The ciGAN architecture. The input consists of two one channel images, and 2 class channels for indicating malignant/benign label. Output of the generator is, together with the real image fed into the discriminator, which predicts whether each image is either generated or original and also whether the image contains benign or malignant lesions. 77  the class label ([1,0] representing the non-malignant class, extracted from pretrained networks [10]. It encourages the and [0,1] representing the malignant class). generator to output images with similar high level features The generator is comprised of multiple convolutional blocks. as the original image. In this case, the VGG-19 [11] convolutional neural network is used, pretrained on the The first convolutional block receives input stack, downsampled ImageNet dataset. It is defined as to the 4x4 resolution. Resolution is doubled between consecutive blocks. So the next convolutional block is fed with concatenation of the output from the first layer, upsampled to the 8x8 and an input stack resized to 8x8. This is repeated until resolution of where R denotes a real image, S a synthetic image and a 256x256 is obtained. The discriminator has similar, but inverse feature function; structure.  Boundary Loss: is used to encourage smoothing between infilled components and the context of the generated image. 3.4 Differences to the related work It is a L1 difference between the real and generated images Our work is based on the before mentioned ciGAN [3], with a at the boundary and defined as few improvements. While the former method was trained on non- malignant versus malignant cases, our approached uses benign and malignant cases, since we believe that the real hardship is where w denotes the mask with Gaussian filter of standard distinguishing the lesions and not only noticing them. Images in deviation 10 applied, and is the element wise product; the original work show that for acquiring synthetic non-  Adversarial Loss: is the general GAN loss. It is defined as a malignant mammograms, the lesion was removed, making the distance between the true and the generated distribution at picture a normal mammogram. Since we used a sliding window the current iteration. Its goal is to converge to the approach of extracting normal patches instead of the mask, we equilibrium in the minmax game between generator G and did not have to remove the malignant lesion, but we applied both discriminator D, as follows: masks independently, so we obtained only benign and malignant cases. All generated benign cases contain a lesion. We also applied zooming and rotation to lesions before generating new images, hence our generated images have more diverse tumors. where c denotes the class label. 4 GENERATING ARTIFICIAL IMAGES 4.3 Training The ciGAN is first pretrained on perceptual loss for 300 epochs. 4.1 Preprocessing Then the training of discriminator and generator are alternating, To extract patches of 256x256 pixels that are fed into ciGAN, we when loss for either drops below 0.3 for additional 2000 epochs. used a sliding window technique. The program loops through the The ciGAN produces realistic images as shown in Figure 2. whole mammogram image with the stride of 128 and checks if the rectangular region overlaps the majority of the breast. It also checks whether the patch contains lesion or it shows only normal breast tissue, and labels it accordingly. This is done by comparing the same region of the corresponding binary mask. At the end the patch dataset contains 5466 images, 1743 of them are normal, 2198 benign and 1525 malignant. After acquiring a dataset of patches, the program loops through all the patches containing only normal tissue. For each normal patch, it randomly chooses one patch that contains a 1. Normal image 2. Random malignant mask lesion. The patch with lesion is then randomly zoomed in/out by a small factor, to obtain more diverse masses. Next, we check whether on the same location as is lesion, on the normal patch, is only breast tissue and not background. If not, the next random lesion patch is chosen and the whole process is repeated until a suitable match is found. Once there is a suitable pair obtained, the normal image is corrupted, by replacing the area defined by the mask of the lesion with uniform distribution. 4.2 Loss functions 3. Corrupted image 4. Generated image The ciGAN model is trained by utilizing three loss functions [3]: Figure 2: A generated sample from ciGAN. Image 1 is the  Perceptual loss: is a loss calculated between the ground truth normal image without a lesion, image 2 is the binary mask and the output image. But unlike a per-pixel loss, which is representing the random malignant lesion, image 3 is the based on differences between pixels, it measures the corrupted image and image 4 is the synthesized image with discrepancy between high-level perceptual features malignant lesion. 78 5 EVALUATION AND RESULTS Testing these methods on different medical datasets shall be the subject of future work. As well, one may consider using these For evaluation of results three metrics were used. The first one is methods on bigger data sets and improve the current state of the accuracy, which tells us how many examples were correctly art algorithms. Since the ciGAN’s discriminator was also classified. The second one is recall/sensitivity, which is the conditioned on class, we intend on extracting its features and fraction between true positives and the sum of true positives and using it for classification on other mammography dataset, for false positives. It is the most important metric in this case, due to example on the INBreast dataset. We also plan on adding more the risk of overlooking cancer. The third one is Area Under synthetic images to the dataset, to see if we can further improve Curve (AUC), which measures area under the ROC curve. We the classification. evaluate the results by performing 4 experiments: Currently, the mammogram classification is performed by 1. Shallow CNN [12]: we implement it as the baseline. The the doctors and radiologists, but we hope that improving the network is fed a patch and classifies it as either malignant classification with the use of machine learning combined with or benign. It consists of three convolutional blocks, these and similar techniques could relieve them of such tasks in composed of 3x3 Convolutions, Batch Normalization, the near future. ReLU activation function and Max Pooling, followed by three Dense layers, and softmax function for binary Table 1: The obtained accuracy, recall and AUC scores classification. 2. ResNet-50: we classify the data using a ResNet-50 [13]. accuracy recall AUC 3. ResNet-50 with finetuning: we check if transfer learning improves the results. Shallow CNN 0.57267 0.44810 0.54943 4. ResNet-50 + Traditional data augmentation, Resnet-50 without 5. ResNet-50 + Traditional data augmentation and generated 0.58295 0.53859 0.58634 finetuning artificial images. ResNet-50 0.60155 0.55769 0.59443 As mentioned in [5], we fine-tuned the Resnet-50 [12] model with ImageNet weights. It is an extremely deep neural network ResNet-50 0.67132 0.64231 0.66666 + traditional with 150+ layers and consists of convolutional layers, pooling layers and multiple residual blocks. In the residual blocks, the ResNet-50 layers are fed into the next layer and also directly into the layers + traditional 0.76145 0.61538 0.71638 about two to three hops away. The input to the ResNet-50 model + artificial is a patch of a size 224x224x3. Since mammograms have only grayscale channels, the color information is copied over all three channels. We used the Adam optimizer with an initial learning REFERENCES rate of 10−5, 𝛽1 = 0.9, 𝛽2 = 0.999, 𝑒 = 10−8 and ImageNet [1] Wang, J., & Perez, L. (2017). The effectiveness of data augmentation in weight initialization. We trained it for 50 epochs with batch size image classification using deep learning. Convolutional Neural Networks Vis. Recognit, 11. of 32 and a 0.9 learning rate decay every 30 epochs. 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In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 770-778). compared to distinguishing non-malignant and malignant images. 79 Mobile Nutrition Monitoring System: Qualitative and Quantitative Monitoring Nina Reščič Marko Jordan Jasmijn de Boer nina.rescic@ijs.si Department of Intelligent Systems, ConnectedCare Department of Intelligent Systems, Jožef Stefan Institute Nijmegen, Netherlands Jožef Stefan Institute Ljubljana, Slovenia International Postgraduate School Jozef Stefan Ljubljana, Slovenia Ilse Bierhoff Mitja Luštrek ConnectedCare mitja.lustrek@ijs.si Nijmegen, Netherlands Department of Intelligent Systems, Jožef Stefan Institute Ljubljana, Slovenia ABSTRACT Edison et al. [8] proposed a method that recognizes each intake 1 gesture separately and later the intake gestures within 60 minutes The WellCo project aims to provide a mobile application featur- interval are clustered. ing a virtual coach for behaviour changes aiming to achieve for For qualitative monitoring we evaluated both dietary recalls healthier lifestyle. The nutrition monitoring module consists of and FFQs as self-reporting methods. However, dietary recalls two main parts - qualitative (Food Frequency Questionnaire) and require typing or complex food item selection which can be quantitative (eating detection and bite counting). In this paper cumbersome on mobile devices, so we opted for FFQ. FFQs are we present the nutrition monitoring module that connects both the most commonly selected tools in nutrition monitoring as they monitoring aspects as implemented in the virtual coach (mobile are efficient, cost-effective and non-invasive [9, 6].The developed application). FFQ covers all key aspects of healthy diet, and is modular, so that KEYWORDS only questions pertaining to certain aspects can be asked. This is important in ubiquitous settings where one wishes to minimize nutrition monitoring, eating detection, FFQ the required inputs from the user. 1 INTRODUCTION To our knowledge the developed application module is the first one to combine qualitative (validated FFQ) and quantitative mon- Proper nutrition habits are beneficial for healthy lifestyle and itoring (bite counting method) and to provide recommendations help to prevent many chronic diseases, such as cancer, diabetes based on data gathered by monitoring. and hypertension. Automated monitoring has become really im- portant i nutrition monitoring, but in only gives quantitative information (when is the user eating, how much did he eat...), 2 METHOD while qualitative information (what is the user eating) is acquired by using 24 hour food recall diaries or by using Food Frequency 2.1 Method Overview Questionnaires (FFQs). In the WellCo project we aimed to devel- The paper describes the nutrition monitoring module developed oped a user friendly nutrition module, which monitors qualitative in the Wellco project. and quantitative aspects of users’ nutrition. We combined the The qualitative monitoring starts with a five-question ques- self-reported FFQ, Extended Short Form Food Frequency Ques- tionnaire that provides essential information about the user’s tionnaire (ESFFFQ), developed and validated in the project project diet. Based on this, some goals to improve the user’s nutrition [5], with automated monitoring by using a commercially avail- can already be recommended. However, the users are invited able wearable smartwatch. This paper describes the developed to answer a more extensive questionnaire that paints a more module and the improvements we made since our previous pa- complete picture and allows recommending more goals. This pers [5, 2, 7]. questionnaire is an extended version of a validated questionnaire, By using wrist-worn devices to collect data, it is possible to rec- and the extension was validated by us [5]. How successful the ognize eating gestures [4] or even count ’bites’ or assess caloric users are at achieving their goals is monitored with goal-specific intake [10]. Mirtchou et al. [3] explored eating detection by us-questions on a bi-weekly basis. ing several sensors and combining real-life and laboratory data. The quantitative monitoring uses the accelerometer and 1 gyroscope in a smartwatch to detect micromovements related to http://wellco- project.eu eating (e.g., picking up food, putting it into the mouth). From a se- Permission to make digital or hard copies of part or all of this work for personal quence of such micromovement, we then recognise whether the or classroom use is granted without fee provided that copies are not made or user has made one “bite” (taken the food to the mouth). The im- distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this proved method uses a Convolutional neural network to recognise work must be honored. For all other uses, contact the owner /author(s). the micromovements and a LSTM neural network to recognise Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia bites. The latter achieved higher accuracy so it was the one se- © 2020 Copyright held by the owner/author(s). lected to be integrated into the WellCo system. 80 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Reščič and Jordan, et al. 2.2 FFQ - Qualitative Monitoring First we linearly interpolated all accelerometer and gyroscope measurements as well as the probabilities of bites to 4Hz fre- When choosing goals that would help users of the WellCo virtual quency. Next, the normalization was applied to interpolated ac- coach towards behavioural changes for healthier lifestyle, we celerometer and gyroscope data. We constructed 90 s long sliding were leaning on national dietary recommendation and dietary windows with a 2.5s step. Each window contained 360 of the recommendations for elderly, combined with expert knowledge previously obtained accelerometer, gyroscope and bite probabil- by the nutritionist involved in the project. A summary of national ity values (obtained with CNN and LSTM networks as described dietary recommendations is presented in Table 1. in [2]). 4Hz frequency was used to achieve faster training and Guidelines specifically for the elderly are very similar to na- predicting, while also enabling us to construct longer windows. tional dietary recommendations for all three countries involved in A window was labelled as a positive instance, if the majority of pilots (Italy, Spain and Denmark), but they put additional empha- the window belonged inside a meal. sis on dairy consumption, as this is a good source of proteins and To solve this machine learning task, an inception-type neural calcium, which are beneficial and often under-consumed; drink- network was constructed, with the added GRU layers at the end. ing enough water, as dehydration is often a problem with elderly; The inception part of the network is mainly made of two types of and leucine consumption (in milk, peanuts, oatmeal, peanuts, fish, inception blocks. Both types consist of convolutional layers and poultry, egg white, wheat sprouts, etc). Given these recommenda- end with a filter concatenation. The B block includes also a max tions, we chose goals we will suggest WellCo users to follow and pooling operation. Each block in the network is succeeded by a use in order to improve their diet: fruit consumption, vegetable consumption max pooling layer. The entire architecture is presented in Table , salt consumption, fat consumption, fibre consump- tion 1. The inputs were transformed in the (batch size,timestamps,1,7) , protein consumption, salt consumption, fish consumption and water consumption shape. “Prep” (preparation) in Table 1 refers to the yellow con- . volutional layers in Figure 5, whereas “Pool proj” refers to 1x1 In our search for a comprehensive but still short FFQ we found convolutional layer after 4x1 max pooling layer. The final model a validated questionnaire named Short Food Frequency Question- used approximately 130 K parameters. naire (SFFQ)[1], which consists of 23 questions and fully covers With the intention of smoother and better learning, the ratio five of our chosen goals – fruit and vegetable consumption, sugar consumption between positive and negative instances was fixed to 1:2. During , fat consumption and fish consumption. To cover the the sampling, we actually focused more on problematic areas, by four missing goals (protein, fibre, salt and water consumption) first predicting with the network and then selecting problematic we added additional 8 questions, turning the SFFQ into the so- instances to train on. Learning rate was set to keep decreasing called Extended Short Food Frequency Questionnaire (ESFFQ). every few epochs. Certain hyper-parameters were subject to The validation of the questionnaire is described in our previous optimization during cross-validation, with the help of hyperopt paper [5]. library. The function to minimize was categorical cross entropy. In the next part, the outputs ∈ [0,1] of the neural network, 2.3 Quantitative Monitoring which represent the probabilities that the given windows are eating instances, are taken to form possible/candidate meals. The main objective of the smartwatch-based nutrition monitoring This is done in the following manner: is bite counting (counting the number of time the user takes food to the mouth). • Round 1: Find all probabilities, denoted as beacons, that The bite-counting algorithm described in [2] was used as the are higher than a p1 threshold. Include also all probabilities base for all of the following work. When deciding how to present that are closer than t1 seconds to any of the beacons. Set the results of the developed algorithm to the users in the mobile all the other probabilities temporarily to 0. application, we had to make some improvements to our model. As • Round 2: Find all probabilities that are higher than a p2 the number of bites does not really give much useful information threshold and group them together, if they are immediately to the users, we decided to join individual bites into meals and next to each other. For each group find the time distance to recognize meals as snack, small meal or big meal. to its nearest group. Finally remove all groups that have either 1 or 2 members and are more than t2 seconds away 2.3.1 Datasets. To construct the bite detection algorithm, we from the corresponding nearest group. created the Wild Meals Dataset (WMD). It includes 51 sessions • Round 3: If there exist any two groups of the form [A,B] and 99 meals, with known starting and ending time points, be- and [C,D], where 0 ≤ C − B ≤ t3 (all in seconds), combine longing to 11 unique subjects, recorded ’in-wild’. For 68 of those these two groups together to form a new group, [A,D]. meals we have also obtained the approximate number of the This means that indices in [A,D] can now represent the corresponding bites, since the subjects were asked to count them probabilities of zero as well. while eating. Additionally we used the publicly available The • Round 4: Similar as Round 3, but with a t4 parameter in Food Intake Cycle (FIC) dataset and The Free Food Intake Cycle place of t3. (FreeFIC). All datasets contains tri-axial signals from accelerome- At this point the probabilities of windows, previously temporar- ters and gyroscopes in wrist devices with the sampling frequency ily set to zero, are switched back to their original values. For of 100 Hz. the final model, we obtained the following values of the above hyperparameters: 2.3.2 Meal detection method. The algorithm for meal detection Since p2 > p1, this means that Round 1 in this particular case was comprised of two parts: in the first part probabilities that was not necessary, although in some other cases it could have given time periods are part of eating were assigned, whereas been. Once the candidate meals have been obtained, the features in the second part these probabilities were grouped together to are constructed for the ensemble of random forest, support vector form a meal. machine, knn and gradient boosting algorithms. The ensemble 81 Mobile Nutrition Monitoring System: Qualitative and Quantitative Monitoring Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Table 1: Architecture of the network Type Units/Nodes Kernel/stride Output 1x1 4x1 prep 4x1 6x1 prep 6x1 Pool Inception-A 360x1x128 32 64 32 Max pool 3x1/2 180x1x128 Inception-B 180x1x128 32 64 64 16 16 16 Max pool 3x1/2 90x1x128 Inception-B 90x1x128 32 64 64 16 16 16 Max pool 3x1/2 45x1x128 Inception-B 45x1x128 32 64 64 16 16 16 Max pool 3x1/2 23x1x128 GRU 23x32 GRU 32 Dense 64 64 Dropout(0.36) 64 Dense 2 2 Table 2: Hyperparameters. Table 3: Results of bite recognition and meal detection al- gorithm. p1 t1(sec) p2 t2(sec) t3(sec) t4(sec) 0.46 61 0.87 120 63 61 F1-score precision recall cov_area outside_area Avg. 0.76 0.88 0.72 0.81 0.03 makes the final decision whether a candidate meal is in fact a Table 4: Example of recommendations for qualitative meal or not. The following features are created for each candidate monitoring (goal_sugar) and quantitative monitoring (nu- meal: trition_number_of_meal). • The mean, standard deviation, the 25th, 50th and 75th percentile of all the probabilities inside a given candidate goal_sugar It seems you don’t eat enough veg- meal. etables. Vegetables are important • The mean and standard deviation of the first and second sources of many nutrients, such as half of a potential meal, separately. vitamins, minerals and dietary fibre. • The mass of all the future probabilities inside all the poten- Try to eat 2 servings of vegetables tial meals closer than 3 hours to a given candidate meal, per day. Serving is 1 cup of fresh or divided by their time centre. half cup of cooked vegetables. • The mass of all the past probabilities inside all the poten- nutrition_number_of_meal Try to eat 3–5 meals per day (e.g. 3 tial meals closer than 3 hours to a given candidate meal, bigger, 2 smaller). Avoid snacking divided by their time centre. between meals. Hyper-parameters for each model in the ensemble, as well as p1, t1, p2 t2, t3 and t4 values, were calculated with a cross-validation, with the help of hyperopt library. The function to minimize was • For F1-score, precision and recall, def A was used, while negative F1-score. cov_area and outside_area used def B. However, double cross-validation results show that all ground truth meals, 3 RESULTS with one exception, had at most one corresponding, true 3.1 Bite Counting positive predicted meal. • Covered area (cov_area): for a given ground truth meal, In Table 4 we present the results of evaluation of our work. The the length of the areas, which laid inside the ground truth analysis of the entire pipeline is based on Leave-One-Subject-Out meal, of the corresponding true positive meals, divided by double cross-validation. For calculation of the above statistics the length of the ground truth meal. the following definitions were used: • Outside area (outside_area): for a given predicted, true • True positive prediction of a meal: any prediction of the positive meal, the length of the area that laid outside the respective meal for which the majority of the prediction corresponding ground truth meal, divided by the length laid inside the ground truth meal. If there was more than of the predicted meal. one prediction of eating for a certain meal, only one pre- diction is actually counted as a true positive, whereas all 3.2 Application Implementation the others are not regarded as a false positive.. This is due to the possibility that the subjects didn’t eat their en- The application shows users the detected meals, number of bites tire recording time; as such it did not seem reasonable to and score quality for the chosen goals (see Figure 1). Based on penalize the pipeline for predicting more than one meal, the results we additionally show the user recommendations to however, only one true positive is counted in order not follow in order to improve their nutrition. Example for recom- to encourage the algorithm to predict a bundle of eating mendations for both, qualitative and quantitative monitoring is instances. shown in table. 82 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Reščič and Jordan, et al. Figure 1: Application view for both monitoring tasks. 4 CONCLUSION [3] Mark Mirtchouk, Drew Lustig, Alexandra Smith, Ivan Ching, Min Zheng, and Samantha Kleinberg. 2017. Rec- The developed nutrition monitoring module consists of two parts ognizing eating from body-worn sensors: combining free- - qualitative monitoring and quantitative monitoring. Both of the living and laboratory data. 1, 3. doi: 10.1145/3131894. developed modules are implemented in a mobile application. In [4] Raul I. Ramos-Garcia, Eric R. Muth, John N. Gowdy, and our future work we would like to improve the developed eating Adam W. Hoover. 2014. Improving the recognition of eat- detection and bite counting algorithms. ing gestures using intergesture sequential dependencies. The developed FFQ (ESFFFQ) can be used to support a wide IEEE Journal of Biomedical and Health Informatics, 19, 3, range of nutrition goals and minimizes the number of questions 825–831. asked, so it is suitable for mobile nutrition monitoring. To make [5] Nina Reščič, Eva Valenčič, Enej Mlinarič, Barbara Koroušić the application user friendly the questions from the FFQ will Seljak, and Mitja Luštrek. 2019. Mobile nutrition monitor- not be asked all at the same time, but separately during a course ing for well-being. In Adjunct Proceedings of the 2019 ACM of fortnight. This means that some of the questions won’t be International Joint Conference on Pervasive and Ubiquitous asked, hence it is really important to ask the right questions. In Computing and Proceedings of the 2019 ACM International our future work we will try to explore the problem of question Symposium on Wearable Computers (UbiComp/ISWC ’19 ranking. With this we would be able to ask the questions in a Adjunct). London, United Kingdom, 1194–1197. specific order and loose as few information as possible. [6] JS Shim, K Oh, and HC Kim. 2014. Dietary assessment 5 ACKNOWLEDGMENTS methods in epidemiologic studies. Epidemiol Health, 36. doi: 10.4178/epih/e2014009. WellCo Project has received funding from the European Union’s [7] Simon Stankoski, Nina Reščič, Grega Mežič, and Mitja Horizon2020 research and innovation program under grant agree- Luštrek. 2020. Real-time eating detection using a smart- ment No 769765. watch. In Junction Publishing, USA. REFERENCES [8] Edison Thomaz, Irfan Essa, and Gregory D. Abowd. 2015. A practical approach for recognizing eating moments with [1] Christine L Cleghorn, Roger A Harrison, Joan K Ransley, wrist-mounted inertial sensing. In Association for Comput- Shan Wilkinson, James Thomas, and Janet E Cade. 2016. ing Machinery, New York, NY, USA. isbn: 9781450335744. Can a dietary quality score derived from a short-form doi: 10.1145/2750858.2807545. ffq assess dietary quality in uk adult population surveys? [9] Frances Thompson and T Byers. 1994. Dietary assessment Public Health Nutrition, 19, 16, 2915–2923. doi: 10.1017/ resource manual. The Journal of nutrition, 124, (December S1368980016001099. 1994), 2245S–2317S. doi: 10.1093/jn/124.suppl_11.2245s. [2] 2019. Counting bites with a smart watch. In Slovenian Con- [10] Shibo Zhang, William Stogin, and Nabil Alshurafa. 2018. ference on Artificial Intelligence : proceedings of the 22nd In- I sense overeating. Inf. Fusion, 41, C, (May 2018), 37–47. ternational Multiconference Information Society. Volume A, doi: 10.1016/j.inffus.2017.08.003. 49–52. 83 Recognition of Human Activities and Falls by Analyzing the Number of Accelerometers and their Body Location Miljana Shulajkovska, Hristijan Gjoreski miljanash@gmail.com, hristijang@feit.ukim.edu.mk Faculty of Electrical Engineering and Information Technologies Ss. Cyril and Methodius University Skopje, N. Macedonia ABSTRACT the voluntary interaction of the users with the sensors. In the latter, the sensors are attached to the user. This paper presents an approach to activity recognition and This paper presents a machine learning approach to fall detection using wearable accelerometers placed on activity recognition and fall detection using wearable different locations of the human body. We studied how the accelerometers placed on different locations of the human location and the number of wearable accelerometers body. The goal of the paper is to study how the location and influence on the performance of the recognition of the the number of wearable accelerometers in luence on the activities and the falls. The final goal was to build a machine performance of the recognition of the activities and the falls. learning model that can correctly recognize the activities and This study is of practical importance of such systems, i.e., to the falls using as few accelerometers as possible. The model build a machine learning model that can correctly recognize was evaluated on a public dataset consisting of more than the activities and the falls using as few accelerometers as 850 GB of data, recorded by 17 people. In total we evaluated possible. 15 combinations of four accelerometers placed on the belt, the left ankle, the left wrist and the neck. The results showed that the neck and the ankle accelerometers proved sufficient 2 RELATED WORK to correctly recognize all the activities and falls with 94.2% A considerable amount of work has been done in human accuracy. Each of the sensors used individually achieved activity recognition for the last decade where a lot of studies 94.02% and 93.4% accuracy respectively. aim to identify activities based on data obtained from KEYWORDS accelerometers as sensors widely integrated into wearable systems [3][4]. activity recognition, fall detection, wearable sensors, Researchers have reported high accuracy scores in machine learning detecting activities when investigating the best placement of the accelerometer on the human body [5][6][7]. Increasing 1 INTRODUCTION the number of sensors increases the complexity of the classi ication problem. For these reasons, a number of According to United Nations World Population Prospects studies have investigated the use of a single accelerometer. 2019, by 2050, one in six people in the world will be over the However, doing so generally decreases the number of age of 65 [1]. As people are getting older, their risk for falls activities that can be recognized accurately [8]. Consequently, also increases. Falls are a major public health problem in one of the major considerations in activity recognition is the elderly people often causing fatal injuries. It is important to location or combination of locations of the accelerometers assure that injured people receive assistance as quickly as that provide the most relevant information. possible. Because of this, building a good fall detection In [5] the authors study the best location to place system is of a big importance to help medicine solve this accelerometers for fall detection, based on the classi ication problem. of postures. Four accelerometers were placed at the chest, The ield of Human Activity Recognition (HAR) and fall waist, ankle and thigh. Statistical features were calculated for detection has become one of the trendiest research topics each axis of the accelerometer in addition to the magnitude. due to availability of low cost, low power consuming sensors, Results indicated that one accelerometer (chest or waist) by i.e., accelerometers. The recognition of human activities has itself was not enough to suf iciently classify the activities been approached in two different ways, namely using (75%). There was, however, a signi icant improvement in ambient and wearable sensors [2]. In the former, the sensors classi ication accuracy achieved by combining the are ixed in predetermined points of interest on the body of accelerometer at the chest or waist with one placed on the the subject, so the inference of activities entirely depends on ankle (91%). Following the work described in [5] we explore ∗ Both authors contributed equally to this research. this approach using different dataset while investigating all Permission to make digital or hard copies of part or all of this work for personal possible sensor placement combinations. or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 84 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia 3 ACTIVITY RECOGNITION datasets representing every combination of these sensors to show the importance of the placement of the accelerometer. 3.1 Dataset In our research the sampling rate of the sensor is 18 Hz, which means 18 samples are provided every second. In In this research we used the UP-Fall Detection dataset, which Figure 1Error! Reference source not found. the raw data is publicly available [9]. The dataset contains 17 Subjects that from 3-axis accelerometer is shown from person who is are performing 11 activities. Each activity is performed 3 performing three activities: standing, falling forward using times. The activities performed are related to six simple hands and laying. human daily activities and ive human falls showed in Table 1. These types of activities and falls are chosen from the 3.2 analysis of those reported in literature [10][11]. All daily Feature Extraction activities are performed during 60 s, except jumping that is Feature extraction is really important step in the activity performed during 30 s and picking up an object which it is an recognition process in order to ilter relevant information action done once within a 10-s period. A single fall is and obtain quantitative measures that allow signals to be performed in each of the three ten seconds period trials. compared. In our research we used statistical features to create the feature vectors. All the attributes are computed by using the technique of overlapping sliding windows [5]. Table 1: Activities performed in the Dataset Because the inal sampling frequency of our accelerometers was 18 Hz, we chose a window size of 18, Activity ID Description Duration (s) which is one second time interval. We decided for one- 1 Falling forward using hands 10 second time interval because in our target activities there are 2 Falling forward using knees 10 transitional activities (standing up and going down) that 3 Falling backwards 10 usually last from one to four seconds. Statistical attributes 4 Falling sideward 10 are extracted for each axis of the accelerometer. 5 Falling sitting in empty chair 10 The feature extraction phase produces 36 features 6 Walking 60 (summarized in Table 2) from the accelerations along the x, 7 Standing 60 y, and z axes. The irst three features (Mean X/Y/Z,) provide 8 Sitting 60 information about body posture, and the remaining features 9 Picking up an object 10 represent motion shape, motion variation, and motion 10 Jumping 30 similarity (correlation). 11 Laying 60 Once the features are extracted (and selected), a feature vector is formed. During training, feature vectors extracted In order to collect data from young healthy subjects from training data are used by a machine learning algorithm without any impairment, is considered a multimodal to build an activity recognition model. During classi ication, approach for sensing the activities in three different ways feature vectors extracted from test data are fed into the using wearables, context-aware sensors and cameras, all at model, which recognizes the active. the same time. However, of our particular interest is how acceleration data can be used for the recognition of activities. The analyzed data is obtained from accelerometers placed on Table 2: Overview of the extracted features. The number of features is represented with # ankle, neck, wrist and belt. This way we created 15 different Feature name # Mean (X, Y, Z) 3 Standard deviation (X, Y, Z) 3 Root mean square (X, Y, Z) 3 Maximal amplitude (X, Y, Z) 3 Minimal amplitude (X, Y, Z) 3 Median (X, Y, Z) 3 Number of zero-crossing (X, Y, Z) 3 Skewness (X, Y, Z) 3 Kurtosis (X, Y, Z) 3 First Quartile (X, Y, Z) 3 Third Quartile (X, Y, Z) 3 Autocorrelation (X, Y, Z) 3 3.3 Methods Machine learning approach was used for the activity Figure 1 Raw Data from 3-Axis Accelerometer recognition. In this study, the machine learning task is to learn a model that will be able to classify the target activities 85 Human Activity Recognition Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia (e.g. standing, sitting, falling, etc.) of the person wearing Four evaluation metrics are commonly used in activity accelerometers. For this purpose, we used 4 different recognition: the recall, precision, accuracy and F-measure. machine learning algorithms: Random Forest, Support We have analyzed the accuracy score, which shows how Vector Machine, k-Nearest Neighbors and Multilayer many of the predicted activities are correctly classi ied. Perceptron. The Random Forest (RF) classi ier, like its name implies, 4.2 Results consists of a large number of individual decision trees that For the irst experiment we compared 4 ML models using the operate as an ensemble. The fundamental concept behind RF ankle accelerometer - shown in Figure 2. We used the ankle is the low correlation between any of the individual accelerometer because our initial studies showed that it constituent models protecting each other from their performs the best. Random Forest showed the best results individual error. with 92.92% of accuracy. Therefore, it was used for further The Support Vector Machine (SVM) method has also been experiments. broadly used in HAR although they do not provide a set of Table 3 shows the comparison of activity recognition rules understandable to humans. SVMs rely on kernel accuracy using 4 accelerometers placed on ankle, belt, neck functions that project all instances to a higher dimensional and wrist. It shows how the number and placements of space with the aim of inding a linear decision boundary (i.e., accelerometer can affect the recognition of particular a hyperplane) to partition the data. activities. The k-Nearest Neighbors (k-NN) is a supervised classi ication technique that uses the Euclidean distance to 100 92.92 classify a new observation based on the similarity (distance) 90.14 92.43 84.31 between the training set and the new sample to be classi ied. 80 The Multilayer Perceptron (MLP) [12], is an arti icial 60 neural network with multilayer feed-forward architecture. 40 The MLP minimizes the error function between the Accuracy in % 20 estimated and the desired network outputs, which represent 0 the class labels in the classi ication context. Several studies RF SVM MLP KNN show that MLP is ef icient in non-linear classi ication problems, including human activity recognition. Brief study Figure 2: Comparison of different algorithms using of MLP and other classi ication methods is shown in [13][14]. Ankle Accelerometer Placing the accelerometer on the belt can distinguish 4 EXPERIMENTS sitting, standing or jumping, but distinguishing different kind of falls that include some transitions, like standing, falling 4.1 Evaluation Techniques and then laying is a problem. Adding one accelerometer on the neck, can slightly improve the results, but still cannot To properly evaluate the models, we divided the data into recognize correctly the falls. Combination of neck and ankle train and test using leave-one-person-out cross-validation. accelerometer proved best results with 94.2% accuracy. On With the leave-one-person-out each fold is represented by the other hand, an accelerometer on the ankle can distinguish the data of one person. This means the model was trained on walking, standing and laying, but has problems with picking the data recorded for 16 people and tested on the remaining up an object and also recognizing the falls. Most of the fall person's data. This procedure was repeated for each person activities are recognized as standing or laying. By combining data (17 times) and the average performance was measured. Table 3: Comparison of activity recognition accuracy using different number of accelerometers (1, 2, 3 or 4) placed on ankle, belt, neck and wrist 86 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia this sensor with neck accelerometer, the algorithm can models and Random Forest showed best results. Then, we distinguish each of the discussed activities. compared the best model on different data, and we got the Because of situation like this, we decided to compare the conclusion that the data from ankle and neck sensors was results using different number of accelerometers and suf icient for human activity recognition and fall detection different body placements. The idea is to use as few sensors process with accuracy of 94.2%. as possible to maximize the user’s comfort, but to use enough of them to achieve satisfactory performance. REFERENCES [1] United Nations Publications. World Population Ageing 2019 Highlights. Department of Economic and Social Affairs Population Division. [2] Labrador, Miguel A., and Oscar D. Lara Yejas. Human activity recognition: using wearable sensors and smartphones. CRC Press, 2013. [3] Ravi, N., Dandekar, N., Mysore, P. and Littman, M.L., 2005, July. Activity recognition from accelerometer data. In Aaai (Vol. 5, No. 2005, pp. 1541-1546). [4] Kwapisz, J.R., Weiss, G.M. and Moore, S.A., 2011. Activity recognition using cell phone accelerometers. ACM SigKDD Explorations Newsletter, 12(2), pp.74-82. [5] Gjoreski, H., Lustrek, M. and Gams, M., 2011, July. Accelerometer placement for posture recognition and fall detection. In 2011 Seventh International Conference on Figure 3: Confusion matrix for Neck and Ankle Intelligent Environments (pp. 47-54). IEEE. Accelerometer [6] Gjoreski, M., Gjoreski, H., Luštrek, M. and Gams, M., 2016. How accurately can your wrist device rcognize daily We must make a trade-off between correctly detecting activities and detect falls?. Sensors, 16(6), p.800. simple activity and speci ic fall. The results showed that neck [7] Atallah, L., Lo, B., King, R. and Yang, G.Z., 2011. Sensor and ankle accelerometers are best suited for fall detection positioning for activity recognition using wearable with overall accuracy of 94.19%. The confusion matrix for accelerometers. IEEE transactions on biomedical circuits neck and ankle accelerometers is shown in Figure 3. The and systems, 5(4), pp.320-329. most false positive predictions for fall activities are predicted [8] Bonomi, A.G., Plasqui, G., Goris, A.H. and Westerterp, K.R., as laying. Also, very small percent of the non-fall activities are 2009. Improving assessment of daily energy expenditure predicted as falls, which dismiss the false alarms for falls. by identifying types of physical activity with a single accelerometer. Journal of applied physiology. [9] The Challenge UP dataset: 5 CONCLUSION http://sites.google.com/up.edu.mx/har-up/ [10] Igual, R., Medrano, C. and Plaza, I., 2013. Challenges, issues In this paper we presented an approach to human activity and trends in fall detection systems. Biomedical recognition and how location and number of sensors can engineering online, 12(1), p.66. impact on the process of HAR. Our aim was to build a model [11] Z Zhang, C Conly, V Athitsos. 2015. A survey on vision-who can correctly recognize and classify the fall activities based fall detection. 8th ACM International Conference on using small number of accelerometers, but still can obtain PETRA '15, ACM, New York, NY, USA, Article 46, 1–7. high accuracy scores. With one accelerometer placed on the [12] Attal, F., Mohammed, S., Dedabrishvili, M., Chamroukhi, F., Oukhellou, L. and Amirat, Y., 2015. Physical human activity ankle or the neck we got high accuracy scores, but by recognition using wearable sensors. Sensors, 15(12), combining these two sensors the model can classify the falls pp.31314-31338. more precisely. [13] Altun, K., Barshan, B. and Tunçel, O., 2010. Comparative The main input to our system is the data from the inertial study on classifying human activities with miniature sensors. Because the data is sensory, additional attributes inertial and magnetic sensors. Pattern Recognition, 43(10), are calculated. This process of feature extraction is general pp.3605-3620. and can be used in similar problems. Next, the algorithms for [14] M. Gjoreski, V. Janko, G. Slapničar, M. Mlakar, N. Reščič, J. the inal tasks of activity recognition and fall detection are Bizjak, V. Drobnič, M. Marinko, N. Mlakar, M. Luštrek, M. designed and implemented using the data from the ankle Gams, Classical and deep learning methods for recognizing accelerometer. We used a machine learning approach for human activities and modes of transportation with smartphone sensors, Information Fusion, Volume 62, 2020, solving the problem of activity recognition. We evaluated the Pages 47-62, 1566-2535. 87 Sistem za ocenjevanje esejev na podlagi koherence in semantične skladnosti Automated Essay Evaluation System Based on Coherence and Semantic Consistency Žiga Simončič Zoran Bosnić Univerza v Ljubljani, Fakulteta za računalništvo in Univerza v Ljubljani, Fakulteta za računalništvo in informatiko informatiko Večna pot 113, 1000 Ljubljana Večna pot 113, 1000 Ljubljana zs3179@student.uni- lj.si zoran.bosnic@fri.uni- lj.si POVZETEK osredotočajo predvsem na sintaksno analizo, premalo pozornosti pa posvečajo semantiki [6]. To slabost obstoječih sistemov rešuje V članku opisujemo implementacijo sistema za ocenjevanje ese- sistem SAGE, ki ga Zupanc opisuje v svoji disertaciji [5]. SAGE jev v angleškem jeziku. Zgledujemo se po metodologiji obstoje- dosega zavidljivo napovedno točnost v primerjavi z ostalimi so- čega sistema, ki poleg ocenjevanja sintakse uporablja tudi mere dobnimi sistemi, vendar je trenutna implementacija sistema v koherentnosti in semantične skladnosti. Metodologijo implemen- prototipni fazi in ni zrela za produkcijo. tiramo v grafičnem okolju Orange, s prijaznim vmesnikom, op- Glavni cilj dela je bila implementacija sistema na način, da bo cijsko uporabo vektorskih vložitev za predstavitev besedila in uporabnikom čimbolj dostopen, enostaven in prijazen za upo- možnostjo nadaljnjega razvoja sistema. Sistem evalviramo na rabo. Da zadostimo tem ciljem, smo se odločili za implementacijo podatkih dostopnih na spletnem mestu Kaggle in, kolikor je mo- 1 v programskem okolju Orange, ki je namenjen hitremu pro- goče, rezultate primerjamo z rezultati dosedanje metodologije in totipiranju modelov in raziskovanju podatkov, namenjen tako jih podrobno analiziramo. Poglobimo se tudi v izbiranje atribu- začetnikom kot zahtevnejšim uporabnikom. Sistem je v Orange- tov za izboljšanje rezultatov. Glavni prispevki dela obsegajo (1) u implementiran v obliki gradnikov (angl. widgets). Med seboj implementacijo sistema, (2) enostavnost uporabe in (3) izboljšave jih lahko povezujemo in kombiniramo, tako da smo uvoz dato- dosedanjega dela, vključno z dodatnimi računskimi opcijami in tek, gradnjo in testiranje modelov prepustili gradnikom, ki so podrobno analizo izbiranja atributov za izboljšanje rezultatov. v Orange-u že implementirani. Skupno smo implementirali tri KLJUČNE BESEDE gradnike — prvi implementira vse atributske funkcije, vključno s koherenco, drugi implementira sistem za analizo semantične ocenjevanje esejev, semantična skladnost, Orange skladnosti, tretji pa je namenjen evalvaciji modela po kvadratno uteženi kapi. ABSTRACT Sistem Zupanc [6] temelji na ekstrakciji različnih atributov iz In this paper we describe an implementation of an essay grading podanih besedil (esejev) in se loči na tri (pod)sisteme: AGE, AGE+ system. We lean heavily on the methodology of an existing sys- in SAGE. Oznaka “sistem Zupanc” predstavlja njeno implemen- tem, which, besides using syntactical measurements, also uses tacijo vseh teh treh sistemov. Vsak sistem nadgradi prejšnjega coherence and semantic cosistency measures. We implement the z dodatnimi atributi. Sistem AGE predstavlja skupek atributov methodology in the Orange data mining tool, with a firendly user osnovne sintaktične statistike, berljivostnih, leksikalnih, slovnič- interface, optional use of word embeddings for word representa- nih in vsebinskih mer. To obsega različne značilnosti besedila, vse tion and the possibility for further developments of the system. od osnovnih, kot so število znakov, besed itd., pa do števila slov- The system is evaluated on public datasets from the Kaggle web- ničnih napak in računanje podobnosti z ostalimi eseji. Skupno ta site. The results are to the most possible extent compared with sistem zajema 72 različnih atributov, v prispevku tega članka pa the results of the existing methodology and analyzed in detail. smo temu sistemu dodali še pet novih atributov (št. znakov brez We also compare several attribute selection methods, which im- presledkov in štiri dodatne atribute, ki štejejo število posameznih prove our results. Main contributions of this work are comprised oblikoskladenjskih oznak). Skupno torej 77 atributov. of (1) implementation of the system, (2) ease of use and (3) im- Atributom sistema AGE dodamo atribute za merjenje kohe- provements upon previous work, including additional computing rence in s tem dobimo sistem AGE+. Koherenco merimo tako, options and detailed attribute selection analysis. da besedilo najprej razdelimo na prekrivajoče se odseke (drseče okno) in posamezne odseke pretvorimo v večdimenzionalni pro- KEYWORDS stor. V tem prostor lahko posamezne odseke primerjamo in z automated essay evaluation, semantic consistency, Orange različnimi merami ocenimo ocenimo konsistentnost besedila in tok misli. Število atributov za merjenje koherence je 29. 1 UVOD Če vsem zgornjim atributom dodamo še nabor treh atributov, ki jih pridobimo s preverjanjem semantične skladnosti, govo- Učitelji v izobraževalnih ustanovah so odgovorni za predajanje rimo o sistemu SAGE. Sistem za zaznavanje semantičnih napak v znanj velikemu številu učencev. Del učnega procesa je tudi pisa- ozadju uporablja ontologijo, kateri postopoma dodajamo dejstva, nje esejev, ki jih morajo učitelji prebrati in oceniti. Ocenjevanje ki jih izluščimo iz besedila. Z logičnim sklepanjem nato ugoto- esejev ni le časovno potratno, ampak potencialno tudi nekoliko vimo, če so trditve iz besedila logično konsistentne ali ne. To nam pristransko. Naloga učitelja je tudi, da napake označi, popravi in prinese tri dodatne atribute in možnost povratne informacije, v komentira celotno delo. katerih povedih je prišlo do semantičnega neskladja. S pomočjo računalnika lahko ocenjevanje esejev olajšamo. Dandanašnji sistemi za ocenjevanje esejev (tudi komercialni) se 1 https://orange.biolab.si/ 88 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Simončič in Bosnić 2 SORODNA DELA V sklopu svojega dela se je Zupanc [5] osredotočila na (v času njenega raziskovanja že zaključeno) tekmovanje avtomatskega 2 ocenjevanje esejev, ki ga je gostil Kaggle. Na tem tekmovanju so pomerili različni sistemi, s katerimi je Zupanc primerjala svoj sistem. Najboljša mesta na končni lestvici so večinoma zasedali komercialni sistemi za ocenjevanje esejev, nekaj pa je bilo tudi po meri narejenih uporabniških modelov. Komercialni sistemi 3 4 5 kot so PEG, e-rater in IntelliMetric imajo že dolgo zgodovino in s tem velik tržni delež ter izpopolnjen finančni model. V času raziskovanja noben od naštetih ni ponujal brezplačne verzije sistema. Podrobno razčlenitev modelov in splošen opis njihovega delovanja najdemo v delih Zupanc [5] ter Zupanc in Bosnić [6]. V zadnjem času se na različnih področjih čedalje bolj uve- ljavljajo nevronski modeli, zato smo pogledali in testirali nekaj izvedb. Martinc in sod. [3] opisujejo uspešnost treh različnih nevronskih modelov pri ocenjevanju besedil, ki sicer niso eseji. Tudi Taghipour in Tou Ng [4] sta primerjala različne nevronske modele za ocenjevanje esejev (na istih podatkih kot mi). Najboljši model dosega skoraj tak rezultat, kot mi. Alikaniotis in sod. so objavili članek [1], kjer so tudi testirali uspešnost različnih ne- vronskih modelov na enaki podatkovni zbirki esejev, kot smo jo uporabljali mi. 3 OPIS IMPLEMENTACIJE IN METODE 3.1 Uporabljena orodja Celoten sistem smo implementirali z uporabo orodja za podat- kovno rudarjenje Orange v programskem jeziku Python. Glavne Slika 1: Prikaz vseh treh gradnikov uporabljene knjižnice za razčlenitev besedila in izračun atributov 6 7 8 9 so NLTK, SpaCy, scikit-learn in language-check za zaznava- nje pravopisnih napak. Gradnik ima tri vhode: 10 Za delo z ontologijami smo uporabili knjižnico rdflib in (1) vhod za ocenjene eseje, zunanja sistema (v smislu samostojna lokalna programa) ClausIE 11 (2) vhod za neocenjene eseje in (na voljo tudi OpenIE5.0) in HermiT. (3) vhod za izvorno besedilo. 3.2 Implementacija gradnikov v Orange Vhoda za ocenjene in neocenjene eseje sta namenjena učni mno- žici ocenjenih esejev in množici neocenjenih esejev, ki jim ho- Skupno smo razvili tri gradnike, ki zajemajo celoten opisan sistem. čemo napovedati ocene. Na obeh množicah se izračunajo enaki Slika 1 prikazuje vse tri gradnike, ki so opisani v nadaljevanju. atributi. Atribute ocenjenih esejev uporabimo za gradnjo modela. Prvi gradnik je namenjen izračunu vseh različnih mer. To Vhod za izvorno besedilo je neobvezen in predstavlja izhodiščno so osnovne (plitke) statistične mere, mere berljivosti, leksikalne zgodbo, knjigo ali dejstva, ki naj bi jih pisec eseja poznal. Če mere, slovnične mere, vsebinske mere in mere koherentnosti. so eseji osnovani na podlagi nekega izvornega besedila, ga po- Gradnik predstavlja sistema AGE in AGE+, odvisno od uporabni- vežemo na ustrezen vhod in s tem izračunamo dodaten atribut kove izbire atributov, ki naj se izračunajo. Če označimo izračun (podobnost eseja z izvornim besedilom). Gradnik ima dva izhoda, vseh atributov, razen atributov za koherenco, govorimo o sistemu AGE in sicer izhod za izračunane atribute ocenjenih esejev in izhod , z dodanimi atributi za koherenco pa govorimo o sistemu AGE+ za izračunane atribute neocenjenih esejev. To nam omogoča, da . Ker je računanje nekaterih naprednih mer bolj zahtevno, podatke ustrezno nastavimo kot vhode v ostale Orange-ove gra- se lahko uporabnik odloči za izračun kakršnekoli kombinacije dnike. naštetih šestih skupin mer. Za vsebinske mere in mere koheren- Drugi gradnik obsega delo in iskanje semantičnih neskladno- tnosti je na voljo dodatna izbira metode pretvorbe besedila v sti z ontologijo. Predstavlja izračun dodatnih atributov, ki jih večdimenzionalni vektorski prostor. Tu podpiramo dve metodi: prinaša sistem SAGE. Gradnik je samostojen zaradi velike ra- statistično pretvorbo TF-IDF in vektorske vložitve GloVe (v dveh čunske in časovne zahtevnosti. Ima dve nastavitvi: ali želimo izvedbah: SpaCy in Flair). uporabiti razreševalnik koreferenc in ali želimo, da se nam za 2 https://www.kaggle.com/ semantične napake vrne podrobna razlaga. Uporaba koreferenc 3 https://www.measurementinc.com/products-services/automated-essay-scoring je priporočljiva, saj je v primerih posrednega navezovanja na raz- 4 https://www.ets.org/ lične pojme v besedilu to edini način zajetja celotne semantične 5 http://www.intellimetric.com/direct/ 6 informacije. Izberemo lahko tudi izvorno besedilo ali zgodbo, s https://www.nltk.org/ 7 https://spacy.io/ katerim se razširi ontologijo, tako da ta vključuje tudi vsebino 8 https://scikit-learn.org/stable/ osnovnega besedila. To besedilo se bo obdelalo pred vsem osta- 9 https://pypi.org/project/language-check/ 10 lim, izluščene trojice pa bodo dodane v ontologijo. Razširjena https://rdflib.readthedocs.io/en/stable/ 11 http://www.hermit-reasoner.com/ ontologija se bo uporabila za preverjanje skladnosti esejev. Če 89 Sistem za ocenjevanje esejev na podlagi koherence in semantične skladnost Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Za posamezen esej poiščemo koreference v besedilu (angl. co- reference resolution). Ugotavljanje referenc nam omogoča odkri- vanje posrednih referenc na določene entitete in zamenjavo z neposredno entiteto. Primer: “Bob likes pizza. He eats it all the time.” nadomestimo z “Bob likes pizza. Bob eats pizza all the time”. Naslednji korak je razčlenitev besedila na posamezne povedi in ekstrakcija informacij s pomočjo sistema OpenIE (angl. Open Information Extraction). V tem koraku posamezne povedi pretvo- rimo v eno ali več trojic, ki opišejo relacije, izražene v povedi in so primerne za logično obdelavo. Za zgornji primer bi tako dobili dve trojici: (Bob, like, pizza) in (Bob, eat, pizza). Uporabili smo sistem za ekstrakcijo ClausIE [2], podpiramo pa tudi mo- 13 žnost uporabe sistema OpenIE5. Vse pridobljene trojice nato postopoma dodajamo v ontologijo, obenem pa preverjamo njeno skladnost. Za vsak element trojice poskušamo v ontologiji najti Slika 2: Primer uporabe sistema AGE/AGE+ že obstoječ element. Pri tem preiščemo sopomenke, nadpomenke in protipomenke, v najslabšem primeru pa dodamo v ontologijo nov element. Po vsakem dodajanju elementov in trojic, preverimo skladnost ontologije. Skladnost preverjamo z logičnim sklepal- izvornega besedila ne dodamo, se za preverjanje skladnosti nor- nikom HermiT, ki vrača dva tipa napak. Prvi tip napak se zgodi, malno uporabi osnovna ontologija (ontologija COSMO). Gradnik ko ima nek razred (owl:class) prirejene entitete, ki jih ne sme ima samo en vhod — vhod za eseje ter en izhod — tabela treh imeti (unsatisfiable case). Drugi tip napak pa se proži, ko se s atributov o številu posameznih napak in niz z osnovno razlago sklepanjem ugotovi logična napaka — nekonsistentna ontologija ter dodatni stolpec s podrobno razlago, če je ta izbrana. (angl. inconsistent ontology). Do takšnih napak pride ponavadi Tretji gradnik je namenjen evalvaciji napovedanih ocen in zaradi neposrednih nasprotij (npr. owl:disjointWith) med dvema pravih ocen esejev. Ker Orange ne podpira mer za izračun natanč- relacijama, ki pravi, da entiteta ne more imeti obeh relacij hkrati). nega strinjanja (angl. exact agreement) in kvadratne utežene kape Na podlagi povzročenih tipov napak osnujemo tri dodatne (angl. quadratic weighted kappa - QWK ), smo naredili gradnik, atribute, ki jih lahko uporabimo pri napovedovanju ocen esejev: ki prejme tabelo z napovedanimi ocenami in pravimi ocenami. število neizpolnjenih primerov (pri dodajanju novih entitet v on- Zgledovali smo se po izhodu gradnika Test and Score — za zago- tologijo), število napak nekonsistentne ontologije (pri dodajanju tavljanje interoperabilnosti lahko ta izhod vežemo neposredno trojic) in vsota obeh prejšnjih. na vhod našega gradnika, kjer se izračunata prej omenjeni meri. Uporaba gradnika za izračun atributov in evalvacijo modela s 3.4 Rezultati kvadratno uteženo kapo je prikazana na Sliki 2. Sistem smo testirali na podatkih že nekaj let starega tekmovanja 14 ASAP na spletni strani Kaggle. Podatki obsegajo osem različnih 3.3 Semantična analiza podatkovnih zbirk (oz. devet, ker se druga zbirka ocenjuje po Eden glavnih prispevkov dela Zupanc in Bosnić [6] je uporaba dveh kriterijih). Tema esejev v vsaki podatkovni zbirki je različna. ontologij za ugotavljanje semantične skladnosti. Ta postopek je Zbirke so razdeljene na učno, validacijsko in testno množico, uporaben na dva načina: z njim pridobimo nekaj dodatnih atri- vendar ocene validacijske in testne množice niso na voljo, zato butov, ki jih lahko uporabimo pri napovedovanju ocen esejev, smo za evalvacijo našega sistema uporabili 10-kratno prečno pre- dodatno pa nam ta postopek tudi sporoči, kje se nahajajo seman- verjanje. Razpon ocen je v vsaki zbirki različen, gibljejo se od 0–4, tične napake. Slednja funkcionalnost je zelo pomembna, saj tako pa vse do 0–60. Za oceno modelov smo uporabili mero kvadra- učenec prejeme neposredno informacijo o napakah v eseju. tno utežene kape (angl. quadratic weighted kappa), ki upošteva Postopek temelji na uporabi ontologije, v katero postopoma razpon ocen in vrne relativno ujemanje napovedane ocene z de- dodajamo v relacije strukturirane stavke in sproti preverjamo jansko oceno. Sistem smo testirali na modelu linearne regresije skladnost ontologije. Osnovna struktura ontologije je predsta- in naključnih gozdov. Bolje se je odrezala linearna regresija, zato vljena s “trojicami” v obliki (osebek, relacija, predmet). Relacija smo se nanjo osredotočili v nadaljnjih eksperimentih. Uporabili lahko predstavlja omejitev, konceptualno povezavo (npr. (Alice, smo regularizacijo L2 s parametrom 𝛼 = 0, 02. isMotherOf, Bob)) ali definira tip. V implementaciji smo za predsta- Na začetku smo modele gradili na celotnem naboru izračuna- vitev trojic uporabili jezik RDF, ki je podoben jeziku OWL, vendar nih atributov. Ker sistem AGE+, domnevno zaradi prevelikega šte- ni logični jezik. Uporabili smo ontologijo COSMO (angl. Common vila atributov (106), ni dosegal boljših rezultatov od sistema AGE, Semantic Model 12 ). Predstavljena je v semantičnem jeziku OWL smo preizkusili nekaj metod za izbiranje atributov. Glavni metodi (Web Ontology Language), ki omogoča gradnjo kompleksnih shem naše analize sta bili vnaprejšnje izbiranje atributov (angl. forward različnih konceptov, dejstev in medsebojnih relacij. V primeru, attribute selection) in izločanje atributov (angl. backward feature da bi hoteli ontologiji dodati dodatna specifična znanja, to lahko elimination). Obe metodi sta izboljšali rezultat. Uporabili smo jih storimo. V našem primeru je poleg nekaterih esejev tudi izvorno skupaj z 10-prečnim preverjanjem. Na vsaki iteraciji prečnega besedilo, na podlagi katerega so bili eseji spisani. Izvorno besedilo preverjanja smo dodali/odstranili posamezne atribute in glede dodamo v ontologijo pred eseji in po enakem postopku kot eseje na povprečje preko vseh iteracij dodali/odstranili atribut z najve- in je razložen spodaj. čjim/najmanjšim prispevkom. To smo ponavljali, dokler ni bilo 13 https://github.com/dair-iitd/OpenIE-standalone 12 14 https://www.w3.org/OWL/ https://www.kaggle.com/c/asap- aes 90 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Simončič in Bosnić Tabela 1: Primerjava rezultatov brez izbiranja atributov ocenjevanje modelov (kvadratno utežene kape). Sumimo, da so naše implementacije sistemov AGE in AGE+ (TF-IDF), pri- za učenje svojega modela uporabili vse podatkovne zbirke skupaj, merjava s sistemom Zupanc (AGE) in strnjeni rezultati iz- saj je njihov rezultat v območju skoraj 100% natančnosti (0,96), z biranja ter izločanja atributov na sistemu AGE+ dvakrat večjo absolutno napako (RMSE), kot naš model, ki ima rezultat približno 0,77. Z uporabo vseh zbirk na našem sistemu Brez izbiranja Izbiranje Izločanje tudi dobimo tako visok rezultat (0,97 in 0,94, odvisno od modela). AGE AGE+ Zupanc (AGE) AGE+ AGE+ DS1 0,8358 0,8343 0,8447 0,8369 0,8439 4 ZAKLJUČEK DS2a 0,7001 0,7073 0,7389 0,7158 0,7324 V sklopu tega dela smo implementirali sistem za ocenjevanje DS2b 0,6789 0,6676 0,5386 0,6941 0,7028 esejev po zgledu dela Zupanc [5] v programskem okolju Orange. DS3 0,6578 0,6622 0,6591 0,6656 0,6958 Implementacija v okolju Orange omogoča enostavno uporabo DS4 0,7536 0,7547 0,7174 0,7619 0,7769 sistema in združljivost z že implementirami funkcionalnostmi DS5 0,7964 0,7955 0,7949 0,8028 0,8122 Orange-a. Sistemu smo dodali nekaj novih atributov in možnost DS6 0,7734 0,7675 0,7636 0,7771 0,7871 predstavitve besed z vektorskimi vložitvami GloVe. Naša imple- DS7 0,8071 0,8034 0,7888 0,8083 0,8183 15 mentacija sistema je na voljo na repozitoriju git. Sistem temelji DS8 0,7479 0,7428 0,7738 0,7681 0,7717 na ekstrakciji velikega števila atributov iz besedil in nato izboru AVG 0,7501 0,7484 0,7356 0,759 0,7712 najboljšega nabora za določeno podatkovno zbirko. Inovativni del preteklega dela, ki je vključen tudi v naši implementaciji, je dodaten sistem za preverjanje semantične skladnosti, s pomočjo več izboljšanja. Pri analizi smo opazili, da je nabor atributov, ki katerega nabor atributov dodatno obogatimo, obenem pa imamo pride v končni izbor, relativno majhen. Ugotovili smo, da je zaradi možnost, da nam sistem izpiše vse zaznane semantične napake prečnega preverjanja velika možnost, da s trenutnim naborom oz. neskladja. Prispevek tega članka predstavlja tudi primerjava atributov pridemo v lokalni optimum. Zaradi povprečenja čez tehnik izbiranja atributov in primerjava rezultatov s preteklim vse iteracije lahko nek atribut v prvi iteraciji izboljša rezultat, v delom. Sistem bi bilo smiselno preizkusiti tudi z drugimi napove- drugi pa poslabša, in je v povprečju označen kot neprimeren. Za dnimi modeli, saj smo se v našem delu najbolj osredotočili le na izogibanje tem lokalnim optimumom smo implementirali mejo, linearno regresijo in naključne gozdove. Zanimiv izziv bi bil tudi kolikokrat se lahko v povprečju rezultat poslabša, preden nabor prilagoditev sistema za slovenski jezik, ker je jezik sintaktično atributov označimo kot končen. S tem smo kratkoročno poslab- kompleksnejši, orodja za obdelavo besedil pa še niso tako zrela šali rezultat, vendar dolgoročno ustvarili kombinacijo atributov, kot za angleški jezik. ki dajejo v povprečju boljši rezultat. S to metodo izogibanja opti- mumov smo še dodatno izboljšali končne rezultate, ki so strnjeno ZAHVALA prikazani v Tabeli 1. Pri izbiranju in izločanju atributov je AGE Zahvaljujemo se sodelavcem Laboratorija za bioinformatiko na izpuščen, saj AGE+ v obeh primerih dosega boljše rezultate. Ker Fakulteti za računalništvo in informatiko za podporo in nasvete testni podatki niso več na voljo, smo naše rezultate s sistemom Zu- pri implementaciji sistema v programskem okolju Orange. panc lahko primerjali le s primerjavo sistemov AGE z 10-kratnim prečnim preverjanjem. Vidimo, da dosegamo zelo podobne rezul- LITERATURA tate, kot sistem Zupanc oz. jih nekoliko presegamo. Z ustreznim [1] Dimitrios Alikaniotis, Helen Yannakoudakis in Marek Rei. izbiranjem atributov pa naš rezultat še dodatno izboljšamo. 2016. Automatic text scoring using neural networks. Pro- Sistem SAGE smo iz tabele izpustili, saj so rezultati z izloča- ceedings of the 54th Annual Meeting of the Association for njem atributom le malenkost boljši od sistema AGE+, prav tako Computational Linguistics (Volume 1: Long Papers). doi: 10. pa smo ga uporabili le na podatkovnih zbirkah, ki so vsebovale 18653/v1/p16- 1068. http://dx.doi.org/10.18653/v1/P16- 1068. izvorno besedilo (samo štiri zbirke). Kljub temu pa sistem SAGE [2] Luciano Del Corro in Rainer Gemulla. 2013. ClausIE: Clause- ob zaznanem semantičnem neskladju nudi izpis povratne infor- Based Open Information Extraction. V Proceedings of the macije. Primer v nadaljevanju prikazuje delovanje razreševalnika 22nd international conference on World Wide Web, 355–366. koreferenc in odkrivanje semantičnih napak. Zaradi korenjenja [3] Matej Martinc, Senja Pollak in Marko Robnik-Šikonja. 2019. so nekatere besede v razlagi lahko odsekane. Vhod “George likes Supervised and unsupervised neural approaches to text basketball and doesn’t like sports.”, sproži napako z razlago: “Re- readability. arXiv preprint arXiv:1907.11779. lation ’George likes basketball and George doesn’t like sports.’ is [4] Kaveh Taghipour in Hwee Tou Ng. 2016. A neural approach inconsistent with a relation in ontology: ’George likes basketball to automated essay scoring. V Proceedings of the 2016 Confe- and George doesn’t like sports.’” in podrobno razlago: “Relation rence on Empirical Methods in Natural Language Processing. not consistent: Georg likes Basketball. Relations doesNotLike Association for Computational Linguistics, Austin, Texas, and likes are opposite/disjoint. Relation not consistent: Georg (november 2016), 1882–1891. doi: 10.18653/v1/D16- 1193. doesNotLike Basketball.”. Osnovna razlaga deluje na ravni po- https://www.aclweb.org/anthology/D16- 1193. vedi in nam v tem primeru pove, da je poved v nasprotju sama s [5] Kaja Zupanc. 2018. Semantics-based automated essay eva- sabo. Podrobna razlaga pravi, da George ima in nima rad košarke. luation. Doktorska disertacija. Fakulteta za računalništvo Beseda “sports” se v podrobni razlagi ne pojavi, ker je košarka in informatiko, Univerza v Ljubljani. podrazred športa in tam najprej pride do nasprotja. [6] Kaja Zupanc in Zoran Bosnić. 2017. Automated essay eva- Omenili bi še primerjavo našega sistema z omenjenimi ne- luation with semantic analysis. Knowledge-Based Systems, vronski modeli. Model Taghipour in Tou Ng [4] dosega podobne 120, 118–132. rezultate, kot naš sistem (nekaj pod 0,77). Alikaniotis in sod. [1] opisujejo, da njihov model dosega rezultat 0,96, vendar sumimo na nekaj nepravilnosti, ki izvirajo iz napačne uporabe mere za 15 https://github.com/venom1270/essay-grading 91 Mental State Estimation of People with PIMD using Physiological Signals Gašper Slapničar Erik Dovgan gasper.slapnicar@ijs.si erik.dovgan@ijs.si Jožef Stefan Institute, Jožef Stefan IPS Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Jakob Valič Mitja Luštrek jakob.valic@ijs.si mitja.lustrek@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT their surroundings through technology. One part of the system People with profound intellectual and multiple disabilities are a considers the patterns in a person’s gestures and facial expres- very diverse and vulnerable group of people. Their disabilities are sions, which might have some significance and correlation to cognitive, motor and sensory, and they are also incapable of sym- their behavioural and mental state, or their communication at- bolic communication, making them heavily reliant on caregivers. tempt. The initial solution dealing with this part was already We investigated the connection between physiological signals described by Cigale et al. [1, 2]. In this paper, we instead focus on and inner states as well as communication attempts of people exploring the relationship between the physiological response with PIMD, using signal processing and machine learning tech- of the body and the mental state of the people with PIMD by niques. The inner states were annotated by expert caregivers, and using features computed from photoplethysmogram (PPG). PPG several heart rate variability features were computed from photo- is a periodic signal, where each cycle corresponds to a single plethysmogram. We then fed the features into hyper-parameter- heart beat. We obtained the PPG in two different ways: 1.) by tuned classification models. We achieved the highest accuracy using a high-quality wearable Empatica E4 with an optical sensor of 62% and F1-score of 0.59 for inner state (pleasure, displeasure, measuring the reflection of light from the skin and 2.) by using a neutral) classification using Extreme Gradient Boosting, which contact-free RGB camera mounted on a wall, which records the notably surpassed the baseline. color changes of the skin pixels. The features were then used to train classification models, which predicted the person’s inner KEYWORDS state or communication attempt. The rest of this paper is structured as follows: we first inves- PIMD, mental state, physiological signals, classification tigate the related work in Section 2, then we describe the data collected and used in the experiments in Section 3. We continue 1 INTRODUCTION with the methodology and experimental setup description in People with profound intellectual and multiple disabilities (PIMD) Section 4, and conclude with results and discussion in Section 5. often face extreme difficulties in their day-to-day life due to severe cognitive, motor and sensory disabilities. They require a nearly everpresent caregiver to help them with most tasks. 2 RELATED WORK Additionally, they are unable to communicate their feelings or The connection between physiological parameters and mental express their current mental state in a traditional symbolic way. states is a mature and highly-researched field when it comes to This causes a gap between a caregiver and the care recipient, average healthy people. as it can take an extended period of time for the caregiver to Schachter et al. [6] investigated the emotional state of people recognize any potential patterns and their relationship with the as a function of cognitive, social and physiological state. Several mental state of the care recipient. propositions were made and experimentally confirmed, support- The aforementioned reasons call for a technological solution ing the overall connection between emotional and physiological that might help bridge the gap between the caregiver and the care state. recipient and help the former better understand the latter. The Cigale et al. [1, 2] explored the communication signals of peo- INSENSION project [8] aims to develop such assistive technol- ple with PIMD, which are atypical and idiosyncratic. They high- ogy, which takes into account many aspects of the care recipient. lighted the challenging interpretation of these signals and their The aim is to both bridge the previously mentioned gap as well meaning and suggested how technology could help overcome as empower the people with PIMD to be able to interact with the gap between caregivers and care recipients. Some models were proposed that take the person’s non-verbal signals (NVS) Permission to make digital or hard copies of part or all of this work for personal as input and classify their inner state or communication attempt. or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and Kramer et al. [3] highlighted the challenges of analysing the the full citation on the first page. Copyrights for third-party components of this NVS in people with PIMD, as they are difficult to discern, instead work must be honored. For all other uses, contact the owner/author(s). focusing on physiological body responses. They conducted a Information society ’20, October 5–9, 2020, Ljubljana, Slovenia research in which the expressions of three emotional states of one © 2020 Copyright held by the owner/author(s). person with PIMD were recorded during nine emotion-triggering 92 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Slapničar, et al. situations. They collected heart rate (HR) and skin conductance level (SCL), and investigated the connection between these two physiological signals and the emotional state. They found higher SCL activity during anger or happiness and lower SCL activity during relaxation or neutral state. Vos et al. confirmed that HR and skin temperature allow the same conclusions in people with PIMD and people without dis- abilities, regarding positive and negative emotion. This finding gives additional motivation to our work, showing that the con- nection between physiological and mental state also holds for people with PIMD [9]. 3 DATA We created a recording setup in the INSENSION project, which uses two Logitech C920 cameras capable of recording full HD (1920x1080) resolution video at 30 frames per second (fps). The cameras were setup perpendicular to one another to record from two distinct angles, allowing for decent facial exposure even when the face changes direction. The caregivers were instructed to attempt to conduct their activity in front of one of the cam- eras whenever possible. Additionally, the subjects were given an Empatica E4 wristband, which served both as the ground truth for PPG, as well as a fall-back mechanism for obtaining physio- Figure 1: Example of good (green) and bad (red) video logical signals in cases when camera is unreliable or unavailable. recordings. The wristband records PPG at 64 Hz, allowing for capture of reasonable morphological details. The temporal synchronization between the video and ground truth was ensured to the best of our abilities using suitable protocols and checks. 𝑝𝑟 𝑜𝑡 𝑒𝑠𝑡 With the described setup, we obtained 48 recording sessions,     (2) each lasting between 10 and 30 minutes. Five sessions were elim- 𝐶𝑜𝑚𝑚𝐴𝑡 𝑡 𝑒𝑚𝑝𝑡 = 𝑐𝑜𝑚𝑚𝑒𝑛𝑡  inated immediately, as there was a large mismatch between the  𝑑𝑒𝑚𝑎𝑛𝑑  duration of the video and the duration of the ground truth, which The caregivers were tasked with annotation of videos, looking may happen due to several reasons, such as a caregiver forgetting at camera recordings and marking inner states and communica- to turn on the wristband during a session or the wristband losing tion attempts in time, always marking the start and end of each connection. recognized state, regardless of duration (can be a few seconds or It is important to note that the recordings were made in a a few minutes). Naturally, large periods remained where noth- natural way, as the caregivers were not given any additional ing was annotated, as the experts were either not sure or did restrictions other than to be in front of the camera when possible. not recognize any of the pre-defined states. This does not mean In practice this means that large parts of some recordings might that nothing is happening in those periods, but simply that the be useless due to the person with PIMD being turned away or inner experience of the person with PIMD is unknown. Thus, we the caregiver blocking them. Examples of good and bad sessions added an additional class value for the areas where nothing was are shown in Figure 1. annotated – unknown. 3.1 Annotating the ground truth 4 METHODOLOGY OF MENTAL STATE In order to classify mental states of people with PIMD, we first ESTIMATION required the ground truth annotations. As it is generally difficult Having both the ground truth annotations and physiological to obtain such ground truth, we relied on the expert knowledge data and videos, we then investigated two approaches: 1.) we of partners in the project who specialize in education of people attempted to reconstruct PPG from the camera recordings in a with special needs, alongside the caregivers, who know their contact-free manner and use the reconstructed rPPG (remote care recipients the best. Together they devised an annotation PPG) to calculate features and to classify inner state and commu- schema, in which they annotated inner states and communication nication attempt and 2.) we directly used the Empatica ground attempts of people with PIMD and can take the values given in truth PPG to calculate features to be used in the same classifica- Equations 1 and 2. tion task. 𝑑𝑖𝑠 𝑝𝑙 𝑒𝑎𝑠𝑢𝑟 𝑒 if 1, 2 or 3  4.1 Using rPPG Reconstruction    𝐼 𝑛𝑛𝑒𝑟 𝑆 𝑡 𝑎𝑡 𝑒 = 𝑛𝑒𝑢𝑡 𝑟 𝑎𝑙 if 4, 5 or 6 (1) In order to obtain the remote PPG, we used a rather standard   𝑝𝑙 𝑒𝑎𝑠𝑢𝑟 𝑒 if 7, 8 or 9 pipeline, which was updated with a convolutional neural network  The three numbers within each mental state indicate the inten- in order to further enhance the rPPG. At a high level, the pipeline sity, where a lower number for displeasure means more intense consists of detection or region of interest (ROI), extraction of displeasure, and a higher number for pleasure indicates more red, green and blue signal components (RGB), detrending and intense pleasure. band-pass filtering of RGB, rPPG reconstruction using the Plane 93 Mental State Estimation of People with PIMD using Physiological Signals Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Orthogonal to Skin (POS) algorithm, band-pass rPPG filtering Table 1: List of computed HRV features. (0.5 to 4.0 Hz), and rPPG enhancement via deep learning. Details were already described in our previous work [7] and are not Feature Description subject of this paper. HRmean 60/𝑚𝑒𝑎𝑛(𝑁 𝑁 ) We ran the pipeline described above on 30-second segments HRmedian 60/𝑚𝑒𝑑𝑖𝑎𝑛(𝑁 𝑁 ) of video using a sliding window without overlap. We decided to IBImedian 𝑚𝑒𝑑𝑖𝑎𝑛 (𝑁 𝑁 ) use 30 seconds due to the nature of some frequency features that SDNN 𝑠𝑡 𝑑 (𝑁 𝑁 ) we chose, as frequency analysis makes sense once a reasonable SDSD ′ 𝑠𝑡 𝑑 (𝑎𝑏𝑠 (𝑁 𝑁 )) number of periods are available - in our case this means that a RMSSD ′ 𝑠𝑞𝑟 𝑡 (𝑚𝑒𝑎𝑛 ( (𝑁 𝑁 )2)) sufficient number of heart cycles must be available. Additionally, NN20 and NN50 The number of pairs of successive NNs this length makes sense as we are primarily attempting to predict that differ by more than 20ms and 50ms inner states, which do not change extremely in such a short time pNN20 and pNN50 The proportion of NN20 and NN50 di- span. An example output of the pipeline is shown in Figure 2. vided by total number of NNs SDbonus1 𝑠𝑞𝑟 𝑡 (0.5) ∗ 𝑆 𝐷 𝑁 𝑁 SDbonus2 2 2 𝑠𝑞𝑟 𝑡 (𝑎𝑏𝑠 (2 ∗ 𝑆 𝐷𝑆 𝐷 − 0.5 ∗ 𝑆𝐷𝑆𝐷 )) VLF Area under periodogram in the very low frequencies LF Area under periodogram in the low fre- quencies HF Area under periodogram in the high fre- quencies LFnorm and HFnorm Area under periodogram in the low and high frequencies, normalized by the Figure 2: Example of a good rPPG segment obtained with whole area under periodogram our pipeline. LFdHF 𝐿𝐹 /𝐻 𝐹 We then used the rPPG to compute several heart rate variabil- where 𝑠𝑡𝑑 is standard deviation, ity (HRV) features. These are known to be well-correlated with 𝑎𝑏𝑠 is absolute value, ′ stress, cognitive load, conflict experience and other inner states 𝑋 is the first order derivative, [5, 4]. A detailed list of computed features is given in Table 1. 𝑠𝑞𝑟 𝑡 is the square root and 𝑁 𝑁 are the beat-to-beat intervals. 4.2 Using Empatica PPG The Empatica records PPG directly on the skin, thus making label it actually belongs to, so we decided to exclude it from the raw PPG readily available, without the need for additional evaluation. This left us with 272 instances for class inner state reconstruction. Still, due to subject arm and wrist movements, we and 80 instances for class communication attempt, which was opted to use similar preprocessing steps used previously, namely annotated more sparsely. The final distributions for each class detrending and band-pass filtering, as the signal can sometimes are shown in Figure 3. be quite noisy. We computed the same set of features and window length as before (see Table 1), and used them in the same classification task, attempting to recognize inner states and communication attempts. 5 EXPERIMENTS AND RESULTS Once both the input (HRV features) and output (annotations) were known, we investigated six classification algorithms (k Nearest Neighbours, Decision Trees, Random Forest, Support Vector Machines, AdaBoost and Extreme Gradient Boosting) for Figure 3: Distributions of both classes. this task, always training separate models for inner state and communication attempt. We always compared each algorithm Initially we conducted a 5-fold cross validation (CV) to inves- against a baseline majority vote classifier using two metrics, tigate the best hyper-parameters using a grid search. Once the accuracy and F1-score. hyper-parameters were determined, we ran a separate experi- ment, using the best overall hyper-parameters for each model. 5.1 Using Empatica PPG Again, we ran a 5-fold CV with the best hyper-parameter set- We started our evaluation using the Empatica data, as it is more tings obtained on the full data to validate the performance. All reliable, since the PPG reconstruction is not needed. At the time the investigated algorithms (from the Scikit-learn and XGBoost of evaluation, we had annotations for 15 recording sessions in packages) and their corresponding sets of optimized parameters which 2 different people with PIMD are present. Using the chosen with the best values are available from the authors, but are not 30-second window, we initially had 417 segments of Empatica listed here due to space restrictions. Results of our evaluation PPG available. The unknown class label heavily skewed the data in terms of accuracy and F1-score for both classes are given in for both classes, and there is no way to know which (other) class Table 2. 94 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Slapničar, et al. Table 2: Accuracy and F1 score for both classes. 0.59 for inner state, and accuracy of 48% and F1 score of 0.45 for communication attempt, notably surpassing the baseline majority Algorithm classifier. 𝐴𝐶𝐶 𝐹 1 𝑚𝑒𝑛𝑡 𝑎𝑙 𝑠𝑡 𝑎𝑡 𝑒 𝑚𝑒𝑛𝑡 𝑎𝑙 𝑠𝑡 𝑎𝑡 𝑒 Limitations of our work lie in low number of instances for Baseline (majority) 0.52 0.36 communication attempt and little variety in subjects, having just kNN 0.55 0.55 two for which annotations were available. Additionally, the eval- Tree 0.54 0.56 uation using the rPPG is limited, as we had very few instances for RF 0.57 0.56 which both high-quality segments of video and annotations were SVM 0.55 0.52 available. Thus, the focus of future work should be on gathering AdaBoost 0.59 0.56 more data and conducting a more extensive evaluation of the XGB 0.62 0.59 methods, which is planned in the trial stage of the INSENSION Algorithm 𝐴𝐶𝐶 𝐹 1 project. 𝑐𝑜𝑚𝑚𝑎𝑡 𝑡 𝑒𝑚𝑝𝑡 𝑐𝑜𝑚𝑚𝑎𝑡 𝑡 𝑒𝑚𝑝𝑡 Baseline (majority) 0.45 0.27 ACKNOWLEDGMENTS kNN 0.42 0.42 Tree 0.41 0.39 This work is part of the INSENSION project that has received RF 0.46 0.43 funding from the European Union’s Horizon 2020 research and SVM 0.43 0.34 innovation programme under grant agreement No. 780819. The AdaBoost 0.43 0.41 authors also acknowledge the financial support from the Slove- XGB 0.48 0.45 nian Research Agency (ARRS). REFERENCES 5.2 Using rPPG reconstruction [1] Matej Cigale and Mitja Luštrek. 2019. 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Expression of emo- the models previously trained on the Empatica data, to classify tions of people with profound intellectual and multiple these instances obtained via the rPPG. We achieved reasonably disabilities. A single-case design including physiological high accuracy of 75% and F1-score of 0.84 for inner state and low data. Psychoeducational Assessment, Intervention and Reha- accuracy of 33% and F1-score of 0.33 for communication attempt. bilitation, 2, 1, 15–29. Confusion matrices are shown in Figure 4. [4] Richard D Lane, Kateri McRae, Eric M Reiman, Kewei Chen, Geoffrey L Ahern, and Julian F Thayer. 2009. Neural corre- lates of heart rate variability during emotion. Neuroimage, 44, 1, 213–222. [5] Junoš Lukan, Martin Gjoreski, Heidi Mauersberger, Anneka- trin Hoppe, Ursula Hess, and Mitja Luštrek. 2018. Analysing physiology of interpersonal conflicts using a wrist device. In European Conference on Ambient Intelligence. Springer, 162–167. [6] Stanley Schachter. 1964. 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The tell-tale: what We conducted an initial investigation of the connection between do heart rate; skin temperature and skin conductance reveal physiological signals and mental states of people with PIMD, about emotions of people with severe and profound intel- attempting to classify their inner states and communication at- lectual disabilities? Research in developmental disabilities, tempts. We used HRV features computed from the PPG obtained 33, 4, 1117–1127. with an Empatica E4 wristband and investigated the performance of such models on instances obtained via rPPG. XGB has shown the best performance, achieving accuracy of 62% and F1 score of 95 Energy-Efficient Eating Detection Using a Wristband Simon Stankoski Mitja Luštrek Department of Intelligent Systems Department of Intelligent Systems Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan International Jožef Stefan International Postgraduate School Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia simon.stankoski@ijs.si mitja.lustrek@ijs.si ABSTRACT Another group of people that require monitoring of their eating behavior are people with mild cognitive impairment and Understanding people’s dietary habits plays a crucial role in dementia. They often forget whether they have already eaten interventions that promote a healthy lifestyle. For this purpose, and, as a result, eat lunch or dinner multiple times a day or not a multitude of studies explored automatic eating detection with at all. It might cause additional health problems. Proper various sensors. Despite progress over the years, most proposed treatment of these issues requires an objective estimation of the approaches are not suitable for implementation on embedded time the meal takes place, the duration of the meal, and what devices. The purpose of this paper is to describe a method that the individual eats. uses a wristband configuration of sensors to continuously track Wristband devices and smartwatches are increasingly wrist motion throughout the day and detect periods of eating popular, mainly because people are accustomed to wearing automatically. The proposed method uses an energy-efficient watches, which makes the wrist placement one of the least approach for activation of a machine learning model, based on a intrusive body placements to wear a device. Additionally, the specific trigger. The method was evaluated on data recorded cost of these devices is relatively low, which makes them easily from 10 subjects during free-living. The results showed a accessible to everyone. However, these devices offer limited precision of 0.84 and a recall of 0.75. Additionally, our analysis computing power and battery life, which makes the shows that by using the trigger, the usage of the machine implementation of a smart feature as eating detection on such a learning model can be reduced by 80%. device a challenging task. This paper describes a method for real-time eating detection KEYWORDS using a wristband. The proposed method detects periods and Eating detection, wristband, energy efficient, activity duration of eating. The output from the method can be used to recognition track frequency of eating and could serve to start methods for counting food intakes. The work done in this study is important for the following 1 INTRODUCTION reasons. We developed a trigger that can reduce the usage of the Understanding people’s dietary habits plays a crucial role in machine learning procedure, meaning that our method will not interventions that promote a healthy lifestyle. Obesity, which is greatly affect the battery life of the device. Additionally, we a consequence of bad nutritional habits and excessive energy evaluated different machine learning algorithms in terms of intake, can be a major cause of cardiovascular diseases, diabetes accuracy and model size. The method was evaluated on data or hypertension. Latest statistics indicate that obesity recorded in real-life from 10 subjects. prevalence has increased substantially over the last three decades [1]. More than 600 million adults (13% of the total adult population) were classified as obese in 2014 [2]. In 2 RELATED WORK addition, the prevalence of obesity is estimated to be 23% in the Recent advancements in wearable sensing technology (e.g., European Region by 2025. Also, in 2017, it was reported that commercial inertial sensors, fitness bands, and smartwatches) poor diet has contributed to 11 million deaths worldwide. have allowed researchers and practitioners to utilize different Monitoring eating habits of overweight people is an essential types of wearable sensors to assess dietary intake and eating step towards improving nutritional habits and weight behavior in both laboratory and free-living conditions. A management. multitude of studies for the detection of eating periods have been proposed in the past decade. Mirtchou et al. [3] explored eating detection using several sensors and combining real-life Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or and laboratory data. Edison et al. [4] proposed a method that distributed for profit or commercial advantage and that copies bear this notice and recognizes intake gestures separately, and later clusters the the full citation on the first page. Copyrights for third-party components of this intake gestures within 60-minute intervals. The method was work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia evaluated on real-life data. Dong et al. [5] proposed a method © 2020 Copyright held by the owner/author(s). for eating detection in real-life situations based on a novel idea 96 that meals tend to be preceded and succeeded by periods of detect eating after a trigger is activated during a meal, then the vigorous wrist motion. Amft et al. [6] presented an accurate constraints of the trigger should be reduced. method for eating and drinking detection using sensors attached The next step is the definition of stopping criteria for the to the wrist and upper arm on both hands. Navarathna et al. [7] machine learning model. The idea here is to stop the machine combined sensor data from a smartwatch and a smartphone, learning procedure after a specific number of windows if there which resulted in improved eating detection accuracy compared is no eating detected. Each time our trigger is activated, the to only using smartwatch data. Kyritsis et al. [8] proposed a machine learning procedure is turned on for the next three deep learning based method that recognizes bite segments, buffers of data. The machine learning procedure is stopped if which are used for construction of eating periods. there is no positive prediction in any of the three windows. The work presented in this paper is an extension of our However, if there is at least one positive prediction, the previous work [9], and the main novelty is an energy efficient machine learning procedure continues to work for another three approach for real-time eating detection. new buffers. Also, the number of windows for which the machine learning procedure is active was experimentally obtained. 3 METHOD The proposed eating detection method consists of two parts, 3.2 Machine-Learning Procedure namely: a threshold-based trigger, used for activation of an А detailed description of the used method can be seen in [9]. eating detection machine learning procedure, and a machine- The method is based on machine learning and consists of the learning method that predicts whether eating took place. following steps: filtering the accelerometer and gyroscope data coming from the wristband, segmentation of the filtered data, 3.1 Energy-Efficient Trigger feature extraction, feature selection, two stages of model The recent advancements in the technological development and training and predictions smoothing. accessibility of wearable devices bring new opportunities in the In the first step, the raw data were filtered with a 5th order field of human activity recognition (HAR). However, the median filter to reduce noise. Furthermore, the median filtered limited battery life and computational resources remain a data was additionally filtered with low-pass and band-pass challenge for real-life implementation of advanced HAR filters. Hence, we ended up with three different streams of data, applications. Using a machine learning based model for eating median, low-pass and band-pass filtered data. detection that is working all the time results in a rapid battery The accelerometer and gyroscope data were segmented drain. Therefore, we designed a threshold-based trigger that using a sliding window of 15 seconds with a 3-second overlap activates the machine learning model only when specific between consecutive windows. This means that once we have criteria are met. The main concept behind the trigger is to only 15 seconds of data, the buffer is adjusted to only store 3 select moments when the human is making a movement with seconds of new data. After that, each time the buffer is full, we his hand towards the head. add the new 3 seconds of data to the previous 15 seconds For this purpose, we used data from an accelerometer. This window and we drop the oldest 3 seconds from it. The reason sensor provides information about the wristband’s orientation for the length of the window is that it needs to contain an entire from which we can see whether the hand is oriented towards the food intake gesture [10]. head. The recent accelerometers that are used in battery-limited After the segmentation step, we extracted three different devices can store acceleration values in their internal memory groups of features. Also, we included a feature selection step to without interacting with the main chip of the microcontroller. improve the computational efficiency of the method, to remove The first step of trigger implementation is to define the the features that did not contribute to the accuracy and to reduce buffer size in the sensor’s internal memory and the sensor’s the odds of overfitting. sampling frequency. Based on these two parameters, we enable The training procedure for the method used in this study the accelerometer to collect data for a specific time without consists of three stages. The first two aim at training an eating- interacting with the main chip of the microcontroller. This detection models on an appropriate amount of representative means that the main chip of the microcontroller could be in eating and non-eating data. The third step smooths the sleep mode for the predefined period. When the accelerometer’s predictions of the model. buffer is full, the accelerometer interrupts the main chip and transfers the stored acceleration data to it. We use the accelerometer’s y-axis and z-axis to detect moments when the 4 DATASET AND EXPERIMENTAL SETUP individual is moving the hand towards the face. Namely, we For this study, we recorded data from 10 subjects (8 male and 2 calculate the mean value for both axes, and if both of the values female), ranging in age from 20 to 41 years. The data were are above a predefined threshold value, the machine learning recorded using a commercial smartwatch Mobvoi TicWatch S procedure for eating detection is activated. We used two axes running WearOS, providing 3–axis accelerometer and 3–axis for the trigger to reduce the possible situations in which our gyroscope data sampled at 100 Hz. The technical description of trigger is falsely activated. However, one can work only with the sensors from the smartwatch shows that the recorded data is one axis, which will result in more activated triggers. We could compatible with our target wristband for which we are say that having more activated triggers is not desirable. developing our eating detection method. Additionally, the use However, if the eating detection method is not good enough to of a commercially available smartwatch was an easier option for recording data. The collected dataset contains recordings 97 from usual daily activities performed by the subjects, including Table 2: Results of eating detection procedure achieved with eating. The subjects were wearing the smartwatch on their different algorithms and their model size. dominant hand while recording. The smartwatch had an application installed on it, which enabled them to label the Algorithm Precision Recall F1 score Model size beginning and the end of each meal. There were no limitations Random Forest 0.84 0.75 0.79 36339 KB about the type of meals the subjects could have while recording, Logistic Regression 0.70 0.71 0.70 1.25 KB which resulted in having 70 different meals included in the dataset. Furthermore, the subjects were also asked to act LinearSVC 0.69 0.71 0.70 1.8 KB naturally while having their meals, meaning talking, Decision Tree 0.59 0.65 0.62 175 KB gesticulating, using the smartphone, etc. The total data duration is 161 hours and 18 minutes, out of which 8 hours and 19 The used combinations for the window and slide size are shown minutes correspond to eating activities. in the first column of the table. The second column shows the For evaluation, the LOSO cross-validation technique was average time needed for the trigger to be activated for the first used. In other words, the models were trained on the whole time after a meal is started. The third column shows the average dataset except for one subject on which we later tested the percentage of triggered windows during a meal. These two performance. The same procedure was repeated for each subject columns were used as a metric for selecting the optimal size of in the dataset. The results obtained using this evaluation a window and slide between the windows. The last column technique are more reliable compared to approaches where the shows the number of meals when the trigger was activated. The same subject’s data is used for both training and testing, which values for the second and third columns were obtained only show excessively optimistic results. from the meals for which the trigger was activated. Row-wise As mentioned before, smartwatches offer limited resources, comparison between these two columns shows the results one of which is the size of the RAM memory. Therefore, we obtained with each different combination of a window and analyzed models with different sizes to see whether the bigger slide. We can see that the most optimal combination regarding and more complex models provide higher accuracy. We tested the average time needed for a trigger to be activated after a the performance of four different machine learning algorithms, meal is started is a window size of 3 seconds with a slide of 1 Random Forest [11], Decision Tree [12], Logistic Regression second between two windows. Therefore, in our further [13] and LinearSVC [14]. analysis, we used this combination. The optimal window size of We analyzed the following evaluation metrics: recall, 3 seconds is expected if we have in mind that the usual intake precision and F1 score. These evaluation metrics are the most gesture lasts around 2 seconds. Longer windows fail to detect commonly used metrics for classification tasks like ours and the gesture while having a meal because usually we have two or give a realistic estimate of the efficacy of the algorithm. Also, three intakes in 15 seconds and the mean value over the whole the final results were obtained from the whole recordings by window is low. each subject. The reason for this is mainly to give a real picture Table 2 shows the final results obtained using the whole of how good the developed method is in real-life settings. method described in Section 2. Row-wise comparison between the used evaluation metrics shows the results obtained using the different algorithms shown in the first column. Additionally, the 5 RESULTS last column of the table represents the final model size. We can The primary use of the trigger is to reduce the activity of the clearly see that the results achieved with Random Forest are machine learning procedure. However, for the efficiency of the better than the remaining algorithms. However, if we compare trigger, a very important requirement is when and how often the the model size of the best performing algorithm with the trigger is activated during a meal. In order to achieve accurate remaining algorithms we can say that the results achieved using predictions, we want the trigger to be activated as soon as the Logistic Regression and LinearSVC are acceptable. meal is started. Additionally, the percentage of activated Additionally, the precision value of 0.84 shows that the triggers during a meal should be bigger compared to noneating combination of trigger and machine learning procedure can segments. For this purpose, we explored which window size differentiate between eating and noneating segments. However, works best with our trigger. Table 1 shows the results achieved the recall value of 0.75 suggests that a more accurate method in the conducted experiments. We tested two different window regarding the eating periods is needed. sizes with two slide values for each window, resulting in a total We also analyzed how much time each of the previously of four combinations. described algorithms was active during the noneating period. The results from this experiment are shown in Table 3. Additionally, in this table we can see the false positive rate Table 1: Different window size for the trigger procedure. during the noneating period. The best results are achieved using a Random Forest classifier, which is active only 20% of the Window and Trigger % of activated Meals whole noneating period. This means that our trigger-based slide size activation time triggers detected procedure reduces the usage of the machine-learning procedure 3 - 1 36 s 34.2 68/70 for 80%. However, this number also depends on the detection 3 - 3 41 s 32.6 68/70 method because once it is activated, the eating predictions 15 - 3 48 s 42.0 55/70 extend the active time of the method. 15 - 5 41 s 42.0 54/70 98 Table 3: Comparison of active time and false positive rate of to activate the trigger during eating periods more easily. the machine learning algorithms during noneating period. Additionally, this could reduce the activation of the machine- learning procedure during non-eating periods. Also, we plan to Active time during explore memory efficient methods for storing the models in Algorithm False positive rate noneating period memory. Random Forest 20% 1.36% ACKNOWLEDGMENTS Logistic Regression 22% 2.18% This work was supported by the WellCo and CoachMyLife LinearSVC 22% 2.34% projects. The WellCo project has received funding from the Decision Tree 23% 3.93% European Union’s Horizon 2020 research and innovation programme under grant agreement No 769765. The CoachMyLife project has received funding from the the AAL programme (AAL-2018-5-120-CP) and the Ministry of Public 6 CONCLUSION AND FUTURE WORK Administration of Slovenia. In this paper, we presented a method that can accurately detect eating moments using a 3-axis accelerometer and gyroscope REFERENCES sensor data. Our method consists of an energy-efficient trigger [1] World Health Organization. World Health Statistics 2015. Luxembourg, WHO, 2015 and a machine-learning procedure, which is started only after [2] Public Health England. Data Factsheet: Adult Obesity International the trigger is activated. We evaluated this method using a Comparisons. London, 2016. dataset of 70 meals from 10 subjects. The results from the http://webarchive.nationalarchives.gov.uk/20170110165728/http://www. noo.org.uk/NOO_pub/Key_data LOSO evaluation showed that we are able to recognize eating [3] M. Mirtchouk, D. Lustig, A. Smith, I. Ching, M. 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ACM transactions on intelligent systems and We believe that personalized values for the threshold will help technology (TIST) 2.3 (2011): 1-27. 99 Comparison of Methods for Topical Clustering of Online Multi-speaker Discourses Vid Stropnik Zoran Bosnić Evgeny Osipov University of Ljubljana, University of Ljubljana, Luleå University of Technology, Faculty of Computer and Faculty of Computer and Department of Computer Science, Information Science, Information Science, Electrical and Space Engineering, Velenje, Slovenia Ljubljana, Slovenia Luleå, Sweden vs6309@student.uni-lj.si zoran.bosnic@fri.uni-lj.si evgeny.osipov@ltu.se ABSTRACT speakers. Consequently, traditional summarization methods do not translate well to these sorts of text bodies. Discussions held on online forums differ from traditional text In Section 2 of this paper, the related work establishes the documents in several ways. In addition to individual text-bodies general framework that other authors generally use for the task (submission comments, forum posts etc.) being very short, they at hand. It establishes the Latent Dirichlet Allocation (LDA) also have multiple messengers, each of whom may exhibit topic modeling algorithm as the current leading method for unique patterns of speech. Consequently, state of the art methods topical grouping of individual comments. These topical groups for text summarization are often rendered inapplicable for these play a pivotal role in later summarization steps, also presented in sorts of corpora. This paper evaluates the topic-clustering Section 2. algorithm used in the state-of-the-art online comment clustering In this paper, we externally evaluate and compare LDA techniques, as parts of commonly used summarizer models. It versus two frameworks, using word representations in semantic proposes two alternative, vector-based approaches and presents vector space. We describe the analyzed methods in Sections 3 results of a comparative external analysis, concluding in the three and 4. In Section 5, we describe the comparative evaluation methods being comparable. methodology used to determine the applicability of each modeling technique and present our results. We follow it up by KEYWORDS discussing further work in the conclusion of this paper. latent Dirichlet allocation, word embeddings, GloVe, hyperdimensional computing, self-organized maps, topical clustering, clustering evaluation, discussion summarization 2 RELATED WORK Online discussion summarization is a field that has not been addressed directly by many authors. One group of works [5-7] have roughly described a three-step process, commonly 1 INTRODUCTION presented as the state of the art. The approaches includes a topical User generated comments carry a great amount of useful clustering of all the observed comments, establishing a ranking information. Big data researchers have successfully used them to method for determining the most salient ones in each cluster, and predict stock market volatility [1] and predict the characteristics later summarizing this selection. Between them, the authors of such comments that perform the best on a given online confidently establish Latent Dirichlet Allocation (LDA) topic platform [2]. User comments can also offer vast amounts of modeling as the most human like grouping algorithm. Further complementary information, as well as being forms of work also proposes a novel graph-based linear regression model information surveillance, entertainment or social utility [3]. based on the Markov Cluster Algorithm (MCL), [8] which Existing mechanisms for displaying comments on websites do outperforms LDA, but uses the knowledge of multidomain not scale well and often lead to cyberpolarization [4]. knowledge bases for implementation. While we argue that Furthermore, they are platform-specific and often fail to offer an extractive summarization is not an ideal method for the analysis overall image of the topics discussed in a given comments of multi-speaker corpora, the first step of identifying and section. topically clustering individual comments in each comment A comprehensive, easily understandable automatic summary section is assumed as a required step towards successful of the online discourse at hand can be instinctively understood as summarization of the topics discussed therein. a solution to this problem. This, however, is no easy task, seeing To the best of our knowledge, popular NLP word embedding as these corpora are often very short and come from multiple algorithms (i.e. word2vec, GloVe) have not been used directly for comment summarization applications up until now. Similarly. Permission to make digital or hard copies of part or all of this work for personal or neither have hyperdimensional representations, another topic of classroom use is granted without fee provided that copies are not made or distributed interest. for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 100 3 NLP METHODS 3.2 Word Embeddings In this work, we examine three distinct topical clustering models, Word Embeddings is a collective name for a set of language the output of which is always a set of comment clusters, given a modeling and feature learning techniques, yielding word multi-comment input. representations using vectors, the relative similarities of which The first is an LDA model, using a Term frequency – inverse correlate with the semantic similarity of the represented words. document frequency (TFIDF) word representation as an input. In These meanings are extracted from the contexts – fixed-size this representation, the comments were hard-clustered into the windows of preceding and succeeding words, in which groups, determined by the degree of membership of which had individual words appear in in the training corpus. The generation been the highest in a soft-clustering approach, provided by the of these vectors is achieved by Context counting [11] or Context LDA model. prediction [12]. While there have been several claims of one of The second examined model uses GloVe word embeddings the methods for synthetizing word embeddings being superior clustered with the k-means clustering algorithm, thus portraying over another, recent work implies the correspondence between words in semantic vector space using information of contexts in these model-types [13]. Whichever way these word-vectors are which words often appear. created, they represent semantic meaning in vector space. Using The third model creates Hyperdimensional representations of algebraic similarity measures (in our case, cosine distance) on words, mapped them into a two-dimensional topology using the comment-word averages, the relative likeness of the examined self-organized maps algorithm and then clustered it like the comments’ meanings is calculated. Comment clusters can then preceding model. This approach is the least explored for this use- be created by clustering the semantic-space points into groups case and is inspired by the observed differences between the with high intra-cluster and low inter-cluster similarity. These functionality of the human brain and the traditional von groups represent topical clusters, used in our examination. Neumann architecture for modern computing. We performed the comparative evaluation of the models on 3.3 Hyperdimensional Computing the Reddit Corpus (by subreddit) dataset, provided by the Cornell Hyperdimensional computing is a family of biologically inspired Conversational Analysis Toolkit (Convokit)1. Five Conversations, methods for representing and manipulating concepts and their corresponding to as many treads on the website Reddit were meanings in high-dimensional space. Random Bipolar vectors of extracted from the corpus. We selected threads, discussing topics high, but fixed dimensionality ( ≥ 1000 ) are initialized as from different subject domains, where each contained at least 50 individual word representations and are then transformed in ways non-removed comment text bodies. Two human annotators were that represent semantically similar comments closer in the high- then asked to manually identify topical clusters in the selected dimensional vector space, while the similarity of dissimilar Conversations. The comment texts were provided to them in the comments is likely close to zero due to their inherent form of a set of numbered text files, containing only the text data orthogonality. The methods used to transform these vectors are in chronological order of submission. Reddit post titles or other binding, bundling and permuting [14]. By using these methods, metadata were not available to the annotators and no guidance individual hyperdimensional vectors are created for each was given as to the number of topics required. The clusterings comment, encoding the used words and their position in the were examined as-is, with no singleton removal performed. comment in the vector. We describe the NLP techniques used to create the three Similar to the clustering of word embeddings, semantically clustering models in the following subsections, with external similar comment groups can be found by clustering, thus evaluation results being presented in Section 5. determining the outputs of the third model. However, the performance of this method did not yield comparative results at first. We hypothesised that this might be due to the high 3.1 Latent Dirichlet Allocation component count of the used vectors (more than double the Latent Dirichlet Allocation (LDA) is a topic modeling technique dimensions of the Word Embedding approach), so a method of initially proposed in the context of population genetics, but later dimensionality reduction was examined, aiming to improve its applied in machine learning in the early 21st century. It assumes results. It is described in the next sub-section. a generative process of documents as random mixtures over a collection of latent topics. Each of these topics, in turn, is 3.4 Self-Organized Maps characterized by a certain distribution over words. A topic model Self-organizing maps (SOM), also known as Kohonen networks can be created by estimating the per document distribution of are computational methods for the visualization and analysis of topics θ and the per topic distribution over words φ. [9] Many high-dimensional data. The output of the algorithm is a set of methods, such as variational inference, Bayesian parameter nodes, arranged in a certain topology that represents the nodes’ estimation [9] and Collapsed Gibbs sampling [10], have been mutual relation, with each node being represented with a weight used to approximate these values. In the end, they all boil down vector of t dimensional components, with t corresponding to the to maximizing the model’s probability of creating the exact uniform dimensionality of data being reduced [15]. As data documents, provided to it in the input, assuming the knowledge representations in high-dimensional vector spaces are inherently of the number of topic distributions. vulnerable to sparseness, clustering outputs can differ in cases where the clustered data is first dimensionally reduced. Thus, we used the SOM algorithm to examine if the results (of the 1 https://convokit.cornell.edu/documentation/index.html/ 101 examination in Section 5) of any of the proposed frameworks can even clearer in Figure 2, which shows each model’s performance be improved by dimensionally reducing the vector with respect to the agreement score between the two human representations prior to clustering. annotators. The percentage is calculated as an averaged sum of SOM proved to drastically improve the performance of the all four metric scores, weighted by the sum of these scores, Hyperdimensional computing model, while making the Word achieved by the human versus human evaluation. In the figure, Embeddings-based model perform worse. Consequently, we Word Embeddings can be seen as the best-performing approach, only use SOM prior to clustering the HD-based approach in the reaching 54.18 % of the Human agreement. The performance of evaluation, presented in Section 5. LDA presented in Figure 2 is also comparable to that found in [5]. However, the difference in results between the best and the 4 IMPLEMENTATION All implementational work was done with the Python programming language. All text corpora were pre-processed using the WordNetLemmatizer and PorterStemmer from NLTK.2 Stop word removal was done in the pre-processing step using the topic modeling package Gensim3, which also provided the submodules for TFIDF and LdaModel, used for the implementation of Latent Dirichlet Allocation. GloVe word embeddings were provided as part of the NLP open-source library SpaCy 4 as part of the “en_core_web_md” pretrained statistical model for the English Language. The SOM algorithm was implemented using the SimpSOM package5, with k-means clustering being provided by Scikit-Learn.6 5 EVALUATION To analyze the applicability of LDA, Word Embeddings and Figure 1: Visualization of agreement metric results between dimensionally reduced Hyperdimensional computing for the the human annotators (top) and the average annotator vs. discussed use-case, topical clustering outputs were created for 5 model agreement (bottom three) Reddit Conversations. Two human annotators also manually created topical groups for these conversations. The goal of our evaluation was to see which model created the most human-like worst performing models being less than 7% of the total human clusters; consequently having the highest average agreement agreement score, this metric is not enough to establish Word measure with the clustering samples, provided by the two Embeddings as superior to LDA or indeed, dimensionally annotators. reduced High-dimensional computing. We can conclude that Topical clusters, created by the three models, were externally both Hyperdimensional computing and Word Embeddings can evaluated using four symmetric agreement measures: The V- produce topical clusters, comparable to the current state of the art Measure [16], The Fowlkes-Mallows Index [17], the Rand Index LDA method. [18] and the Mutual information score [19]. The latter two were Semantic document representations performing as well as the also adjusted for variance. For each examined model, the best state-of-the-art topic modeling framework using LDA opens up performing number of topic clusters was selected. The agreement plentiful possibilities in the field of multi-speaker conversation of the clustering output of each model was measured against both analysis. Whereas topic modeling’s more direct approach of of the manual clusterings, with the per annotator average of each inferring latent conversation topics might be useful in their metric being the final output. discovery, the possibility of applying algebraic functions to Figure 1 shows the result scores of all four metrics for each individual comment vectors might enable further topic mining analyzed method. In the top row, the average agreement between and experimentation. While the k-means clustering algorithm the two annotators is also shown. This is, expectedly, higher than requires a desired number of clusters at input, similar to LDA, its the average agreement between any examined model and the job is not to encode semantics in the Word Embedding or SOM- human outputs. A few takeaways can be addressed, examining HDC framework. This means that an alternative clustering the figure. Firstly, the different methods were successful to a algorithm – one without the need for an input number of medoids varying degree, depending on the used metric, with each - could be used for the task of grouping comments. This, in turn, performing the best according to at least one. 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Structural relations among users’ motives, types of websites, information credibility, 103 Machine Learning of Surrogate Models with an Application to Sentinel 5P Michał Artur Szlupowicz Jure Brence Jennifer Adams m.szlupowicz@gmail.com jure.brence@ijs.si jennifer.adams@esa.it Warsaw University of Technology, Jožef Stefan Institute Φ-lab, ESA/ESRIN Faculty of Physic Ljubljana, Slovenia Frascati, Italy Warsaw, Poland Edward Malina Sašo Džeroski edward.malina.13@alumni.ucl.ac.uk saso.dzeroski@ijs.si Earth and Mission Science Division Jožef Stefan Institute ESA/ESTEC Ljubljana, Slovenia Noordwijk, the Netherlands ABSTRACT the task of prediction, while offering a choice between PCA and autoencoders to reduce dimensionality [4, 6, 3]. In this paper we Surrogate models are efficient approximations of computation- present an extension of the framework with two types of ensem- ally expensive simulations or models. In this paper, we report bles of decision trees for prediction [4], as well as an evaluation improvements of a framework for learning surrogates on input of the performance and utility of three additional algorithms and output spaces with reduced dimensionality. We present non- for dimensionality analysis and dimensionality reduction: t-SNE linear embeddings and feature importance as additional methods [11], UMAP [12] and feature importance based on random forests for dimensional analysis and reduction. The choice of models for [10]. prediction is extended with two types of ensembles of decision trees. The performance of the additions is evaluated and com- pared with the original approaches on a dataset, generated by 2 DATASET RemoTeC, a complex radiative transfer model. The training dataset was generated using the RemoTeC tool and KEYWORDS in total consists of 50000 samples. Each input state vector con- tains a set of atmospheric parameters: solar zenith angle (SZA), spectral data, neural network, ensemble, surrogate model, dimen- albedo, temperature, pressure, aerosols and profiles of the CH4, sionality reduction CO and H20 gases (in total 125 dimensions). The sampling of the data ensures that the data covers the entire range of conditions 1 INTRODUCTION that S5P/TROPOMI is expected to encounter. Exploratory data The TROPOspheric Monitoring Instrument (TROPOMI) is an analysis reveals three dimensions with zero variance. Removing on board satellite instrument on the Copernicus Sentinel-5 Pre- them results in a dataset with a 122-dimensional input space. cursor satellite [9]. Its main objective is to provide accurate ob- The output training data was created using the RemoTeC RTM servations of atmospheric parameters, as the concentrations of in the S5P/TROPOMI Shortwave InfraRed (SWIR3) band. Each atmospheric constituents. Those can be used to obtain better target vector consists of an infrared spectrum with 834 dimen- air quality forecasts and to monitor global trends. However, the sions. retrieval of interesting attributes involves running a retrieval algorithm, such as RemoTeC [2, 8], based on “optimal estimation 3 SURROGATE MODELS methods" that tend to be computationally very expensive [7]. The framework for learning surrogates is capable of learning Machine learning techniques can be used to learn surrogate both forward and backwards models. The former predict spectra, models that approximate the outputs of intensive simulations given atmospheric parameters. The latter reverse this process and are much faster at making predictions [13]. A framework and learn to approximate atmospheric parameters that produce a for learning surrogates of radiative transfer models has been given spectrum, which is useful for optimizing parameters of the developed [1]. Due to the high dimensionality of both input and RemoTeC simulation. Surrogates are generally predictive models output spaces, the framework employs dimensionality reduction that map directly between input and output data of a simula- - methods that find low-dimenensional projections (embeddings) tion or computationally expensive model. They offer much faster of data that preserve as much information as possible [4]. Predic- predictions at the cost incurring a prediction error. However, tive models are learned on input and output spaces with reduced when the data is high dimensional and contains many samples, dimensionality. the computational cost of training and prediction can still be Despite promising results, the existing framework for learning non-trivial. In such cases, methods of dimensionality reduction surrogates is limited to simple feed-forward neural networks for can offer not only time savings, but also improvements in predic- Permission to make digital or hard copies of part or all of this work for personal tive performance. In our framework, we employ dimensionality or classroom use is granted without fee provided that copies are not made or reduction to atmospheric parameters, as well as to the spectral distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this space. Predictive models learn to map between reduced spaces. work must be honored. For all other uses, contact the owner /author(s). An inverse transformation is performed on predictions in the re- Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia duced space to obtain predictions in the original output space. For © 2020 Copyright held by the owner/author(s). that reason, dimensionality reduction algorithms must provide 104 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Michał A. Szlupowicz and Jure Brence, et al. an inverse transformation in order to be useful as a component of regularization techniques can be employed. One of options is of a surrogate model in our framework. adding artificial noise to the input data, which forces the network to generalize. 3.1 Dimensionality Reduction In our framework, we employ this kind of autoencoder, often referred to as a denoising autoencoder, by adding Gaussian noise A high number of dimensions makes a problem much harder for with mean 0 and standard deviation 0.1 to input data during the many machine learning algorithms due to the curse of dimen- training process. A more thorough investigation of the effect of sionality. For this reason, we have tried a range of dimensionality this technique on the predictive power can be found in [1]. For reduction (DR) methods on our data before performing training both atmospheric parameters and the spectral space, we used the on them. DR methods are (potentially unsupervised) algorithms same 7 layers architecture with an appropriate size of input and that try to find a projection of the data to a lower dimension of output layers. The architecture can be summarized as: space that preserve as much information as possible. A lower number of dimensions helps reduce computation time • input layer of size 𝑁 + Gaussian noise 0 and often even improves the predictive performance of models. • dense layer of size 𝑁 and ReLu activation 1 < 𝑁0 Furthermore, DR methods can also be used to visualize high • dense layer of size 𝑁 = 1 and ReLu activation 2 𝑁1 2 dimensional data by finding an informative projection into two • dense embedding layer of size 𝑁 and linear activation 3 dimensions that is understandable to humans. Some algorithms, • dense layer of size 𝑁 and ReLu activation 2 such as t-SNE or UMAP, serve especially this purpose. • dense layer of size 𝑁 and ReLu activation 1 Principal Component Analysis (PCA) is one of the most pop- • output layer of size 𝑁 and linear activation 0 ular dimensionality reduction methods [4]. PCA finds linear pro- The t-Distributed Stochastic Neighbor Embedding (t-SNE) jections to a lower-dimensional subspace so that variance in the [11] is a non-linear unsupervised technique for high dimension data is maximized. Visualizing the ratio of variance, covered by data visualization that can model complex, non-linear dependen- individual principal components is a way of assessing the intrin- cies. t-SNE places points that are similar in the original space close sic dimensionality of the data, as shown in Figure 1. We see that, together in the embedding layer with a high probability, while for the 122-dimensional atmospheric parameter space, we need: placing dissimilar points close together with only a low probabil- • 23 dimensions to explain 95% of the variance, ity. Since t-SNE is a stochastic and non-parametric method there • 45 dimensions to explain 99% of the variance, is no way to perform a reverse transformation from the embed- • 73 dimensions to explain 99.9% of the variance, ding space to the original space. This excludes the method from and for the output 834-dimensional spectral space: use as part of the surrogate modelling process. It can, however, • 1 dimension to explain 95% of the variance, be useful for visualizing the dataset. Another disadvantage of • 2 dimensions to explain 99% of the variance, t-SNE is its high computational complexity. • 9 dimensions to explain 99.9% of the variance. Uniform Manifold Approximation and Projection (UMAP) [12] is another dimension reduction technique used for dataset visualizations, constructed from a theoretical framework based in Riemannian geometry and algebraic topology. UMAP preforms similarly to t-SNE, but preserves more of the global data structure with superior run time performance. As is the case with t-SNE, UMAP does not allow for reverse transformations, which means we can not use it to learn surrogates. However, visualizations using UMAP allowed us to gain useful insights into the structure of our dataset. 3.2 Prediction Models One of the predictors we used in our experiment was a feed- forward neural network (NN). We have chosen an architecture, consisting of 2 hidden full connected layers with ReLu activation functions and linear activation on the output layer [6]. Random Forest (RF) is an ensemble learning technique suited for both regression and classification problems. It uses sample bagging and feature sampling methods to train a set of decision trees. Prediction is performed by averaging over predictions from the individual regression trees. The main advantage of RF over a simple decision tree is the much better generalization. We decided Figure 1: Dependence of the cumulative relative variance to use this kind of predictor, because it is capable of performing on the number of principal components for both the input multi target regression [10]. and the output space. Extra Random Trees (ET) is a technique very similar to random forests, with two main differences. First, it uses the whole dataset Autoencoders (AE) [3] are a type of artificial neural network for training individual trees instead of using bags of samples. used to learn low dimensional representations. AE are trained to Second, it uses random cuts for each split, instead of using the reproduce input data on the output of the network after passing optimal one (in case of Gini or Entropy reduction). It has been through a bottleneck in the network architecture. To prevent shown to perform better than random forests for some problems autoencoders from memorizing the training dataset, a variety [5]. 105 Machine Learning of Surrogate Models with an Application to Sentinel 5P Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia 4 EXPERIMENT two principal components. Only about half of the features are assigned non-negligible importance. The features identified by Our experiment is composed of three parts. In the first two, we this approach warrant further investigation by domain experts. employ methods of dimensionality reduction as a way to gain insight and understanding about our dataset and problem. The third part is an empirical evaluation of different combinations of methods for dimensionality reduction and prediction, aiming to identify the one that offers the best predictive performance on unseen data. 4.1 Visualization We applied the UMAP and t-SNE visualization techniques to both atmospheric parameters and spectrum data. As expected, both methods showed clusters in the atmospheric parameters data. In the spectrum data space, UMAP identified a structure in the data, depicted in figure: 2. A comparison of the data points sampled from different clusters shows a large difference in the scale of individual data points. This is likely one of the reasons why such a high variance is concentrated in the first principal component (as seen in Figure 1). Figure 3: Random forest predictor importance of atmo- spheric data features. 4.3 Regression To compare different regressors and methods of dimensionality reduction, we performed forward and backward predictions us- ing neural network, random forest and extra random trees for both autoencoder and PCA embeddings. We reduced the dimen- sionality of the input space from 123 to 73 and the dimensionality of the output space from 834 to 9. These values correspond to 99.9% explained variance when using PCA. The noise level of the autoencoder was set to 𝜎 = 0.1. A more thorough study of the effects of these parameters can be found in [1]. We compare the predictive power of various combinations of either AE or PCA for dimension reduction, and either neural network, random forest or extra trees as a predictive model, using 10-fold cross valida- (a) UMAP visualization tion. In Table 1 we compare the results, using the coefficient of determination as the evaluation metric [4]: 𝑀 𝑆 𝐸 (model) 2 𝑅 = 1 − . 𝑣 𝑎𝑟 𝑖𝑎𝑛𝑐𝑒 (training set) Table 1: Coefficient of determination for various combina- tions of dimensionality reduction methods (DR) and pre- dictive models (PM), estimated by 10-fold cross validation. forward backward (b) Comparison of data points PM / DR AE PCA AE PCA Figure 2: UMAP visualization of the spectrum data. NN 0.9995 0.9998 0.8454 0.9206 RF 0.8931 0.9937 0.9267 0.9311 ET 0.9228 0.9958 0.9370 0.9510 4.2 Feature Importance 2 The main advantage of using tree-based models over neural net- For the forward model, the best performance of 𝑅 = 0.9998 is works is their interpretability. While the ability to be understood achieved by a neural network, mapping between spaces reduced by a human is lost when moving to an ensemble from a single by PCA. For the backward model, the best performing model 2 tree, random forests can be very useful for estimating the impor- are extra trees, paired with PCA, achieving 𝑅 = 0.9510. Both tance of individual features for prediction. We trained a random represent very satisfactory and promising models to employ as forest predictor on the full dataset and visualized feature impor- surrogates for radiative transfer modeling. From Table 1, we can tance values in Figure 3. We see that 70% of feature importance also see that PCA outperformed autoencoders in all cases, while is accumulated in just two dimensions. This corresponds well also being much faster to compute. The comparison of predic- to the PCA estimate of most variance being encompassed by tive models is not as simple. For the forward model, the neural 106 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Michał A. Szlupowicz and Jure Brence, et al. network is the best, but only by a small margin. For the back- insight about the data. However, feature importance can also be ward model, the differences are larger, with the neural network used to compute feature rankings and perform feature selection, performing the worst. The performance of random forests was which can be considered as another method of dimensionality re- between the performances of the other two predictive models duction. In further work, it might be worthwile to investigate this for both the forward and the backward problem. approach further and include it as an option in the framework Since one of the main uses for surrogate models is speeding for learning surrogates. up computation, time complexity is an important consideration. The main disadvantage of neural networks is the computational 6 ACKNOWLEDGEMENTS complexity required for both training and prediction. An autoen- We thank dr. Jovan Tanevski for his initial work on the project, coder takes about ten times as long to transform a data point as well as his ideas and help in further work. to the embedding space than PCA. For predictive models, the neural network used in this study needed approximately three REFERENCES times as long to make a prediction than random forests and extra [1] Jure Brence, Jovan Tanevski, Jennifer Adams, Edward Ma- trees, which had a similar time complexity. Nonetheless, mak- lina, and Sašo Džeroski. 2020. 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Ljubljana, Slovenia ABSTRACT taking into account underlying dependency structure and pow- In this paper we address the problem of Chest X-ray (CXR) clas- erful deep features, could advance current state-of-the-art of the sification in a multi-label classification (MLC) setting, in which supervised MLC deep-learning based approaches. each sample can be associated with one or several labels. The availability of large-scale CXR datasets has provided the abil- ity to develop highly accurate deep-learning based supervised models, that closely resembles the performance of human radiol- ogists. We compare an end-to-end deep-learning based approach with different ensembles of predictive clustering trees (PCTs) and show that similar predictive performance can be achieved, when using the features extracted from the pre-trained deep-learning model. KEYWORDS Chest X-ray, deep-learning, predictive clustering trees, random forest, extra tree 1 INTRODUCTION Chest X-ray (CHR) is one of the most common medical imag- ing modalities, with millions of scans performed globally every year [6]. A computer-aided diagnosis (CAD) system can signifi- cantly reduce the burden of radiologists and thus reduce preva- lence and early detection of many deadly diseases. There has been a lot of effort recently, to harness the power of machine learning based methods, especially deep-learning, for disease classifica- tion and localization from CXR images [17]. Interpreting CXR images is very difficult even for the trained pathologists, with different visual ambiguities representing a significant challenge to distinguish between different diseases, resulting in misdiag- noses [5]. Recently, deep-learning based approaches have been presented, that together with the availability of large-scale datasets signifi- cantly improve the performance of CAD methods and in some Figure 1: Few examples of Chest X-ray images from the cases reach the radiologist-level performance [8]. In comparison CheXpert dataset [8]. with other approaches and datasets [9, 13, 1], newly presented datasets [8, 10] enable the development of CAD methods for detection of presence of multiple diseases present in CXR images 2 RELATED WORK at the same time. We evaluate an end-to-end deep-learning based approach Recent prevalence of deep-learning methods and increased avail- for multi-label classification (MLC) of CXR images, based on ability of large-scale datasets with labeled data has provided med- DenseNet architecture [7] and compare it with the traditional ical community with significant advances, in comparison with approach based on predictive clustering trees (PCT) [2], in an en- the methods that require sub-optimal manual feature engineer- semble setting, using the features extracted from the pre-trained ing [14]. State-of-the-art CNN models are becoming a de-facto deep-learning network. We demonstrate a similar predictive per- standard for a wide range of application in medical imaging, such formance on a large-scale CheXpert dataset [8], thus opening the as detection, classification and segmentation. Similar advances potential to use PCTs also in a hierarchical setting [20], which in terms of the methods and available data have been observed in the domain of Chest X-ray (CXR) images. Permission to make digital or hard copies of part or all of this work for personal Multi-label classification (MLC) setting is a very common set- or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and ting in interpreting CXR images, due to presence of multiple the full citation on the first page. Copyrights for third-party components of this diseases in one particular CXR sample. Deep-learning architec- work must be honored. For all other uses, contact the owner/author(s). ture CheXNet [19] was proposed, based on DenseNet-121 [7], Information society ’20, October 5–9, 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). trained on ChestX-ray14 dataset [21], which achieved state-of- the-art results over 14 labeled pathologies and even exceeded 108 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Dejan Štepec (b) (a) Figure 2: (a) Label uncertainty distribution over 14 pathologies in the CheXpert dataset [8] over all the samples in the training data and (b) distribution and probability of occurrence of multiple pathologies in a particular sample (multi-label classification). radiologist performance on pneumonia. Recently, very large-scale using radiographs, thus labels only represent positive or negative CXR datasets were presented, such as CheXpert [8] and MIMIC- class, with no uncertainties. Evaluation is performed only on 5 CXR [10], which enabled the development of much more robust observations, selected based on their clinical significance and supervised models. Additionally, the new datasets also capture prevalence in the dataset (i.e. Atelectasis, Cardiomegaly, Consoli- the notion of uncertainty through labels and different approaches dation, Edema and Pleural Effusion). have been proposed for handling such labels. A similar archi- The distribution of all the observed pathologies in the train- tecture to CheXNet was proposed and performance surpassed 3 ing data and their uncertainty is presented in Figure 2a and the certified radiologists in 3 different pathologies [8]. distribution of observations over a single example in Figure 2b, The above MLC approaches do not take into the account the which shows that there is around 30% chance of having at least 2 dependencies between disease labels, which, when exploited, pathologies present at the same time, labeled as definite positive. significantly improves the performance of the predictive mod- In CheXpert [8], different strategies of using uncertainty labels els [16]. We evaluate an end-to-end deep-learning based approach were evaluated. The two most simple approaches are to ignore for MLC of CXR images, based on DenseNet architecture [7] and uncertain samples during the training or to map them to either compare it with the traditional approach based ob predictive negative of positive class. They also evaluate a semi-supervised clustering trees (PCTs) [2], in an ensemble setting, using the fea- approach, where the ignore approach is used to label uncertain ex- tures extracted from the pre-trained deep-learning network. We amples, in order to re-label them. 3-class classification approach demonstrate a similar predictive performance on a large-scale is also evaluated where uncertain label is used as a separate class CheXpert dataset [8], thus opening the potential to use PCTs also during the training and during testing, only the probabilities for in a hierarchical setting [20], which taking into account under- positive and negative class are reported. In our work, we use lying dependency structure and powerful deep features, could the simple mapping approach, by mapping uncertain labels to a advance current state-of-the-art of the supervised MLC deep- positive class and not-mentioned samples to a negative class. learning based approaches and also compete against hierarchical deep-learning based approaches [4, 16], which take the hierarchy into account implicitly, using the conditional probability. 3.1 Methods We evaluate an end-to-end deep-learning based approach for 3 CHEXPERT: A LARGE CHEST multi-label classification (MLC) of CXR images, based on DenseNet- 121 architecture [7] and compare it with the traditional approach RADIOGRAPH DATASET based ob predictive clustering trees (PCT) [2], in an ensemble CheXpert [8] is a large publicly available dataset for chest ra- setting, using the features extracted from the pre-trained deep- diograph interpretation, consisting of 224,316 CXR images of learning network. 65,240 patients, where the presence of 14 different observations is labeled as positive, negative, uncertain or not mentioned. CXR images are collected retrospectively from Stanford Hospital, to- 3.2 End-To-End Deep Learning gether with associated radiology reports. Labels (and their un- Several convolutional neural networks (CNNs) were evaluated certainty) were automatically extracted from the section of the in CheXpert [8] and DenseNet-121 [7] architecture produced the radiology report, which summarizes the key findings. A large best results. Because of that, we used DenseNet-121 for all of list of phrases was manually curated by multiple board-certified our experiments. Original DenseNet is designed for multi-class radiologists to match various ways of observations, mentioned classification, where the neural network has the same number differently in the reports. Extracted phrases are then classified of output nodes as the number of classes. Each output node into positive, negative, uncertain or not-mentioned classes and belongs to some class and outputs a score for that class. In a aggregated into a final set of predefined observations (i.e. patholo- multi-class setting, the scores are passed through softmax layer, gies) with prevailed occurrence. The publicly available test data which converts scores into probabilities (class probabilities sums consists of 234 samples from 234 patients, where ground truth to 1) and the input sample is classified into a corresponding class, is set by a consensus of 3 radiologists, who annotated the set that has the highest probability. 109 Deep Multi-label Classification of Chest X-ray Images Information society ’20, October 5–9, 2020, Ljubljana, Slovenia In a multi-label classification (MLC) setting, the difference is, 4 RESULTS that an input sample can belong to multiple classes at the same We evaluated different approaches on the publicly available test time, thus the final score needs to be independent for each of data, consisting out of 234 samples from 234 patients, where the classes, because of that, sigmoid function is used instead of ground truth is set by a consensus of 3 radiologists. We report softmax. Additionally, categorical cross-entropy loss function the results in terms of the Receiver Operating Characteristic needs to be replaced with binary cross-entropy. We implemented Curves (ROC) in Figure 3 and its area under the curve (AUC) modified DenseNet-121 in PyTorch1 using Adam optimizer with in Table 1. In terms of the approaches presented in our work the same learning rates and parameters as used in CheXpert [8]. (i.e. DenseNet-121, RF-PCT and EXTRA-PCT), DenseNet-121 per- The images were resized to 320 x 320, same as in [8] and we forms the best, with EXTRA-PCT approach following it closely. trained the network for 10 epochs using a fixed batch size of 32 The biggest differences are observed on the Cardiomegaly class, images and evaluated the performance on a left-out validation which coincides with the results reported in CheXpert [8], as set of 500 images using the receiver operating characteristic most of the uncertain cases are borderline, which reduces the curve (ROC) and its area under the curve (AUC), averaged across performance of the simple mapping to positive or negative label. all observations. The best performing model in terms of global Table 1 also compares presented approaches against the DenseNet- AUC score was selected for evaluation on a test set, presented in 121 baseline presented in CheXpert [8], where 10 checkpoints Section 4. per run were chosen and each model was run three times, thus generating and ensemble of 30 models, which improved the re- 3.3 Predictive Clustering Trees sults by a small margin over our baseline DenseNet-121 approach. Predictive clustering trees (PCTs) [2] are decision trees viewed Nevertheless, we achieved or surpassed CheXpert results on Car- as a hierarchy of clusters, where the top node corresponds to diomegaly and Pleural Effusion classes and also achieved similar one cluster containing all the data, which is recursively parti- performance on other classes. tioned into smaller clusters while moving down the tree. PCTs are constructed with a standard "top-down induction of decision 5 CONCLUSION trees" (TDIDT) algorithm, the major difference in comparison In this paper we addressed the problem of Chest X-ray (CXR) with CART [3] or C4.5 [18] induction is that the PCTs treat vari-classification in a multi-label classification (MLC) setting and ance and prototype functions as parameters, selected based on compared an end-to-end deep-learning based approach with dif- the learning task at hand. To construct a regression tree, for ex- ferent ensembles of predictive clustering trees (PCTs) and showed ample, the variance function returns the variance of the given that similar predictive performance can be achieved, when using instances’ target values, and the prototype is their average value. the features extracted from the pre-trained deep-learning model. For the task of predicting tuples of discrete variables, used in This results show the potential to use PCTs also in a hierarchi- the multi-label classification (MLC) [15], the variance functions cal setting, which taking into account underlying dependency is computed as the sum of the Gini indices[28] of the variables structure and powerful deep features, could advance current from the target tuple and the prototype function returns a vector state-of-the-art. of probabilities, that an example belongs to a particular class in the target tuple. ACKNOWLEDGMENTS In our work we utilized PCTs in an ensemble setting, where This work has been supported by the H2020 iPC project (826121) a set of predictive models (i.e. PCTs) predictions are combined to obtain a final prediction, this is especially useful for unstable REFERENCES base predictors (e.g. trees), where small changes in the dataset, [1] Worawate Ausawalaithong, Arjaree Thirach, Sanparith yield substantially different models and usually achieves a much Marukatat, and Theerawit Wilaiprasitporn. 2018. Auto- better predictive performance [12]. In our work we consider a matic lung cancer prediction from chest x-ray images us- Random forest of PCTs (RF-PCT) [12] and ensembles of extremely ing the deep learning approach. In 2018 11th Biomedical randomized PCTs (EXTRA-PCT) [11] for MLC. In RF-PCT, several Engineering International Conference (BMEiCON). 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[14] June-Goo Lee, Sanghoon Jun, Young-Won Cho, Hyunna Lee, Guk Bae Kim, Joon Beom Seo, and Namkug Kim. 111 Smart Issue Retrieval Application Jernej Zupančič Borut Budna Miha Mlakar jernej.zupancic@ijs.si borut.budna@ijs.si Maj Smerkol Jožef Stefan Institute Faculty of Computer and miha.mlakar@ijs.si Jamova cesta 39 Information Science maj.smerkol@ijs.si Ljubljana, Slovenia Ljubljana, Slovenia Jožef Stefan Institute Jožef Stefan International Jamova cesta 39 Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia Figure 1: SIRA screenshot ABSTRACT developers, SIRA can help find existing answers to questions that We present Smart Issue Retrieval Application (SIRA), a customer have already been resolved by developers and therefore reduce support tool for searching of relevant email threads or issues the amount of distractions for the development team. when an email thread and keywords are given. Presented are the We use language models in order to retrieve information about overall application architecture, the processing pipeline, which the question from the issue at hand. Using multiple different ap- transforms the data into a search friendly form, and the search proaches, application searches the database of resolved issues in algorithm itself. order to find a developers’ answers to same or similar questions. KEYWORDS 2 SIRA ARCHITECTURE customer support, language models, information retrieval SIRA comprises five main application components (Fig. 2): (1) Database. PostgreSQL [6] is used as the application data- 1 INTRODUCTION base, since it includes decent built-in text search capabili- ties and change data capture options. Customer support is an important part of many large businesses (2) Processing daemon. Python [7] process responsible for data and high quality customer support can improve the user experi- processing for search in the event of change data capture. ence and help businesses retain their customer for longer periods. (3) Back-end application. Python Flask-based back-end appli- For larger companies, it can also be a strain on their human re- cation exposing the application programming interface sources as many customer support issues need to be resolved for SIRA. in short time. While the customer support team may resolve (4) Front-end application. React-based [8] single-page applica- most issues on their own sometimes they need the help of the tion for interacting with SIRA. development department. Often similar issues are presented to (5) Documentation. MKdocs-based user documentation for the developers multiple times. final users, admins, and developers. In order to minimize the number of issues that need attention from other departments, we have developed an application to Each SIRA component is packaged within a Docker [4] im- help the customer support technicians resolve issues without help age and can be managed using “docker-compose” [2] tool. This from developers. While some issues will still need the attention of enables deterministic packaging of application code for develop- ment, testing and production. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or 3 SIRA FUNCTIONALITY distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this The main goal of SIRA is to enable customer support staff to work must be honored. For all other uses, contact the owner/author(s). quickly find answers to similar questions that have already been Information society ’20, October 5–9, 2020, Ljubljana, Slovenia resolved in the past. Search is therefore the primary functionality © 2020 Copyright held by the owner/author(s). of the application and can be split into three parts: 112 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Novak, et al. particular word. This is sensible for cases when the word actu- ally repeats in the content. However, if it repeats due to the text duplication it could negatively impact the search results. We define a repeated email as an email body that appears within another email body. This is usually a result of using a “Reply” functionality when responding to an email within an email client. To delete email 𝐴 from email 𝐵, the following method is used: (1) Extract only alphanumeric characters from the two email bodies 𝐴 and 𝐵 to get alphanumeric(𝐴) and alphanumeric(𝐵). (2) If alphanumeric(𝐴) appears within alphanumeric(𝐵), mark it for removal from alphanumeric(𝐵). (3) If alphanumeric(𝐴) does not appear within alphanumeric(𝐵), Figure 2: SIRA architecture overview iterate over substrings of alphanumeric(𝐵) and compute the matching percentage of consecutive alphanumeric blocks from alphanumeric(𝐴). The substring with the max- (1) Processing. Upon new data arrival, pre-processes the text imum match is a candidate for removal. If it exceeds a to obtain representation suitable for search. predefined threshold it is indeed marked for removal from (2) Search. Computing relevancy scores upon search request alphanumeric(𝐵). by taking into account as much information about issue (4) Reconstruct 𝐵 by dropping the substring marked for re- or email thread as possible. moval and all non-alphanumeric characters positioned (3) Logging. To improve the search in the future the search re- within the marked substring when expanded with all the sults and structured user feedback is gathered and stored. characters. In the rest of this section we will describe each part in more 3.1.2 Non-author lines removal. An email body usually com- details. prises: (1) Relevant content 3.1 Processing (2) Signature For the search to be efficient it is beneficial to pre-process the (3) Confidentiality notice raw emails. The processing daemon runs as a separate python (4) Previous email headers process and utilizes PostgreSQL’s logical replication functionality (5) Previous email content in order to transform new content as soon as it is written to the The only text that should be used for text comparison is the database. The following steps are executed when processing the relevant content part. While previous email content was mostly issues: removed in the repeated emails removal step (3.1.1), other email (1) HTML clean. Beautiful Soup [1] library is used to extract body parts can still impact text comparison results. Machine only relevant text from email XML markup. learning was utilized to develop a model for determining whether (2) Empty line removal. Python script is used to detect and a particular line in the email body belongs to the relevant content remove empty lines. part of an email or not. (3) Repeated emails removal. Parts of emails are deleted if they Dataset preparation. First, we implemented an application already appear within some previous mails of the same with a basic graphical user interface that enabled us to label each issue. line with one of the following categories: (4) Semi-structured emails handling. Some emails are actually (1) AUTHOR. The relevant content falls into this category. a filled out form in an email format. A python script is (2) QUOTED. This is the previous email content. used to extract only the relevant information. (3) AUTO-PERSONALIZED. This is the text, that was set by (5) Non-author lines removal. A machine learning model was a user in the email client, which is automatically inserted developed and is deployed for tackling this task. by the email client. Signature is an example of this. (6) Non-alphanumeric-only characters lines removal. Python (4) AUTO-NON-PERSONALIZED. This is the text inserted script is used to detect and remove those lines. by the email client automatically. An example of this is (7) Word vector representation computation and update. Fast- previous email headers. Text [3] word vectors are used to compute word vector (5) NEEDS-PRETTIFY. Sometimes the whole email body is representation of text. present in one line only. To properly label the body it (8) Storing of processed text. The processed text is stored into should be further split into multiple lines. database, where built-in database indexing is utilized to (6) OTHER. Everything else. further prepare the text for efficient text searching. Second, we labeled each line belonging to 100 random issues. In the rest of this section we focus on the non-trivial processing This way we generated a dataset of 37,421 labeled lines in 586 steps. emails. Since the assumption was that the “QUOTED” lines are 3.1.1 Repeated emails removal. There were two reasons for re- already filtered out using remove repeated emails method, we moving repeated emails from an email thread. First, when dis- omit those lines from the dataset. This left us with 9,848 labeled playing an email, usually also all the previous emails are included, lines. which results in poor readability. Second, some methods for com- Features. The computed features were of two types: local paring the text take into account the number of occurrences of a features that took into account just the current line, and global 113 Smart Issue Retrieval Application Information society ’20, October 5–9, 2020, Ljubljana, Slovenia features that took into account the relative position and content A basic GUI was built to inspect the models and overview the of a line within the whole email. miss-classified examples. In the end, the hierarchical model was Local features: chosen with most of the presented features, with the exception of (1) Number and proportion of capitalized words “CountVectorizer” and “Tfidf Vectorizer” features. The additional (2) Number and proportion of non-alphanumeric characters chosen higher-level feature was the sum of three consecutive (3) Number and proportion of numeric characters “AUTHOR” probabilities. Random forest was chosen as the clas- (4) “CountVectorizer” from the scikit-learn ([5]) package sification algorithm, without feature standardization or dimen- (5) “Tfidf Vectorizer” from the scikit-learn package sionality reduction step. The threshold probability was lowered (6) Word vector line representation to 0.12 so recall could be kept high. The final model miss-classified 59 out of 2,394 rows marked Global features: as “AUTHOR” (recall = 0.975) and 629 out of 7,454 rows marked (1) Line position from the start as “OTHER” (recall = 0.806). (2) Line position until the end 3.1.3 Word vector representation computation and update. Word (3) Does “regard” appear before this line, within this line, after vector representation of content is used to compare email bodies this line and email subjects between different issues. (4) Do four or more consecutive non-alphanumeric characters To compute the word vector representation of text, either appear before this line, within this line, after line issue body or issue subject, the following steps are executed: (1) (5) Does a date-like string appear before this line, within this Tokenize text, (2) Remove stop-words, (3) Query word vector line, after this line representation for each word using fastText common crawl word (6) Does a time-like string appear before this line, within this vectors with dimension 300, (4) Compute mean of all word vectors line, after this line belonging to the words in the text, (5) Normalize the mean vector In order to smooth the predictions we also tested hierarchical by dividing the mean vector by the mean vector length. modeling by first building a model for “AUTHOR” detection and Instead of generating the representation vectors on-the-fly, then using the predictions on the lower level as additional fea- they are pre-computed and only read when needed, which greatly tures for the higher level. One approach for using the predictions reduces the inference time. To update word vector representation from the lower level was to just use the “AUTHOR” predictions of a particular text, the corresponding row in the word vector of lines just before and just after the current line. The predictions matrix is updated with the new values and stored on disk as a were padded with 1 at the beginning of an email and with 0 at Numpy array. the end. The second approach was based on the sum of three consecutive “AUTHOR” class probabilities for: lines, just before 3.2 Search the current line, lines where the current line is in the middle, and Each issue consists of: subject, document (the email body of text), lines just after the current line. We padded the predictions with and keywords the user marked the issues with. The keywords can 1s at the beginning of an email and with 0s at the end. be positive, meaning that a keyword is related with the contents Further, the features were scaled using the StandardScaler and of the issue, or negative when keyword is not related with the the feature space dimensionality was reduced using the principal contents of the particular issue. Additionally, a keyword can component analysis - PCA, both from the scikit-learn package. be explicit, where a user uses the keyword for searching when Models. For modeling we utilized scikit-learn package and considering a particular issue. On the other hand, a keyword can tested the following algorithms: (1) Logistic regression, (2) Multi- be implicit – soft keywords, where the user searched for relevant nomial Naive Bayes, (3) Support vector machine, (4) Random issues using a keyword, but the search results were not marked forest classifier. as relevant. Rudimentary hyper-parameter tuning was done to pick the When computing the relevancy of issues, given a starting best ones. issue and some keywords, several relevancy sub-scores are first Evaluation. Each pipeline was evaluated using 10-fold cross computed and then aggregated to form a single relevancy score. validation with the splits over issues. This means that all the lines In Table 1 all combinations for relevance sub-scores are listed. belonging to one issue were either in the training or the testing The final score is computed as a weighted average, as in equa- set to prevent data leaking. tion 1. The weights 𝑤 were determined based on the final user Model selection. The performance of all models was tracked 𝑖 feedback. through various metrics: (1) Confusion matrix finalScore = 𝑤1 · KeywordToKeywordScore (2) Precision and recall at different minimum recall thresholds + 𝑤2 · KeywordToSoftKeywordScore (3) Precision-recall curve (4) “AUTHOR” probabilities for each line in the test set + 𝑤3 · KeywordToDocumentScore The main concern regarding the model performance was that + 𝑤4 · KeywordToSubjectdScore it should prioritize keeping the “AUTHOR” lines (“AUTHOR” + 𝑤5 · DocumentToKeywordScore (1) recall) over average model accuracy. This is a direct result of the + 𝑤 application architecture – if the line would be removed by the 6 · DocumentToSoftKeywordScore chosen model, it wouldn’t be possible to search over it. This would + 𝑤7 · DocumentToDocumentScore directly impact the performance in the real-world. Additionally, + 𝑤8 · SubjectToKeywordScore few additional lines shouldn’t hinder the readability too much. The gathered metrics enabled us to closely inspect each model + 𝑤9 · SubjectToSoftKeywordScore and overview the performance regarding real-world application. + 𝑤10 · SubjectToSubjectScore 114 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Novak, et al. Table 1: Relevance sub-scores matrix Other issues (Not) Keyword Soft (Not-) keyword Document Subject (Not-) Keyword Exact match Exact match Full-text search Full-text search issue Soft (Not) Keyword / / / / ent Word vector cosine Document Reverse full-text Reverse full-text / search search similarity Curr Word vector cosine Subject Reverse full-text Reverse full-text / search search similarity 3.2.1 Exact match. This relevance score compares (soft) key- the database, including user defined keywords and appropriate words related to issues and those inserted in the keyword input results marking. box. Given a (soft) keyword, search for all the documents that are Preprocessing is done without any user interaction and in- in relation to this exact (soft) keyword. Each relation can either volves multiple algorithms and AI methods to extract the text of be positive or negative. Therefore, the returned score is positive the issue from original encoded emails. Testing of the algorithms in case of positive relation and negative otherwise. shows good results both in terms of precision and recall. Word vector representations are pre-computed in order to improve 3.2.2 Full-text search. This relevance score compares keywords performance of search algorithms. entered in the keyword input box and issue documents or issue Based on the extracted plain text of the issue the application subjects. Full-text search capability of PostgreSQL is leveraged for searches for similar issues that have already been resolved. The this score. However, the results are modified to return negative users can therefore quickly find the information related to the scores in case of not-keyword match. issue. The system is currently in use and only after some time of 3.2.3 Reverse full-text search. This relevance score compares real-world usage we will be able to evaluate the whole system. the selected issue document or subject and all existing (soft) Due to logging the interactions in the database we expect to keywords. First, for each keyword a full-text search relevance be able to analyze the usage and quality of the results. This will score is computed. Second, for each issue in the database do a allow us to improve the system and add other functionality that sum of its related keyword relevance scores. will improve user experience and further improve the customer support technicians’ workflow. 3.2.4 Word vector cosine similarity. This relevance score com- pares the selected issue document and subject to all existing issue ACKNOWLEDGMENTS documents and subjects, respectively. Pre-computed word vec- tors as described in Section 3.1.3 are used. The relevance score is Nicelabel d.o.o. funded the research presented in this paper. We computed as: thank Gregor Grasselli, Zdenko Vuk and Miha Štravs for help in application development. wordVectorSimilarity(𝑇1,𝑇2) = 1 − 𝑇1 · 𝑇2. (2) Since the word vectors used are normalized, this is actually REFERENCES 1− cosine distance between 𝑇1 and 𝑇2. [1] Beautiful Soup Developers. 2019. Beautiful soup. https:// Two other methods for comparing the text were also tested: www.crummy.com/software/BeautifulSoup/. (2019). PostgreSQL built-in trigram text similarity, which was too slow [2] Docker Inc. 2019. Docker-compose. https://docs.docker. for production use, and tf-idf representation of text and cosine com/compose/. (2019). distance-based relevance score, which did not perform as well as [3] Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas the word vectors method. Mikolov. 2016. Bag of tricks for efficient text classification. arXiv preprint arXiv:1607.01759. 3.3 Logging [4] Dirk Merkel. 2014. Docker: lightweight linux containers To improve the search performance in the future, several interac- for consistent development and deployment. Linux journal, tions with the application are logged: 2014, 239, 2. (1) Search results with relevance scores [5] F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. (2) Viewed search results Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, (3) Relevant issue/belonging email found V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. (4) No relevant issue/belonging email found Brucher, M. Perrot, and E. Duchesnay. 2011. Scikit-learn: Only after sufficient real-world usage of the application we machine learning in Python. 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The main functionalities of the first major release include preprocessing of the text of the issue, search integrating four different search algorithms and a logging system that stores interactions with the system into 115 Adaptation of Text to Publication Type Luka Žontar Zoran Bosnić University of Ljubljana, University of Ljubljana, Faculty of Computer and Information Science Faculty of Computer and Information Science Ljubljana, Slovenia Ljubljana, Slovenia zontarluka98@gmail.com zoran.bosnic@fri.uni- lj.si ABSTRACT In this paper, we adapt texts to context by manipulating three text evaluation metrics: length, polarity and readability. Our In this paper, we propose a methodology that can adapt texts method will be able to transition between social media posts, re- to target publication types using summarization, natural lan- search articles, newspaper articles and official statements, where guage generation and paraphrasing. The solution is based on key each publication type targets a different audience. While gov- text evaluation characteristics that describe different publication ernmental institutions and academics both publish neutrally- types. To examine types, such as social media posts, newspaper oriented texts, research articles tend to be much longer than articles, research articles and official statements, we use three dis- official statements. Social media and news usually target wider tinct text evaluation metrics: length, text polarity and readability. audiences, which is why texts should be more readable. However, Our methodology iteratively adapts each of the text evaluation the two can be separated by the amount of opinion we can in- metrics. To alter length, we focus on abstractive summarization clude. Newspaper articles should be less biased and thus include using text-to-text transformers and distinct natural language gen- less positively or negatively-oriented words. eration models that are fine-tuned for each target publication Our methodology iteratively adapts key text evaluation met- type. Next, we adapt polarity and readability using synonym rics towards the mean values of the target publication type that replacement and additionally, manipulate the latter by replacing will be calculated from a sample set of articles. In each iteration sentences with paraphrases, which are automatically generated our method first manipulates length using abstractive summariza- using a fine-tuned text-to-text transformer. The results show that tion techniques and natural language generation models. Next, the proposed methodology successfully adapts text evaluation it replaces words with more appropriate synonyms and adjusts metrics to target publication types. We find that in some cases polarity and readability scores. Finally, it uses a fine-tuned text- adapting the chosen text evaluation metrics is not enough and to-text transformer to generate more appropriate paraphrases we can corrupt the content using our methodology. However, that replace whole sentences in our text and alter readability. generally, our methodology generates suitable texts that we could present to a target audience. 2 RELATED WORK KEYWORDS While we are trying to automatically adapt texts to a particular genre, researchers have already made progress in automatic text text adaptation, context-aware, artificial intelligence, text sum- simplification, where we try to adapt text to be more readable and marization, natural language processing easier to understand. Carroll and Tait [2] developed a methodol- ogy to simplify texts for people that suffer from aphasia, which 1 INTRODUCTION is a disability of language processing. The developed system con- With more and more internet usage, the textual data on the inter- sists of an analyser component, which provides syntactic analysis net is highly increasing. However, different media target different and a simplifier component, which adapts texts using lexical and audiences and thus an arbitrary article may not be appropriate syntactic simplification. Lexical simplifier replaces the words in for everyone. Consequently, already published content is being text with synonyms by considering Kucera-Francis frequency rewritten and adapted for other target audiences. of each available synonym that is held in WordNet. Syntactic Why is targeting audiences so important? When speaking constructions that are not constructed in Subject-Verb-Object with someone in person, we adjust body language, tone and the order can also be tough to process for aphasic people. Therefore, words we use, so that the audience understands the message we the authors proposed several syntactic simplifications, such as are trying to send. In a similar manner, we also have to be aware replacement of passive constructions with active constructions. of the target audience when writing. Even though the task of A lot of research has already been done on how to evaluate adapting texts to different audiences may look easy to experi- and alter text and we will use many existing methods to help enced writers, rookies and amateurs may struggle in selecting us develop our methodology. We picked three text evaluation the information that might be relevant to a particular target audi- metrics that can be reasonably altered using existing methods. ence. Nevertheless, a way to deal with words and some common Flesch [5] developed an equation that determines the readability sense should be enough to complete the task, but due to the of the text using the number of words per sentence and the latter requirement automating this task becomes a much harder number of syllables per word ratios. Even though structure-based problem. metrics are important, we also have to consider the message of the text. Using sentiment analysis, we can determine whether the Permission to make digital or hard copies of part or all of this work for personal writer has positive or negative affections towards the topic of the or classroom use is granted without fee provided that copies are not made or text. Feldman [4] in his article discusses several approaches of distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this sentiment analysis based on the unit that we will be classifying work must be honored. For all other uses, contact the owner /author(s). (i.e. documents, sentences, aspects). Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia As length is one of the chosen text evaluation metrics that © 2020 Copyright held by the owner/author(s). we wish to adapt, we have to be able to both summarize and 116 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Žontar and Bosnić extend the text. According to Allahyari et al. [1], we differentiate firstly pre-trained on a data-rich task using texts from the between extractive and abstractive summarization approaches. Colossal Clean Crawled Corpus and then fine-tuned on a Extractive approaches shorten the original text by excluding less downstream task using a dataset of texts and their sum- relevant sentences. Significance of the sentence can be evaluated maries as the expected outputs from the aforementioned by determining whether the sentence is related with the main corpus. topic or whether its content is distinctive in comparison to other • To generate additional text, if the input text is shorter sentences. On the other hand, abstractive approaches tend to than the average text of the target publication type, we summarize texts in a new (more human-like) manner by struc- use fine-tuned natural language generation models. turing the text into some logical form such as graphs, trees and We generate four pre-trained GPT2 natural language gen- ontologies [6]. eration models [7] that are based on the aforementioned When adapting shorter texts to longer, natural language gen- unsupervised multitask learners. Each model is then fine- eration has proven to be a very strong tool. Radford et al. [7] tuned on a dataset of 100 texts of a certain considered developed a natural language generation technique to generate publication type and should be able to generate texts simi- additional text and produced state of the art results using unsu- lar to the ones that it was fine-tuned on. Consequently, we pervised multitask learners for model learning. Their model was would assume that the generated text needs less further trained to predict the next word in text based on 40GB of Internet adaptation. content. They concluded that large training datasets and models • While adapting length might be the procedure with the trained to maximize the likelihood of a sufficiently varied corpus most visible results, we also have to adapt the other text can learn a surprising amount of tasks, while no supervision is evaluation metrics. We develop a synonym replacement needed in training. procedure to adjust polarity and readability scores to the Another method that is commonly used when adapting texts target values. The procedure is executed in iterations and to context is paraphrasing, i.e. rewording of something written in each iteration we replace the word with the highest sum by changing its structure or replacing the words with their syn- of absolute relative differences of polarity and readability onyms. Goutham in his article [9] used a pre-trained text-to-text scores to the initial values of the target publication type transfer transformer to generate paraphrases of questions. The with its optimal synonym, i.e. the synonym which causes model was fine-tuned, where the input texts were questions from the sum of absolute relative differences to minimize. We Quora and the expected output were the questions that were used the lexical database WordNet to acquire synonyms labeled as their duplicates. of the considered word. In our paper, we plan to exploit the aforementioned abstractive • Finally, we alter readability by generating paraphrases summarization technique to shorten our texts and fine-tune the with a T5 text-to-text transformer [9] that was fine- pre-trained natural language generation model that Radford et tuned to generate paraphrases by learning on Microsoft al. [7] developed. Similarly as Goutham [9], we intend to fine-Research Paraphrase Corpus dataset [3]. We then pick the tune a pre-trained text-to-text transformer that would be able optimal paraphrase, which minimizes the relative differ- to generate paraphrases of a sentence. To calculate readability ence to the target readability score. score of the input text, we plan to use the formula proposed by Flesch [5]. Replacing sentences with their paraphrases could potentially also alter length and polarity. We test the assumption by generat- 3 ADAPTATION OF TEXT ing five paraphrases for each sentence in 100 documents for each considered publication type and find that the relative difference As mentioned before, the proposed method iteratively manipu- of length and polarity between the initial sentence and its para- lates the chosen text evaluation metrics to adapt text to different phrases is not significant. The obtained mean relative difference target audiences. In Figure 1, which gives an overview of the −3 of polarity scores in this preliminary analysis was 0.91 · 10 and method, we can see that before we start running the process, we −3 the mean relative difference of lengths was 0.11 · 10 . calculate the initial values of text evaluation metrics for each publication type as the average values of a set of documents. Our main dataset consists of 150 documents for each publication type, 4 EVALUATION AND RESULTS where all the documents hold text that contain COVID-19 related In our experiments, we evaluate the quality of text transforma- content, with which we minimize the effect of variables that we tion between all possible pairs of four different publication media will not take into account in text adaptation. We also define the types: social media, news, research articles and official statements. number of iterations (in our case: 5) and the acceptable error 𝜖 We tested our methodology by generating adapted texts of a sub- (in our case: 𝜖 = 0.1) that determines whether it is still worth set of the main dataset that was introduced in Section 3. The altering a particular text evaluation metric. subset consists of 100 documents for each publication type (i.e., In each iteration, relative differences between current and 400 altogether) that were randomly chosen from the main dataset. initial values of text evaluation metrics are calculated. If the We adapted each document to the other three publication types absolute relative difference to some metric is bigger than 𝜖 , we try and thus test all of the 12 possible transitions. We observed how to adjust it to the targeted value. We adjust key text evaluation the key text evaluation metrics behaved and whether the gen- metrics in the main loop of the process in Figure 1 using the erated text was meaningful or not. The results text evaluation following procedures: metrics before and after adaptation to context are shown in Table • In case the target length is smaller than its current value, 1. In Table 2, we present the results of content quality evaluation we use a pre-trained T5 text-to-text transformer [8] to of the generated texts. summarize the input text. The model is an encoder-de- From Table 1 we can observe that the text evaluation metrics coder model that uses transfer learning on a model that is successfully changed in the right direction. In most cases we 117 Adaptation of Text to Publication Type Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Target publication type Official statements Research articles News Social media Input publication type Initial Adapted Initial Adapted Initial Adapted Initial Adapted Length 0.79 0.04 0.04 0.03 36.39 0.35 Official statements Polarity 2.88 0.15 2.05 0.04 2.78 0.4 Readability 0.36 0.75 0.23 0.35 0.4 0.24 Length 3.06 0.05 2.99 0.04 136.23 0.33 Research articles Polarity 0.81 0.27 0.33 0.07 0.18 0.46 Readability 0.17 0.08 0.34 0.22 0.45 0.12 Length 0.97 0.03 0.99 0.03 63.79 0.4 News Polarity 0.88 0.14 0.43 0.1 0.33 0.37 Readability 1.21 0.05 1.2 0.84 0.24 0.11 Length 0.69 0.02 0.64 0.03 0.97 0.04 Social media Polarity 0.85 0.28 0.28 0.02 0.55 0.06 Readability 0.71 0.27 0.69 0.8 0.24 0.28 Table 1: Absolute relative differences to initial values of target publication type before and after transition that synonym replacement method performs suitably, too. Its inefficiency may be caused by the lack of choice in synonym and paraphrase replacement and the limited amount of words and sentences that can be replaced. As an example, we tried to adapt this research article to a social media post. By including statements that are colored in yellow in Figure 2, such as “The authors have proposed” and “The researchers used”, we imply that the social media post talks about a research article, which it does. Furthermore, the replacement of the word “texts” with “written matters” and the word “audiences” with “audience groups” indicates that the initial readability of this research article is higher than the expected value of social media posts, because we lower the Flesch Reading Ease score with the mentioned transformations. The content is appropriate as it extracts some of the most crucial concepts of this article. Figure 2: Example of text adaptation from this research article to a social media post Additionally, we evaluated the content quality by checking semantic similarity between the input and the generated text. Using GloVe word embeddings, we transformed the text into vectors and calculated the angle between the vectors. With cosine measure we evaluated whether the vectors point in a similar direction, i.e. the contents of texts, are similar. In Table 2, we present the mean cosine similarities between GloVe embeddings of the input and the adapted texts. The results show that the generated texts preserve the original content. Cosine similarity Figure 1: Flowchart of the text adaptation methodology scores are high in all transitions, however, the scores are a bit lower when we adapt to or from a social media post. This could be a consequence of the inability to thoroughly define the content significantly improved the values of metrics. The length manipu- in short texts that are expected in social media. lation managed to consistently decrease the relative difference While our method successfully adapts key text evaluation towards targeted length and in many occasions even converge metrics, our results are not perfect when it comes to the con- under 𝜖 value. Polarity and readability scores seem harder to tent. Our method has its drawbacks such as generating lots of adapt. However, in each case we successfully adapted the sum of additional content, which often results in an unconnected text. relative differences of those metrics, with which we can conclude Additionally, synonym replacement and paraphrase generation 118 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Žontar and Bosnić hhhh Original publication type hhhhhhh Research article Official statement Social media News hhhh Target publication type hhhhh Research article 0.94 0.82 0.97 Official statement 0.95 0.82 0.97 Social media 0.83 0.93 0.90 News 0.95 0.96 0.82 Table 2: Cosine similarities between GloVe embeddings can incorrectly replace original sentence or word, where the context and the methodology could also consider patterns that paraphrase or synonym changes the meaning but proves to be might not be obvious to human’s eye. effcient when adapting text evaluation metrics, if there exist such synonyms that are more appropriate to use for a particular target REFERENCES audience. Nevertheless, our methodology generated a few se- [1] Mehdi Allahyari, Seyedamin Pouriyeh, Mehdi Assefi, Saeid quences that could be published for target audiences without any Safaei, Elizabeth Trippe, Juan Gutierrez, and Krys Kochut. changes and lots of texts would only require minor corrections. 2017. Text summarization techniques: a brief survey. In- To conclude this section, we are satisfied with the benchmark- ternational Journal of Advanced Computer Science and Ap- ing results that our method produced in adapting key text evalua- plications (IJACSA), 8, (July 2017), 397–405. doi: 10.14569/ tion metrics. The methodology produces some interesting content IJACSA.2017.081052. and can thus be used as a baseline for further text adaptation to [2] John Carroll, Guido Minnen, Yvonne Canning, Siobhan De- target audiences. vlin, and John Tait. 1998. Practical simplification of english newspaper text to assist aphasic readers. Proc. of AAAI-98 Workshop on Integrating Artificial Intelligence and Assistive 5 CONCLUSION Technology, (July 1998), 7–10. [3] William B. Dolan and Chris Brockett. 2005. Automatically In this article we developed a methodology that adapts texts constructing a corpus of sentential paraphrases. In Proceed- to context. The methodology focuses on three text evaluation ings of the Third International Workshop on Paraphrasing metrics: length, readability and polarity of the text. Our method (IWP2005), 9–16. https://www.aclweb.org/anthology/I05- iteratively adapts text to the calculated initial values based on 5002. the targeted publication type by adjusting the key text evalua- [4] Ronen Feldman. 2013. Techniques and applications for sen- tion metrics. We successfully managed to adjust text evaluation timent analysis. Commun. ACM, 56, (April 2013), 82–89. doi: metrics in nearly all transitions. 10.1145/2436256.2436274. While we found text evaluation metrics that define different [5] Rudolf Flesch. 1979. How to Write Plain English: A Book for publication types, in some cases adjusting these measures is not Lawyers and Consumers. Harper & Row. enough. Generating longer sequences of additional text, we find [6] Kavita Ganesan, ChengXiang Zhai, and Jiawei Han. 2010. that the generated content is not connected and while we can find Opinosis: a graph based approach to abstractive summa- a chain of related topics of subsections, in some cases it is hard rization of highly redundant opinions. In Proceedings of the to define the common thread that is held throughout the whole 23rd International Conference on Computational Linguistics text. Additionally, if such synonyms and paraphrases exist that (Coling 2010). Coling 2010 Organizing Committee, Beijing, corrupt the content but improve the relative differences to the China, (August 2010), 340–348. https://www.aclweb.org/ targeted values of key text evaluation metrics, the methodology anthology/C10- 1039. will replace existing words and sentences with senseless content. [7] Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Despite these drawbacks, we generated lots of results that reflect Amodei, and Ilya Sutskever. 2018. Language models are the targeted publication types and even more results that would unsupervised multitask learners. https : / / d4mucfpksywv. require only minor changes to be completely acceptable. We cloudfront.net/better- language- models/language- models. conclude this article with satisfactory results of both content of pdf . generated texts and their values of key text evaluation metrics. [8] Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Our ideas for further work include improvement of natural Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and language generation model, where the pre-trained model that we Peter J. Liu. 2020. Exploring the limits of transfer learning used should be trained on longer texts so that we could generate with a unified text-to-text transformer. Journal of Machine text based on longer prompts and thus make sure that we hold the Learning Research, 21, 140, 1–67. http://jmlr.org/papers/ common thread throughout the whole text. Determining whether v21/20- 074.html. synonyms or paraphrases corrupt the message of the text is also [9] Goutham Ramsri. 2020. Paraphrase any question with T5 very important. Word embeddings can be used to represent the (Text-To-Text Transfer Transformer). Towards Data Science. context of the text and we could use it to determine whether the [Accessed: 17. 8. 2020]. (2020). https://towardsdatascience. synonym fits the current context or not. Another way to adapt com / paraphrase - any - question - with - t5 - text - to - text - text to context would be to create a dataset of texts, where each transfer- transformer- pretrained- model- and- cbb9e35f1555. row hold different versions of the same text and each version represents the text written for different target audience. This way we would be able to teach text-to-text models to adapt text to 119 120 Zbornik 23. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2020 Zvezek B Proceedings of the 23rd International Multiconference INFORMATION SOCIETY – IS 2020 Volume B Kognitivna znanost Cognitive Science Uredili / Edited by Toma Strle, Jaša Černe, Olga Markič http://is.ijs.si 8. oktober 2020 / 8 October 2020 Ljubljana, Slovenia 121 122 PREDGOVOR Na letošnji konferenci Kognitivna znanost sodelujejo avtorice in avtorji z različnih disciplinarnih področij in predstavljajo tako empirične rezultate svojih raziskav kot tudi teoretska raziskovanja z najrazličnejših področji – od kognitivne nevroznanosti in psihologije do empirične fenomenologije, filozofije in umetne inteligence. Upamo, da bo letošnja disciplinarno in metodološko bogata konferenca odprla prostor za izmenjavo zanimivih raziskovalnih idej ter povezala znanstvenice in znanstvenike z različnih disciplinarnih področij, ki se ukvarjajo z vprašanji kognicije. Toma Strle Jaša Černe Olga Markič FOREWORD At this year’s Cognitive Science conference, the authors present their empirical studies as well as theoretical research from a diverse range of disciplinary backgrounds – from cognitive neuroscience and psychology to empirical phenomenology, phiosophy and artificial intelligence. We hope that this year's cognitive science conference – rich in disciplinary approaches and methodologies – will open space for exchanging intriguing research ideas and will bring together scientists from a diverse range of areas related to the exploration of the human mind. Toma Strle Jaša Černe Olga Markič 123 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Toma Strle, Center za kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Jaša Černe, Center za kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Olga Markič, Filozofska fakulteta, Univerza v Ljubljani Urban Kordeš, Center za kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Matjaž Gams, Odsek za inteligentne sisteme, Institut »Jožef Stefan«, Ljubljana ORGANIZACIJSKI ODBOR / ORGANIZING COMMITTEE Toma Strle, Center za kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Jaša Černe, Center za kognitivno znanost, Pedagoška fakulteta, Univerza v Ljubljani Olga Markič, Filozofska fakulteta, Univerza v Ljubljani 124 Phenomenology of Dissolution Experiences: An Exploratory Study Jaya Caporusso Ema Demšar MEi:CogSci Center for Cognitive Science University of Vienna University of Ljubljana Vienna, Austria Ljubljana, Slovenia jaya.caporusso96@gmail.com ema.demsar@pef.uni-lj.si ABSTRACT The sciences of the mind have lately shown an increased We report on an exploratory empirical phenomenological interest in this kind of experiences. The loss or decrease of study investigating the so-called dissolution experiences the sense of boundaries between the ‘self’ and ‘world’ (also (DEs), characterized by the subject experiencing a) a described as ‘other’ or ‘nonself’, cf. [1, 4]), brought about in dissolution of her psychological or sensory boundaries the context of meditative practice, has been recently and/or a fading of the sense of the self as a separate entity, explored in studies using both third-person [3] and first- and/or b) a feeling of unity or identification with (elements person [4] approaches. Apart from meditation, similar of) the surrounding environment. We conducted nine experiential phenomena have long been associated with the phenomenological interviews investigating seven DEs. The use of psychedelic substances such as LSD and psilocybin [5], qualitative analysis of collected descriptions of experience and have been, in this context, observed and investigated in elucidated the temporal unfolding of each DE episode, several recent studies [e.g., 6–8]. Changes in the habitual identified typical experiential elements characterizing sense of being a separated entity have also been reported in (specific phases of) DEs, and inquired into the differences contexts related to the engagement with art [9] or nature (cf. and similarities of DEs across different contexts. This study [10]). Finally, one can find a myriad of descriptions of similar is considered a pilot for a more extensive investigation of experiences in prose and poetry, for instance in the literary DEs. Our findings provide grounds for making the first step and philosophical movement of transcendentalism [16], in towards the phenomenological and conceptual clarification Walt Whitman’s poetry [17], in the cultural and literary of DEs, which have recently become an object of growing movement of the Beats [18], and in the poetic tradition of interest in the scientific community, consequently enabling haiku [19]; these sources frequently describe such further research. experiences as arising from contact with nature. KEYWORDS Despite their apparent abundance, experiences of this kind seem to lack a common phenomenological and Empirical phenomenology, Dissolution of the sense of conceptual description, with reports frequently expressed in boundaries, Sense of self, Altered states of consciousness language specific to the particular context in which they 1 occurred, or in which they are described. This makes it INTRODUCTION difficult to compare instances of potentially similar Various strands of scientific [e.g., 1–11] and non-scientific experiences reported in different traditions and situations, [e.g., 12–19] literature report on experiential episodes or by different subjects. Depending on the particular text, during which “the subjective sense of one’s self as an isolated these might be described under a variety of names, including entity can temporarily fade into an experience of unity with dissolution of the sense of boundaries (see for example [3–4]), other people or one’s surroundings, involving the dissolution self-transcendent experiences (e.g., [1]), ego death (e.g., [2]), of boundaries between the sense of self and ‘other’” [1:1]. In ego dissolution [6–8], and oceanic feelings [11]. In one of the autobiographical accounts, experiences of this kind are few available overviews of such phenomena, the article titled typically (albeit not always; see for instance [20]) described The varieties of self-transcendent experiences [1], such as “positively transformative moments that rank among the experiences are characterized by “transient mental states most meaningful of one’s life” [1:6]. Most frequently, they are marked by decreased self-salience and increased feelings of reported in association with religious and mystical traditions connectedness” [1:1] (cf. also [19]). (e.g., Atman Brahman union in the traditional Indian We refer to these and similar phenomena as dissolution philosophy of Advaita Vedanta [13], the meditative state of experiences (DEs). In line with the above-mentioned Samadhi in Classical Yoga and Buddhist meditation systems characterizations [1, 11], we define DEs as experiential [14], the phenomenon of unio mystica in the Christian episodes marked by (a) a feeling of a dissolution of one’s Tradition [15]; for an overview, see [1, 2]). psychological and/or sensory boundaries or a fading of one’s sense of self as an isolated entity, separated from ‘world’, Permission to make digital or hard copies of part or all of this work for personal ‘other’ or ‘nonself’, and/or (b) a feeling of one’s unity and/or or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice identification with the surrounding environment, with other and the full citation on the first page. Copyrights for third-party components of people or objects, or with something perceived as larger than this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia oneself. © 2020 Copyright held by the owner/author(s). 125 In this contribution, we present the method and results For illustration, consider the following excerpt from the of an exploratory empirical phenomenological study in interview about DE6 (i.e., the sixth investigated experience), which we investigated seven experiential episodes that, showing a back-and-forth exchange between the interviewer according to the above-specified criteria, qualify as DEs. The and the co-researcher Marco, aiming to describe his findings of this study will serve as guidelines for specifying experience without falling back on phenomenologically the focus and methodology to be adopted in a more extensive imprecise notions and metaphors: study, currently in its early stages of development, whose Marco: It's kind of impersonal and like not being in a body final aim will be to provide a detailed phenomenological […] Like part of something that's a lot bigger than yourself. description of DEs. […] Like I'm not aware of a body anymore. The sense of my The research questions we attempted to answer were: body, like being here at a certain point in the world, is gone. (1) What is it like to experience DEs; what are the typical Interviewer: Okay. And how do you know that the sense of being in your body is gone? experiential elements that can be found in DEs? (2) What are the potential similarities and differences between DEs Marco: Hm. It feels like I’m the universe. [Laughs.] I feel like I’m the universe. I feel like I’m the void. […] It’s a void feeling. occurring in different contexts? Interviewer: Okay, and how does it feel like to be the void? Marco: At first, it's cool! I think there is a first aspect of awe, 2 METHOD like a positive aspect of awe… Between October 2019 and January 2020, six co-researchers Interviewer: Okay, but how do you feel, how do you know (three females) participated in the study. Their average age that you are the void? was 31,2 (SD = 12,6) and they had, on average, 17,7 years of The interviews were conducted in English and Italian; they education (SD = 3,0). Five of our co-researchers were current lasted from 56 to 78 minutes. Each interview focused on postgraduate students of cognitive science; three among detailing the diachronic and synchronic dimension of the them had basic experience in phenomenological reporting selected DE. We started each interview by first asking the co- and one of them was trained in the micro-phenomenological researcher to describe the selected experience in its full method. One co-researcher was not familiar with either temporal unfolding; we then inquired in more detail into the cognitive science or phenomenological inquiry prior to the structure – rather than the content – of the experience within interview. We conducted nine interviews about seven experiential specific temporal phases (of variable duration) that were episodes (two episodes being an object of an interview characterized by the same experiential elements; we also twice) satisfying the above-specified criteria of DEs. We focused on the transitions between different phases. The selected co-researchers who reported having experienced a peak phase, i.e., the phase during which the elements (candidate) DE at any point in their life, and expressed characterizing DEs – a dissolved sense boundaries and/or a interest in its phenomenological exploration. The to-be- feeling of unity or identification with (elements of) the explored DEs were identified by the co-researchers surrounding environment – were present to the largest themselves in a conversation with the principal investigator extent, was identified already during the interview; the prior to the interview. synchronic structure of this phase was investigated in more In line with the breadth of our definition of DEs, the detail. investigated episodes varied with regard to their All interviews were recorded on audio or video and approximate duration (ranging from a few moments to transcribed verbatim. Our analysis process was informed by several minutes), the time since their occurrence (ranging general guidelines of qualitative analysis [22]. Transcripts from five days to 25 years prior to the interview), as well as were chronologically ordered, eliminating or marking the so- the context and activity within which they arose. All called “satellite dimensions” [23], so that further analysis investigated DEs occurred in an ecological setting: three in focused on the parts containing phenomenological the course of meditative practice, three during the use of descriptions. Descriptions of experience were divided into psychedelic substances, and one in the course of engaging temporally distinct phases (extraction of the diachronic with art. structure), with this process being guided by the prior To assist co-researchers in producing identification of the peak phase. For each phase, we identified phenomenologically rich descriptions of their experience, and described different experiential elements present rather than (as appears to often be the case in describing (extraction of the synchronic structure). Interview excerpts DEs) relying on experientially ungrounded used in the present contribution have been edited for clarity conceptualizations, we chose to base our interviewing by removing the interviewer’s interventions and less approach on the guidelines of the micro-phenomenological relevant parts of the transcripts. interview method [21]. When the generated description was phenomenologically too coarse, or when co-researchers 3 resorted to explaining, judging, or conceptualizing their RESULTS experience, the interviewer re-directed their focus back to In accordance with the exploratory character of the study, its describing experience as it was concretely and actually lived. findings are not conclusive, but present preliminary insights 126 that will guide our further research into DEs. Due to the majority of investigated experiences. Namely, DE7 started nature of our results and the space limitations of the present with a gradual diminishment of Lev’s sense of boundaries, contribution, we decided to refrain from laying out an which was then regained during the “break” in the song, only exhaustive list of constructed experiential categories. to be abruptly lost again with the beginning of the peak Instead, this section presents a limited selection of identified phase. By contrast, all other experiences (6/7) were experiential elements and characteristics that we find characterized by a continuous, uninterrupted climax of particularly interesting and/or illustrative of the defining elements of DEs towards the peak phase; in the investigated DEs. phases following the peak phase, these elements would then Specific aspects of DEs are presented in subsections 3.1– gradually or abruptly disappear. 3.3. We would, however, like to start this section by first In line with this more typical temporal unfolding is, for giving the reader a general impression of the studied example, DE2, during which co-researcher Claire perceived a experiences by presenting a typical description of a peak progressive lessening of – as she called them during the phase, taken from the interview about DE7. Co-researcher interview – the “lines of her body”. In the initial phase of the Lev experienced DE7 while attending a concert, standing in a experience, Claire was feeling the freshness of the air crowd of people in front of the stage, with the band playing a touching her skin, and a straight “line” between the skin and specific song. The initial phases of the experience, in line with the space around it; then, starting from the lower left part of the unfolding of the song, were characterized by a crescendo her face and gradually encompassing all of her body, all the of feelings of connectedness, while Lev’s sense of self, sense “lines” of her face and body began feeling “wobbly” at first of time, and sense of space were gradually diminishing. At a and then altogether absent from experience. In the last phase certain point, however, there was a sudden “break in the of the experience, the “lines” separating her body from the song” in which only the singer was performing, with the rest outside world “entered into focus” again. of the band remaining silent; during this phase, Lev reported Variability in the synchronic structure. The seven having briefly regained the type of awareness (of himself, his investigated DEs highly varied with respect to the particular body, and the surrounding space) that he described as experiential elements present in (specific phases of) the similar to that which he habitually experiences in the context described experience. The most notable difference refers to of his everyday life. When the band suddenly started playing which of two above-specified criteria for DEs – (a) and/or (b) again, Lev rapidly entered the peak phase of the experience: – were satisfied during their peak phase, and in what way. Co-researcher Nadja, for example, described an This contrast [between the “break” and the band playing again] really made me lose all my sense of self […] it's like the experience (DE1) she had while meditating with her eyes feeling where it feels like it is exploding and it's just big, all closed, sitting with her legs crossed on the floor of her room. the borders are gone […] it’s like a huge euphoria. But it feels As she was focusing on her breathing (visualizing wood while like it's everywhere. It doesn't feel that it’s in my body or… It exhaling, and imagining being part of this wood while just feels that everything is very euphoric. inhaling), she started experiencing a gradual dissolution of This feeling was accompanied by a decrease of the sense of the boundaries separating her body from her surroundings. being a separate self: Just before the peak phase, Nadja reported feeling a “hole” in It feels like everything is one, so like I'm aware that [the other the middle of her chest; in the peak phase, she described a people] are there but it feels like they are the same as me and sense of not having a frontal part of her torso at all. Here, a we are the same as the music, and […] just everything dissolution of bodily boundaries (criterion a) was reported appears to be one, everything. So before, it seems like we’re without any sense of identification or unity with (elements connected, we’re two different things that are connected, but in the end [i.e., when the peak phase begins] it doesn't seem of) the surrounding environment (criterion b). like [we] are two different things anymore. […] This sense of In DE3, on the contrary, co-researcher Andrea was connection changes into a sense of unity. [This sense of unity] experiencing strong identification with objects present in her cannot really tie to my experience, it just seems like a big physical surroundings (criterion b); however, she did not experience, one big experience. Not like me feeling these report on any sense of boundary dissolution (criterion a). things, just like […] this kind of feelings [that] float in the room, it’s not like me feeling it in my chest or in my whatever, The experience arose after Andrea consumed LSD and but it just seems to be there, everywhere. […] It's not inhaled laughing gas, starting then to recognize the reflection something that I do or that I perceive […] it's just… I’m part of her own face in various objects in her surroundings that of everything else […] If it’s my behavior or someone else’s, it she would look at. She reported feeling that the reflections doesn't really make a difference […] I'm out there somewhere. I don’t really know [where], but I also don’t she was seeing were “also part of who [she was]”, and while really care. she described “extend[ing] a little bit outwards, into what [she was seeing] and touching”, she stressed she never Before presenting specific experiential aspects of DEs, it is stopped feeling “in [her] body”. important to stress that the investigated DEs presented high When involving a sense of boundary dissolution, the variability with regard to their diachronic as well as investigated DEs also varied with regard to the described synchronic structure. mode of experiencing this dissolution: while in some cases, Variability in the diachronic structure. While the above the dissolution was described as an emphatically bodily excerpt from DE7 serves as a good illustration of the peak experience or even had a very specific bodily location (as in phase, its diachronic unfolding differed from that of the 127 the above-described DE1), in other cases (for example in perceived as “passing through their bodily boundaries”, DE7), the co-researcher described the dissolution largely usually without encountering obstacles in doing so (or without referring to the bodily feelings. encountering them less and less). This feeling was felt as In what follows, we list a subset of some interesting or moving either from the outside inwards or from the inside illustrative experiential elements and characteristics that outwards, and was sometimes experientially related to the featured in particular temporal stages of the investigated loosening of the sense of boundaries. For example, Claire DEs: (1) the peak phase, (2) the phases preceding the peak described an experience (DE2) that she had while lying on phase, and (3) the phases following the peak phase. her bed and following a guided meditation. Throughout the experience, she felt a pulsating sensation spreading from her 3.1 Elements present during the peak phase chest that was loosening the “lines of her body”: Identification of the action of feeling and the object felt. Peak [A]s this pulsates, I don't feel any. . block in a way. […] phases of four investigated DEs (in particular, three from the Nothing slows the feeling down in this area. [. .] It goes context of using psychedelic substances, and one from everywhere, sort of just spreads over the body and then goes engaging with art) were characterized by instances where out into space. [. .] Makes my, like this separation of my body, the co-researcher could not distinguish between the action of it makes it sort of thinner and lessens it. feeling and the object of feeling, or was experiencing the two Another example can be found in DE1, in which the peak as identical. For example, co-researcher Andrea, who phase (already mentioned above) was preceded by Nadja experienced DE3 while she was sitting on a couch, reported: experiencing the movement of air freely passing between the There was a certain awe. With the insight of everything being space in front of her chest and the inside of her chest: me […] It was not like there was a world out there. . There’s I inhaled, and I was surprised by this stream of air entering just my perceptions of the world, which are part of me clearly and directly into my chest. As if the air passes directly because they are my perceptions, and this extended to tactile from here [pointing to space in front of her chest] towards feelings [as well as visual]. So, when I was feeling the couch, the inside, and there is nothing that it has to go through. […] the feeling of the couch was part of me. […] It's difficult to I just observe this sensation, I continue inhaling and exhaling, distinguish my perceptions of things from the actual things. until I really […] notice that this air is not stopped by […] I could feel the softness of the couch, that softness was anything. […] At a certain point I really feel like there is a hole part of me, or just the pressure against me was part of me. in my body that makes the air going through it. At the Lev, in describing DE7, similarly remarked: beginning, just a hole. Then, after a while, I just feel there’s no frontal area […] So the frontal part is really just this I cannot really tell what’s the difference between me feeling exchange of air, there’s nothing else […] and in this way something and me seeing something, or like.. what the rest there’s no separation between what is actually the area of the world does, it’s like it's the same for me […] what is inside my body and what is outside, because the exchange of going on on the stage and what is going on in my head, I air is happening in the same space. I’m just a shape in which cannot really tell the difference. this exchange of air can take place, but nothing else. Transmodality. Two DE descriptions (one from the context of 3.3 Elements present after the peak phase using psychedelics, and one from engaging with art) reported Need to go back to the habitual way of experiencing. In two of on the unification of different sensory modalities. Marco, the investigated DEs (one from the meditation context and who experienced DE6 while being in the forest under the the other from the psychedelics context), the end of the peak influence of mescaline, thus described the merging of senses phase was accompanied by a need to go back to the “habitual” accompanying the onset of his sense of boundary dissolution: way of experiencing. In describing DE2, Claire described it as … it might be hard to separate different aspects of the visual and the feeling and the thinking because it might have all a wish, like this nag or a need to come back, to not stay in this been into one. Like the visual part was also the feeling, like because it’s really pleasant […], something that urges to come my sense of self was encompassed by this visual aspect, like back and then colors the entire space. this broad universal view, and then the feeling, like it might Marco reported on the need to “pull away” from what he was have all been wrapped into one. experiencing in DE6 (i.e., losing of sense of time and space, Similarly, in describing the beginning of the peak phase in accompanied by visual hallucinations of “weird creatures”): DE7, Lev reported: And then there's a sense that I don't want to, I don’t want Then, when everything else comes in again, it just loses the that, it's too scary. (…) Well, I don't know if I can control it or separation between the sound and colors and different not, but when I get scared […] then I pull out of it. sensory perceptions. Returning to the body/moment/location. In several analyzed 3.2 Elements present before the peak phase DEs, we noted changes, throughout the experience, of the “Feeling” that passes through the bodily boundaries. In four sense of body (5/7), time (4/7), space/location (4/7), or of investigated DEs (two from the meditation context, one from what the co-researcher was doing (2/7). Usually, the the psychedelics context, and one from engaging with art), awareness of these aspects was at its lowest during the peak co-researchers reported a feeling (a term all four phase, and returned towards the end of the DE. For example, spontaneously used in all four occasions to refer to different Claire reported that at the end of her DE, sensations, e.g., a pulsating or a movement) that they [t]here is a sense of coming back to the body. […] The body comes into focus again and the room […] the sense of the 128 room, where I am positioned, that there is a bed underneath for their time and enthusiasm. We also wish to thank the my legs and my body and then there is a drawer next to me anonymous reviewer for their thorough reading of our and stuff like that, all that sort of comes back, […] it brings to focus the body and where I am and what I’m doing. […] So it’s contribution and their insightful comments. like making the room and the world in a way. REFERENCES 4 FUTURE DIRECTIONS [1] David Bryce Yaden, Jonathan Haidt, Ralph W. Hood Jr, David R. Vago, Despite most co-researchers being familiar with the basic and Andrew B. Newberg, 2017. The varieties of self-transcendent experience . Review of General Psychology 21, 2, 143-160. guidelines for phenomenological reporting, the generated [2] John Harrison, 2010. Ego death and psychedelics. MAPS Bull 20, 40- descriptions of experience have often failed to reach the 41. [3] Yair Dor-Ziderman, Yochai Ataria, Stephen Fulder, Abraham desired phenomenological depth and precision, instead Goldstein, and Aviva Berkovich-Ohana, 2016. 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Phenomenology and the Cognitive Sciences 5, 3-4, 229- 269. experiential aspects of their DEs. [22] Uwe Flick, 2019. An Introduction to Qualitative Research (6th ed.). Sage Publications Limited, London, UK. ACKNOWLEDGMENTS [23] Claire Petitmengin, Anne Remillieux, and Camila Valenzuela- Moguillansky, 2019. Discovering the structures of lived experience. Phenomenology and the Cognitive Sciences 18, 4, 691-730. We would like to thank Maja Smrdu and Urban Kordeš for [24] Russell T. Hurlburt, 2011. Investigating Pristine Inner Experience: their support in this research, as well as our co-researchers Moments of Truth. Cambridge University Press, New York, NY. 129 Primerjava rezultatov analize funkcijske magnetne resonance z različnimi programskimi orodji Results of Functional Magnetic Resonance Imaging Analysis with Different Software Tools: A Comparison Nina Demšar Center za klinično fiziologijo, Medicinska fakulteta Univerza v Ljubljani Ljubljana, Slovenija ninademsar@yahoo.com POVZETEK 1 UVOD Funkcijska magnetna resonanca (fMR) je metoda slikanja Funkcijska magnetna resonanca (fMR) je raziskovalno aktivnosti možganov, ki temelji na kompleksni analizi podatkov, najpogosteje uporabljena metoda slikanja možganske aktivnosti ki jo omogočajo različna programska orodja. Med temi so najbolj [1]. Končni prikaz aktivnosti določenih predelov možganov pogosto uporabljeni AFNI, FSL in SPM. Želeli smo preveriti, če nastane s kompleksno analizo podatkov. Za analizo teh podatkov dobimo enake rezultate, ko podatke analiziramo z različnimi obstaja več programskih orodij, med katerimi so najpogosteje orodji. Naloga, ki so jo udeleženci opravljali, je bila osnovana na uporabljeni Analysis of Functional Images (AFNI), FMRIB blok eksperimentalnem načrtu; opazovali smo čustven odziv na Software Library (FSL) in Statistical Parametric Mapping slike nezdrave hrane v primerjavi v nevtralnimi slikami, ki niso (SPM). Celoten postopek analize vključuje dolg niz odločitev povezane s hrano. Pokazala se je velika variabilnost rezultatov glede zaporedja izvedbe posamičnih korakov ter specifičnih med programskimi orodji, tako v viških aktivacij, kot v samih vrednosti parametrov [2]. Ker vsako orodje uporablja nekoliko področjih teh razlik. Obstaja veliko možnih razlag za te rezultate; drugačne nastavitve in drugačno programsko kodo za največji pomen pripisujemo različnim pristopom registracije in procesiranje signala, obstaja možnost, da pri uporabi različnih normalizacije, ki so onemogočili direktno primerjavo. Ta študija orodij ne dobimo enakih rezultatov. Primerjava rezultatov teh je šele začetek eksploracije tega področja in nakazuje potrebo po orodij je pomembna, da ugotovimo, ali so rezultati fMR analize večji refleksiji fMR znotraj nevroznanosti.* skladni pri uporabi različnih orodij ali so odvisni od specifične izbire programskega orodja za analizo. V slednjem primeru je to KLJUČNE BESEDE potrebno ustrezno upoštevati pri vrednotenju in interpretaciji funkcijska magnetna resonanca, statistična analiza, rezultatov. metodologija, programska orodja, nevrofilozofija Za končno oceno aktivnosti možganov morajo biti zbrani podatki obdelani v kompleksnem procesu analize, ki vključuje ABSTRACT kontrolo kakovosti, popravo prostorskega popačenja, popravo premikov glave, popravo časa zajema posamičnih rezin Functional magnetic resonance imaging (fMRI) is a method of možganov, prostorsko normalizacijo, prostorsko glajenje, capturing brain activity, which is based on a complex analysis of časovno filtriranje, statistično modeliranje, statistično analizo in data. This is done in one of the available software packages, out vizualizacijo [2]. of which AFNI, FSL and SPM are most commonly used. We Carp [3] poudarja, da je v fMR eksperimentih prisotna velika wished to check if we got the same results, if they were analyzed variabilnost v metodoloških odločitvah. Po pregledu 241 fMR with different packages. The task that the participants were given študij je Carp [3] poročal o uporabi 32 različnih programskih was based on a block experimental design; we observed the orodij in 207 kombinacij korakov analize. Zaradi velikega števila emotional response to images of unhealthy food compared to kombinacij korakov pride do analitične fleksibilnosti, t.j. večji neutral images not related to food. The results showed a large spekter zaključkov analiz z uporabo sprejemljivih metod. Iz variability of the peaks of activation, as well as areas associated analitične fleksibilnosti sledita dve negativni posledici: povečano with them between the packages. There are many explanations število lažnih pozitivnih rezultatov in selektivno poročanje. for these results; we would put the main emphasis on the different Le nekaj raziskav je do sedaj primerjalo rezultate analiz z approaches to registration and normalization, which meant that a različnimi programskimi orodji. Bowring idr. [4] so opazili direct comparison was not possible. This study is only the veliko variabilnost v vrednosti t-statistik in lokacijah statistično beginning of the exploration of this area and shows a need for značilnih aktivacij, vendar to ni bilo konsistentno pri vseh more reflection on fMRI in neuroscience. eksperimentih. Glede na splošni vzorec aktivacij ni bilo opaznih KEYWORDS večjih razlik. Medtem ko so pri tej študiji analizo prilagajali eksperimentom, so Pauli idr. [5] primerjali analize s functional magnetic resonance, statistical analysis, methodology, programskimi orodji AFNI, FSL in SPM, pri katerih so uporabili software packages, neurophilosophy najpogosteje uporabljene nastavitve za vsako programsko ∗Tekst je v celoti osnovan na magistrskem delu z istim naslovom. orodje. Rezultati so pokazali podoben splošen vzorec aktivacije, 130 kjer je bilo pri AFNI-ju nekaj manj aktiviranih vokslov. Študija 3 REZULTATI lažnih pozitivnih rezultatov [6], ki je spet primerjala AFNI, FSL in SPM, je pokazala, da vsa orodja kljub nadzoru večkratnega 3.1 Variabilnost moči aktivnosti testiranja kažejo inflacijo statistične značilnosti. Podobno je Variabilnost moči aktivnosti pri programskih orodjih smo pokazala študija, ki je primerjala rezultate analiz na ravni prikazali s primerjavo razlik med Z-vrednostmi v vsakem vokslu posameznikov (in ne na ravni skupin), kjer so razlog za povišano končnih slik. Zaradi nekaterih razlik v končnih funkcijskih slikah število lažnih pozitivnih rezultatov pri SPM-ju pripisali preveč med orodji, ki se pojavijo zaradi različnih pristopov registracije enostavnemu modelu za šum, pri FSL-ju pa podcenjevanju in normalizacije, smo za to primerjavo naredili masko in prostorskega glajenja [7]. upoštevali le voksle, ki so prisotni pri vseh orodjih. Temelj vsakega znanstvenega pristopa je zanesljivost. Ta je Kot je razvidno s histograma na sliki 1, je največ vokslov z bistvenega pomena, če je naš cilj odkrivanje resnice in če želimo minimalnim razponom Z-vrednosti pri primerjavi AFNI-ja in metodo aplicirati v praksi in če želimo sodelovati z raziskovalci FSL-ja. Drugi dve primerjavi imata bolj podobno porazdelitev, z istega in drugih področij. Bennett in Miller [8] sta poudarila, da pri vseh pa je razpon manjši od 1 pri vsaj polovici vokslov. se raziskovalci, ki uporabljajo fMR metodo, premalo zavedajo (ne)zanesljivosti svojih raziskav. Zaradi številnih korakov v predprocesiranju pri izločanju šuma, in metodoloških odločitev, ki sledijo iz tega, je zanesljivost težko doseči. Iz tega sledi indirektnost opazovanja [9] in vprašljivost spadanja v paradigmo realizma [10]. Zanimalo nas je, ali s programskimi orodji AFNI, FSL in SPM dobimo enake rezultate pri analizi fMR podatkov in posledično, ali današnje stanje fMR raziskav odraža resničnost ali metodološko pristranskost. Cilj raziskave je bil, da s primerjavo rezultatov, pridobljenih s programskimi orodji AFNI, SPM in FSL, dobimo pregled nad razlikami in podobnostmi med rezultati. Zanimala nas je razlika v moči aktivnosti, vzorcu aktivnih predelov in deležu vokslov nad določeno mejo. Slika 1: Porazdelitev razponov Z-vrednosti pri vseh 2 METODE primerjavah. med programskimi orodji Raziskava je zajela kontrolno skupino 16 zdravih otrok in mladostnikov (10 ženskega spola) iz študije debelih 3.2 Variabilnost položaja in vzorca aktivnosti mladostnikov. Povprečna starost udeležencev je bila 14,1 let ( SD Položaj aktivnosti smo primerjali z lociranjem področij = 2,7 let, min = 10 let, max = 19 let). aktivnosti in opisom splošnega vzorca. Rezultati aktivnih Študija je bila sestavljena iz dveh nalog čustvene nasičenosti področij so se izkazali za zelo različne. dražljajev, povezanih s hrano. Dražljaji pri blok načrtu so bile Največji delež vokslov s prepoznanimi razlikami med slike, ki smo jih razdelili v dve kategoriji: kategorija nezdrave aktivacijama pod pogojema nezdrava hrana - nevtralni dražljaj je hrane in kategorija nevtralnih slik, ki niso prikazovale hrane. bilo pri analizi v FSL-ju, kjer je 1,14 % vseh možganskih vokslov Podatki so bili analizirani ločeno za blok in z dogodkom prišlo nad mejno vrednost. Sledil je AFNI, kjer je bilo 0,48 % povezan načrt v vsakem od treh programskih orodij AFNI, FSL vseh možganskih vokslov nad mejno vrednostjo, pri SPM-ju pa in SPM. Najprej je bila narejena povprečna strukturna slika vseh je 0 % vokslov preseglo mejo. udeležencev, ki smo jo uporabili za predlogo. Vsaka analiza je Analiza v FSL-ju je pokazala pet skupkov, kjer se največji bila izvedena po postopku in s parametri, ki so privzeti ali nahaja v levem fusiformnem korteksu. Sledita pozitivna razlika priporočeni za vsakega izmed programskih orodij; pri FSL-ju in med aktivacijama pod pogojema nezdrava hrana - nevtralni SPM-ju smo uporabili privzete nastavitve, pri AFNI-ju pa te dražljaj v desnem superiornem parietalnem režnju in desnem možnosti ni, tako da smo uporabili priporočene. Zaradi tega je inferiornem okcipitalnem režnju. Dve negativni razliki med prišlo do razlike v analizi: pri AFNI-ju smo vključili korak aktivacijama sta se pokazali v bilateralnem parahipokampalnem poprave časa zajema posamičnih rezin možganov, pri drugih girusu in lingualnem girusu, kot je razvidno na sliki 2. dveh orodjih pa ne. Po predprocesiranju, prvostopenjski in drugostopenjski analizi smo dobljene rezultate primerjali na več načinov. Variabilnost moči razlik med aktivacijami pod različnimi pogoji med programskimi orodji smo pokazali z razlikami med Z-vrednostmi. Položaj aktivnosti smo primerjali s splošnim vzorcem aktivnosti ter določanjem aktivnega predela s pomočjo različnih atlasov. Razlike med statistično značilnostjo rezultatov smo pokazali z deležem vokslov, ki presegajo izbrano mejno vrednost. Slika 2: Rezultat analize v FSL-ju (koordinate: 24L 40P 10I) 131 Analiza naloge z blok načrtom je v AFNI-ju pokazala šest 4 DISKUSIJA IN SKLEPI skupkov: dve negativni razliki med aktivacijama pod pogojema V pridobljenih rezultatih se je pokazala velika variabilnost F - C v bilateralnem lingualnem in fusiformnem girusu, ena področja in moči aktivacije med programskimi orodji. Ena izmed pozitivna razlika v levi insuli, dve pozitivni razliki v bilateralnem možnih razlag, zakaj je prišlo do te variabilnosti, je razlika v lateralnem okcipitalnem korteksu in ena v srednjem frontalnem metodah analize pri različnih programskih orodjih. Vsako orodje girusu (slika 3). ima drugačno ozadje, različne pristope ter drugačno zaporedje postopkov. 4.1 Primerjava postopkov Privzete ali priporočene nastavitve za vsako orodje so se razlikovale na vsakem koraku, sami koraki pa so se razlikovali v vrstnem redu. Pri vsakem orodju smo za popravo premikov glave uporabili drugačno referenčno sliko (sredinski volumen, povprečje vseh volumnov ali volumen z najmanj odstopanji v signalu) pri registraciji na strukturno in standardno sliko pa smo uporabili drugačne transformacije. Glede na bistvene razlike v maskah rezultatov vsakega orodja lahko sklepamo, da je ta korak bistven za razlike v naših rezultatih. Z AFNI-jem smo opravili najbolj konservativno glajenje, z SPM-jem pa najbolj liberalno. Razlika se je pokazala že pri rezultatih, ki niso statistično značilni, a je še bolj očitna po popravkih za multiple primerjave. Ker obstaja veliko pristopov k temu problemu – kot poudarijo Slika 3: Rezultat analize v AFNI-ju (koordinate zgornjih Poldrack idr. [2], je meja arbitrarno določena – ima vsako orodje treh rezin: 23L 49P 5I, koordinate spodnjih dveh rezin: 43R drugačen priporočen način popravkov na ravni skupkov. Veliko 12A 44S) korakov (predvsem pri predprocesiranju in pri postavljanju končne meje) pri metodah je torej lahko pripomoglo k Pri primerjavi vzorca aktivnosti najbolj izstopa analiza v variabilnosti rezulatov, veliko sprejemljivih možnosti v SPM-ju, ki ni pokazala nobenega aktivnega področja. AFNI in metodoloških odločitvah pa pomeni tudi veliko analitično FSL sta delno pokazala različna aktivna področja, razen fleksibilnost [3]. negativne razlike med aktivacijama pod pogojema F - C v lingualnem girusu in pozitivne razlike med aktivacijama v 4.2 Primerjava rezultatov desnem lateralnem okcipitalnem korteksu, kjer je prišlo do bistvenega pokrivanja. To vidimo na sliki 4, kjer + nakazuje Glede na velike razlike v rezultatih je potrebno izpostaviti, da aktivacije in - nakazuje deaktivacije. primerjava vrednosti vokslov temelji na predpostavki, da so slike prostorsko poravnane. V našem primeru niso bile, kar vidimo v različnih oblikah končih slik možganov. To je zato, ker smo želeli uporabiti privzete nastavitve, te pa so se pri registraciji in normalizaciji tako razlikovale, da so ustvarile končne slike različnih oblik. V manjši meri razlike opazimo pri Z-vrednostih pred postavitvijo meje. Kljub visokem maksimalnem razponu se pri vseh primerjavah vsaj polovica vokslov razlikuje za eno standardno deviacijo ali manj. Variabilnost viškov se je pokazala že v drugih študijah [11] [12], medtem ko je aktivnost na različnih področjih bolj nepričakovana (napram [4] [5] [11][12]). Pri raziskavi, ki so jo opravili Pauli idr. [5], se je AFNI izkazal za programsko orodje z najbolj konservativno analizo, medtem ko je v našem primeru glede na delež aktivnih vokslov to bil SPM. Medtem ko pri SPM- ju ni bilo aktivnega področja, smo z AFNI-jem našli šest skupkov velikosti med 16 in 64 vokslov, s FSL-jem pa kar pet skupkov velikosti med 56 in 406 vokslov. Glede na to, da eno orodje (SPM) ni pokazalo nobene aktivnosti, se postavi vprašanje lažnih pozitivnih rezultatov. Prejšnje raziskave so pokazale, da vsa orodja lahko povzročijo Slika 4: Področja aktivnih predelov glede na različna inflacijo statistične značilnosti [6], pri čemer je je pri SPM-ju programska orodja (koordinate zgornjih rezin: 21L 47P vzrok enostaven model za šum, pri FSL-ju pa podcenjevanje 10I, koordinate spodnjih rezin: 43R 61P 61) prostorskega glajenja [7]. Ker smo dobili tri različne slike, bi glede na našo študijo morali potrditi izjavo Ionnadisa [13], da je več raziskovalnih zaključkov napačnih kot pravilnih. Pomembno 132 pa je poudariti, da naši zaključki veljajo le za privzete oz. ZAHVALA priporočene nastavitve vsakega programskega orodja. Študija je bila izvedena na Centru za klinično fiziologijo (Univerza v Ljubljani, Medicinska fakulteta). Hvala Gregi 4.3 Pomanjkljivosti študije Repovšu in Andreju Vovku, mentorju in somentorju magistrske Za bolj trdne zaključke bi lahko študijo izvedli z določenimi naloge, katere povzetek je ta tekst. popravki. 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Nadaljevanje na kritičnem DOI: https://doi.org/10.1038/sdata.2016.102 raziskovanju delovanja metode fMR je torej ključnega pomena za nevroznanost. 133 What Anime to Watch Next? The Effect of Personality on Anime Genre Selection Sara Jakša sarajaksa@sarajaksa.eu Middle European interdisciplinary master’s programme in Cognitive Science, University of Ljubljana Ljubljana, Slovenia ABSTRACT 1.2 Entertainment preferences Personality can affect people’s entertainment preferences. This Personality can affect interests. Even an indirect indication of in- has been shown with TV shows, movies, books, and music. This terest, for example, Facebook likes, can predict personality [9]. study tries to see if there is also a connection between personal- There are some studies, showing the connection between per- ity and anime watching patterns and preferences. The analysis sonality and entertainment that people choose. was done on the reviews posted on the MyAnimeList website. The entertainment preferences were found to correlate with The study shows, that personality has a small connection with personality. When measured by questionnaires, Communal genre what people watch and a somehow bigger connection with what preference was positively correlated with agreeableness factors. they like to watch as shown by higher ratings. Aesthetic genre preference was positively correlated with open- ness and agreeableness factors. Dark genre preference was neg- KEYWORDS atively correlated with agreeableness and conscientiousness fac- personality, genre, anime, LIWC tors. And cerebral genre preference was positively correlated with openness factors [13]. The specific genres were also connected to personality when 1 INTRODUCTION the later was measured with Facebook likes. For example, in People use different media, to satisfy different psychological and books, openness predicted liking poetry and science fiction, while social needs [7]. But since different people can have different disliking drama, scary, and crime books. Conscientiousness pre- needs, these can also mean, that they choose different media to dicted liking education books and disliking comics, fantasy, and satisfy their needs. One of the ways to conceptualizes differences poetry. Extraversion predicted liking scary and humor books in people is through personality. and disliking fantasy, science fiction, and war books. Agreeable- ness predicted liking drama and education books and disliking 1.1 Personality war and crime books. And on the end, neuroticism predicted lik- ing crime and poetry books, while disliking non-fiction, thriller, Personality can be defined as differences in how people think, and mystery books [4]. feel, and behave in general [3]. The most popular personality Because of the size of the market, focus on mass media, and model in science is currently the Big Five model. The model in- different levels of tolerance for foreign media, most of the media cludes five traits [11]: exports in the world comes from the USA [6]. But Japan held the • Extraversion is defined by the frequency and intensity of primary role in the cartoon segment for decades. With animes positive feelings. These people are positively oriented, so- popularity increasing outside Japan [10], this allows for study cial, and assertive, as opposed to quiet. the mass media from a country that differs from the USA [2]. • Neuroticism is defined by the frequency and intensity of Since there is a lack of studies connecting personality and anime, negative feelings. These people are less resilient and more I would like to see, if there is a connection there. For this purpose, sensitive and nervous. I am going to try to answer two research questions. • Agreeableness is defined by the relative importance peo- Research question 1 Is personality connected with the anime ple place on other people when compared to themselves. genres people choose to watch? These people are more cooperative, empathic, and likable, Research question 2 Is personality connected with how much instead of competitive. people like the anime genres they watch? • Conscientiousness is defined by the need to follow a sys- tem and defined rules. These people are more efficient and organized, as opposed to spontaneous. 2 METHODOLOGY • Openness is defined by the number of associations with Data were collected by scraping the reviews and anime metadata different ideas and concepts. These people are more cu- from the myanimelist.net website in August 2020. There were rious and creative, as not as consistent as people on the 138335 reviews for 7570 anime series written by 52235 users. other end of the trait. Users were differentiated by their user name, there was no at- tempt made to figure out if one user is using multiple accounts. Permission to make digital or hard copies of part or all of this More than half of the users wrote only one review, while the work for personal or classroom use is granted without fee provided user with the most reviews wrote 554 reviews. that copies are not made or distributed for profit or commercial By scraping the genre metadata for each anime, there were 43 advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work different genres. Each anime can be in multiple different genres. must be honored. For all other uses, contact the owner/author(s). The genres are comedy, school, shounen, supernatural, hentai, Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia romance, seinen, dementia, a slice of life, kids, adventure, space, © 2020 Copyright held by the owner/author(s). mecha, military, sci-fi, action, fantasy, magic, music, game, drama, 134 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Sara Jakša shounen-ai, harem, horror, historical, sports, mystery, cars, par- well as the genre with the highest power among statistical re- ody, shoujo, demons, martial arts, yaoi, superpower, ecchi, thriller, sults for both low and high levels of the trait. If there are more vampire, samurai, psychological, police, yuri, josei, shoujo-ai. than three results, only the three strongest are presented. To get the personality scores of the people, I analyzed the con- tent of the reviews with the LIWC [14, 12]. This is a program Table 1: The summary of power results for review presence intended to study texts with the help of the word counts in dif- ferent categories. The categories include function categories, like the number of pronouns, and the content categories, like social trait N average highest high trait low trait processes. A 11 0.00272 .02019 Slice of Life Action I concatenated all the reviews for each person in a separate file. I analyzed these files with the LIWC program. The commer- E 8 0.00170 .00864 Hentai Action cial version also includes the Big Five scores, which is the most N 6 0.00157 .01036 Action Comedy frequent way of how to use LIWC to get personality. But in the C 5 0.00143 .01108 Slice of Life Action academic version, these are not available. So the personality was computed based on the correlations between LIWC categories O 10 0.00239 .01668 Sci-Fi Shoujo and personality found in previous studies. Some studies used this method before [1]. I used the correlations from the Yarkoni study [15], where 3.1.1 Agreeableness. People with higher agreeableness wrote over 600 people’s blogs were analyzed with LIWC and correlated more reviews for slice of life ( 𝜒 2 = 1087 , 𝑝 = . 000 , 𝜙 = . 014), with the Big Five traits from the questionnaire. I used only the comedy ( 𝜒 2 = 931 , 𝑝 = . 000 , 𝜙 = . 012) and music ( 𝜒 2 = 432 , 𝑝 = categories, that were significant at the p=.001. Since the blogs . 000 , 𝜙 = . 005). On the other hand, people with lower agreeable- were analyzed with the earlier version of the LIWC (version ness wrote more reviews for action ( 𝜒 2 = 1524 , 𝑝 = . 000 , 𝜙 = 2001) program, the equivalent groups from LIWC 2015 were used. . 020), horror ( 𝜒 2 = 623 , 𝑝 = . 000 , 𝜙 = . 008) and psychological If the category no longer existed, then it was dropped. The values ( 𝜒 2 = 473 , 𝑝 = . 000 , 𝜙 = . 006). were summed together to get the composite value. Based on this method, the traits were calculated in the follow- 3.1.2 Extraversion. People with higher extroversion wrote more ing way: Conscientiousness was calculated by summing achieve- reviews for hentai ( 𝜒 2 = 673 , 𝑝 = . 000 , 𝜙 = . 008), romance ment, anger (negative), negative emotions (negative), and nega- ( 𝜒 2 = 605 , 𝑝 = . 000 , 𝜙 = . 007) and harem ( 𝜒 2 = 467 , 𝑝 = tions (negative). Agreeableness was calculated by summing the . 000 , 𝜙 = . 005). On the other hand, people with lower extro- words connected with home, leisure, motions, space, positive version wrote more reviews for action ( 𝜒 2 = 576 , 𝑝 = . 000 , 𝜙 = emotions, anger (negative), negative emotions (negative), and . 007) and sci-fi ( 𝜒 2 = 455 , 𝑝 = . 000 , 𝜙 = . 005). swear words (negative). Openness was calculated by summing 3.1.3 Neuroticism. People with higher neuroticism wrote more the propositions, articles, words connected to death, home (neg- reviews for action ( 𝜒 2 = 818 , 𝑝 = . 000 , 𝜙 = . 010) and horror ative), leisure (negative), motion (negative), time (negative), fam- ( 𝜒 2 = 420 , 𝑝 = . 000 , 𝜙 = . 005). People with lower levels of ily (negative), social processes (negative), positive emotions (neg-neuroticism wrote more reviews for comedy ( 𝜒 2 = 679 , 𝑝 = ative), first-person singular pronouns and all pronouns. Extro- . 000 , 𝜙 = . 008), slice of life ( 𝜒 2 = 572 , 𝑝 = . 000 , 𝜙 = . 007) and version was calculated by summing words connected to sexual-romance ( 𝜒 2 = 438 , 𝑝 = . 000 , 𝜙 = . 005). ization, friends, social processes, and second-person pronouns. Neuroticism was calculated by summing anxiety, negative emo- 3.1.4 Conscientiousness. People with higher level of conscien- tions, and second-person pronouns (negative). tiousness write more reviews for slice of life ( 𝜒 2 = 817 , 𝑝 = The problem with this method is, that the result does not rep- . 000 , 𝜙 = . 010), comedy ( 𝜒 2 = 348 , 𝑝 = . 000 , 𝜙 = . 004) and resent the real values, but only the rankings of the people. This sports ( 𝜒 2 = 341 , 𝑝 = . 000 , 𝜙 = . 004). While people with lower is why the analysis will be done by comparing the highest 1/3 of conscientiousness wrote more reviews for action ( 𝜒 2 = 837 , 𝑝 = the review authors with the lowest 1/3 of the review authors on . 000 , 𝜙 = . 011) and horror ( 𝜒 2 = 460 , 𝑝 = . 000 , 𝜙 = . 006). each dimension. 3.1.5 Openness. People with higher level of openness write more reviews for sci-fi ( 𝜒 2 3 RESULTS = 1008 , 𝑝 = . 000 , 𝜙 = . 011), action ( 𝜒 2 = 662 , 𝑝 = . 000 , 𝜙 = . 007) and mecha ( 𝜒 2 = 369 , 𝑝 = . 000 , 𝜙 = 3.1 Analysis of Review Presence . 004). People with lower level of openness write more reviews The first analysis is for the percentage of the reviews that each for shoujo ( 𝜒 2 = 1450 , 𝑝 = . 000 , 𝜙 = . 016), romance ( 𝜒 2 = group wrote for each genre. If there are differences in the watch- 1302 , 𝑝 = . 000 , 𝜙 = . 014) and school ( 𝜒 2 = 752 , 𝑝 = . 000 , 𝜙 = ing patterns of people with different personalities, then this would . 008). be reflected in the number of reviews that people write. The peo- ple usually only write reviews for the shows that they watched. 3.2 Analysis of Review Scores So if there is a difference in ratios of reviews for different genres, In the next section, the scores of the reviews will be analyzed. For this can be indicative of different watching patterns. The ratio of this analysis, only the main score will be used. The analysis will the reviews was analyzed with chi-square, while the effect size be done with a t-test, and the effect size will be calculated with was calculated with 𝜙. Cohen d statistics. The results for five genres with the highest Below are presented the results, where the p-value was lower effect size are presented below. The results were presented, only than the threshold corrected with Bonferroni correction (1 . 136−56). if the p was higher than the corrected value mentioned in the The results are also presented in a table, where for each trait, the previous section. If there were more than 3 results with p-value average power for statistically significant results is presented, as like that, only the 3 with the highest power were shown. 135 What Anime to Watch Next? Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Table 2: The summary of power results for review scores above it. With agreeableness, neuroticism, and conscientious- ness being in the middle effect size territory. The genres with trait N average highest high trait low trait the highest effect sizes for these traits reach the high effect size territory. A 23 .61509 .86056 Harem / Interestingly, that openness and extroversion have less con- E / .14158 .34974 / / nection to which genres the person likes compared to the other N 28 .71882 .83250 / Game three traits. I don’t know the reason, why this would be so. Taking the more general picture of the results, there seems to C 28 .68101 .88185 Shoujo / be some possible connection between the groups of genres and O 17 .39967 .52882 / Thriller personality. The agreeableness seems to be connected to pos- itive social relationships, and negatively connected to conflict and negative emotions. The extraversion seems to be connected 3.2.1 Agreeableness. People with higher level of agreeableness with more thrilling and positive genres along with relationship- rate higher the genres of harem ( 𝑡 = 31 . 1 , 𝑑 𝑓 = 5424 , 𝑝 = based genres, while negatively connected to plot-driven genres. . 000 ,𝑑 = . 860), shoujo ( 𝑡 = 29 . 0 ,𝑑𝑓 = 4467 , 𝑝 = . 000 ,𝑑 = . 851) Neuroticism is connected to negative themes and conflicts and and school ( 𝑡 = 53 . 1 , 𝑑 𝑓 = 19349 , 𝑝 = . 000 , 𝑑 = . 753). There less connected with positive genres. The conscientiousness was were no genres, where people with a lower level of agreeable- connected to more positive, relationship-based, and supernatu- ness would rate higher than people with a higher level of agree- ral genres. The interesting finding here was that some of the gen- ableness. res they enjoyed, they watched less of. This is unlike the finding for the former three traits. The openness also has this gap. They 3.2.2 Extroversion. There were no genres, that trait extraver- prefer to watch more ideas and plot-driven genres and less posi- sion would be connected with at the corrected p level. tive genres. But the people with a lower level of this trait seems 3.2.3 Neuroticism. There were no genres, that people with a to enjoy the genres with conflict and competition more. higher level of neuroticism would rate higher than people with The general results are more or less in line with what would a lower level of neuroticism. People with lower level of neuroti- be expected based on personality theory. Agreeableness’ con- cism rate higher the genres of game ( 𝑡 nection to empathy, extraversion’s connection to positive emo- = −20 . 2 , 𝑑 𝑓 = 2523 , 𝑝 = . tions and sensation seeking, neuroticism’s connection to nega- 000 , 𝑑 = . 832), harem ( 𝑡 = −29 . 1 , 𝑑 𝑓 = 5427 , 𝑝 = . 000 , 𝑑 = . tive emotions, and openness’ connection to the creativity can ex- 798) and vampire ( 𝑡 = −16 . 5 , 𝑑 𝑓 = 2069 , 𝑝 = . 000 , 𝑑 = . 778). plain a lot of the group genre preferences described above. Just 3.2.4 Conscientiousness. People with higher level of conscien- conscientiousness does not have a very easy explanation for it. tiousness rate higher shoujo ( 𝑡 = 29 . 1 , 𝑑 𝑓 = 4345 , 𝑝 = . 000 , 𝑑 = There are a couple of things that I could do to improve the . 881), vampire ( 𝑡 = 17 . 3 ,𝑑𝑓 = 2033 , 𝑝 = . 000 ,𝑑 = . 814) and study. One of them is shown in the one-sidedness of the results harem ( 𝑡 = 26 . 1 , 𝑑 𝑓 = 5303 , 𝑝 = . 000 , 𝑑 = . 740). There were for linking the different genres of the anime. While looking at all no genres, that people with a lower level of conscientiousness results, there are some results for low and high levels of traits, would rate higher than people with a higher level of conscien- the results are still very biased in one direction. So agreeable- tiousness. ness and conscientiousness are positively connected to liking most genres, just as openness and neuroticism are negatively 3.2.5 Openness. There are no anime genres, that people with a connected to liking most genres. One interpretation of the re- higher level of openness would rate higher. But there are genres, sults would be, that people that are higher on agreeableness and that people with a lower level of openness would rate higher. conscientiousness and lower on openness and neuroticism pre- Among these are thriller ( 𝑡 = −16 . 5 , 𝑑 𝑓 = 4565 , 𝑝 = . 000 , 𝑑 = fer anime. The other possible explanation, that I did not test, . 528) superpower ( 𝑡 = −22 . 8 ,𝑑𝑓 = 8270 , 𝑝 = . 000 ,𝑑 = . 519) would be that different personalities are connected to different and shounen ( 𝑡 = −32 . 5 , 𝑑 𝑓 = 19118 , 𝑝 = . 000 , 𝑑 = . 480). actions on the internet. In one study, the agreeableness and ex- troversion were connected with more frequent positive writing, 4 DISCUSSION conscientiousness with less frequent negative writing, and neu- One can see in the results above, that personality is connected roticism and extroversion with more frequent negative writing with both what the people are watching and how much do they [5]. And additional studies should try to separate the effect of like what they watch. But the statistical power with the former personality on writing from the results. is much smaller than with the later. So this would mean that This also leads to the second improvement. The results should that personality does show some connections with the people’s be triangulated with data from different sources or, even better, watching selection and a bit more connection to how much they with a different method. The users of one internet site are not like the genre. always representative of even the whole sub-community on the When it comes to the anime series that people watch, the ef- internet. For example, some studies show, that websites people fect sizes are small. The averages are only approaching the cut- visit are correlated with personality [8]. So the caution should off for the small effect, while the strongest are all, sans extro- be exercised in trying to generalize the results. version, in the small effect size territory. There seems to be a The third way to improve this study would be to use multi- bit higher for openness and agreeableness. But overall, none of ple ways to measure personality. In this study, the correlation them are big. So there seem to be other explanations for the selec- between LIWC categories and personality traits found in an un- tion of which show to watch, that would need to be discovered. related study was used. But the correlations might not be the On the other hand, the effect sizes for liking the genres based same if the study would be done on this dataset, so the results on their personality are bigger. While the extraversion average could be biased because of this. Confirming the personality of effect size is approaching the small effect size, the rest are all 136 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Sara Jakša a subset with questionnaires or using multiple methods would 2019. Anime Industry Report 2019 Sumamry. Re- allow for a greater show of confidence in the results. search report. The Association of Japanese Anima- In conclusion, the personality seems to have a mostly pre- tions. http://aja.gr.jp/english/japan-anime-data. dictable connection what people watch and how much they like [11] Daniel Nettle. 2009. Personality: What makes you it. With a stronger connection to the linking than general watch- the way you are. Oxford University Press, New York, ing patterns. US. ISBN: 9780199211425. [12] James W. Pennebaker and Laura A. King. 1999. Lin- REFERENCES guistic styles: language use as an individual differ- [1] B. Bazelli, A. Hindle, and E. Stroulia. 2013. On ence. Journal of Personality and Social Psychology, the personality traits of stackoverflow users. In 2013 77, 6, 1296–1312. DOI: 10.1037/0022-3514.77.6.1296. IEEE International Conference on Software Mainte- [13] Peter J. Rentfrow, Lewis R. Goldberg, and Ran Zilca. nance, 460–463. 2011. 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Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110, 15, 5802– 5805. ISSN: 0027-8424. DOI: 10.1073/pnas.1218772110. [10] Hiromichi Masuda, Tadashi Sudo, Kazuo Rikukawa, Yuji Mori, Yasuo Kameyama, and Megumi Onouchi. 137 Zaznavanje lastnosti zdravil brez recepta Perception of OTC medicine attributes Karin Kasesnik Jani Toroš Mihael Kline SPC Katedra za trženje in Oddelek za komunikologijo NIJZ management UL, FDV Ljubljana, Slovenia VŠPV Ljubljana, Slovenia karin.kasesnik@guest.arnes.si Ljubljana, Slovenia miro.kline@kline-partner.si jani.toros@imi-institute.org POVZETEK medicines. We researched a perception of the importance related to the OTC medicine attributes, included in the official Pri zdravljenju ima pomembno vlogo jemanje zdravil brez documents. Individual attributes were systematized into several recepta. Pacienti lahko dobijo informacije o teh zdravilih iz več groups. In the present extended abstract a focus is given to the virov. Poleg nasvetov strokovnjakov s področja zdravja je na perception of efficacy and possible side effects of the OTC razpolago tudi več pisnih virov. Razumevanje informacij o medicines. A conjoint method was used for analyzing the data. zdravilih vpliva na odločanje in vedenje pacientov in posredno The responders expressed the preferences toward individual na rezultate medikamentoznega zdravljenja. Raziskovali smo attributes, by answering the questions in the questionnaire. It zaznavanje pomembnosti lastnosti zdravil brez recepta, ki so was confirmed that patients ascribe a higher importance to the del uradnih dokumentov. Posamezne lastnosti smo sistematično attributes’ group, encompassing the risks, especially the serious združili v več skupin. V sedanjem razširjenem povzetku smo se ones, in comparison with the group of attributes which osredotočili na zaznavanje učinkovitosti in možnih neželenih describes the advantages of the OTC medicines. Ascribing an učinkov zdravil brez recepta. Za analizo podatkov smo importance is a part of making decisions, leading to the uporabili »conjoint« metodo. V vprašalniku so respondenti z consumer behavior. The main purpose of the research study is odgovori na vprašanja izrazili preference do posameznih determining of the importance, assigned to the individual lastnosti. Potrdili smo, da pacienti skupini lastnosti, ki opisuje attributes and the groups of the attributes of the OTC tveganja, posebej resnejša, pripisujejo primerjalno večjo medicines. On he basis of the findings regarding the attributes pomembnost kot skupini lastnosti z opisom prednosti zdravil to which the preferences and the importance are assigned, more brez recepta. Pripisovanje pomembnosti je del procesa efficient communication between the healthcare experts and the odločanja, ki vodi v nakupno vedenje. Osnovni namen patients is enabled. Several scientific publications describe the raziskave je določitev relativne pomembnosti, ki jih respondenti theories which emphasize mainly rational or mainly emotional pripisujejo posameznim lastnostim oziroma skupinam lastnosti decision-making by the patients. The response to the risk is zdravil brez recepta. Na osnovi ugotovitev, katerim lastnostim described as an emotional one. Although an assigned pacienti pripisujejo prednost oziroma pomembnost, lahko importance of the risks and other attributes of the OTC strokovnjaki s področja zdravja z njimi bolj učinkovito medicines were determined, an additional research is needed in komunicirajo. V več znanstvenih delih so opisane teorije, ki order to confirm the related response as a rational or an poudarjajo pretežno racionalno ali pretežno emocionalno emotional one. odločanje pacientov. Odziv na tveganja je opisan kot emocionalen. Čeprav smo v raziskavi ugotavljali pripisano KEYWORDS pomembnost tveganj in drugih lastnosti zdravil brez recepta, pa je potrebno nadaljnje raziskovanje, da bi potrdili odziv nanje OTC medicines, attributes, preferences, ascribing an kot racionalen ali emocionalen. importance, efficacy, risks KLJUČNE BESEDE 1 UVOD Zdravila brez recepta, lastnosti, preference, pripisovanje pomembnosti, učinkovitost, tveganja Zdravila brez recepta so pomemben del zdravljenja pacientov. Odločitev za nakup teh zdravil lahko temelji na nasvetu ABSTRACT strokovnjakov, na primer zdravnika ali farmacevta v lekarni. Informacije o zdravilu brez recepta pacient lahko pridobiva tudi Taking OTC medicines has an important role in the treatment. iz različnih pisnih virov. Poleg uradnih, odobrenih pisnih virov Patients can obtain the OTC medicines’ information from so razpoložljivi različna promocijska gradiva, s katerimi several sources. Besides the health experts’ advices also several proizvajalci nameravajo vplivati na odločanje in nakupno written sources are available. Comprehension of medicine vedenje pacientov. Za razliko od zdravil, ki se predpisujejo na information affects decision-making and patients’ behavior and recept, je dovoljena promocija oziroma oglaševanje zdravil brez indirectly influences the results of the treatment with the 138 recepta splošni javnosti, ob upoštevanju zakonskih določil. 2 RACIONALNE IN EMOCIONALNE Oglaševanje zdravil brez recepta pa mora biti skladno z določili TEORIJE O ODLOČITVAH GLEDE Pravilnika o oglaševanju zdravil [1]. Pravilnik določa, kateri podatki o zdravilu brez recepta morajo biti zajeti v ZDRAVLJENJA oglaševalskem sporočilu in katerih informacij sporočilo ne sme Medtem ko nekatere objavljene teorije pripisujejo bistveno zajemati. vlogo racionalnemu vedenju, pa druge teorije poudarjajo pomen Pomembni uradni dokumenti, ki spremljajo zdravila brez emocionalnega vedenja. Sprva so se v večji meri uveljavljale recepta, na primer navodilo za uporabo zdravila in ovojnina teorije, ki so poudarjale racionalno vedenje. Kasneje so zdravil, so v Sloveniji regulatorno urejeni. Vprašljivo pa je, ali raziskovalci spoznavali pomen čustev pri zaznavanju lastnosti je nadzor promocije zdravil brez recepta zagotovljen v zadostni izdelkov, razvoj znanstvenih metod pa je omogočil tudi boljše meri, da nima negativnega vpliva na odločanje in vedenje spremljanje odziva organizma na lastnosti izdelka. pacientov, z verjetnim vplivom na rezultate zdravljenja. Raziskovalci [4] so ugotovili, da čustveni odzivi lahko Ustrezno jemanje zdravil brez recepta je bistveno za doseganje povzročijo vedenje oseb, ki ne vodi v njihovo dobrobit. Avtorji pričakovanih rezultatov medikamentoznega zdravljenja. trdijo, da se zaradi vpliva čustev zaznavanje tveganja ne sklada Zdravila, ki se ne predpisujejo na recept, imajo prav tako kot z racionalnimi, na znanstvenih ugotovitvah temelječimi zdravila na recept pogosto močne učinke, pa tudi možne analizami. Zaradi čustvene obdelave informacij osebe neželene učinke. Določene učinkovine v zdravilih brez recepta zaznavajo negativne strani kot bolj pomembne od prednosti. V medsebojno učinkujejo z učinkovinami z zdravili na recept, ki raziskavi [4] je tudi opisano, da vedenje pod vplivom čustev jih pacienti sočasno jemljejo, pa tudi drugimi snovmi. povzroči slabše predvidevanje prihodnjih preferenc ter Raziskovalci [2] so pokazali, da trditve o učinkovitosti niso v neustrezno oceno preteklih izkušenj in dejanskega tveganja. ravnotežju s trditvami o tveganjih v promocijskih materialih, ki Večina teorij torej odločanje opredeljuje s kognitivnega opisujejo značilnosti zdravil brez recepta. Ustrezno ravnotežje vidika. Avtorji teh teorij razlagajo, da odločitve temeljijo na trditev pa je pomembno za razumevanje in odločanje pacientov. ocenah prihodnjih izidov različnih možnosti, s pomočjo vrste Dobro razumevanje informacij o zdravilih vodi v pravilno analiz, kjer se tehtajo stroški in koristi. Določene teorije jemanje in ravnanje z zdravili. Posebej na področju zdravil brez upoštevajo čustva, a le kot posledico neke odločitve in je ne recepta odločanje pacientov in njihovo razumevanje informacij povezujejo neposredno z odločitvijo. Vendar pa avtorji teorije, še ni dovolj raziskano. ki temelji tudi na fizioloških meritvah, čustvom pripisujejo V opisani raziskavi nas je posebej zanimal vidik zaznavanja večjo težo [5]. Osebe se odločajo ne le z ocenjevanjem resnosti pomembnosti posameznih lastnosti, ki se pojavljajo v uradnih izidov in verjetnosti njihovega pojava, ampak predvsem zaradi dokumentih o zdravilih brez recepta. Medtem ko se z njihove čustvene vrednosti. običajnimi raziskavami o ocenjevanju izdelkov ovrednoti V raziskavi [6] so ugotavljali, kako osebe zaznavajo celoten izdelek, pa smo v tej raziskavi ugotavljali pripisano vsebino sporočila. Ko pacienti zdravljenje zaznavajo kot pomembnost določenih lastnosti. To je bistveno tudi s tvegano, so sporočila s poudarjenim vplivom tveganj bolj praktičnega vidika komuniciranja strokovnjakov s področja učinkovita. Ko pa neko zdravstveno obravnavo osebe zaznavajo zdravja s pacienti. Če se ugotovi primerjalno velika pripisana kot varno, so sporočila s poudarjenimi prednostmi bolj pomembnost neželenih učinkov zdravil brez recepta, je učinkovita, saj osebe prednost namenijo pozitivnim koristno, da strokovnjaki naslavljajo te lastnosti tekom informacijam, pred informacijam o tveganjih. svetovanja pacientom, prav tako pa v pisnih gradivih. Raziskovalci [7] so preučevali sposobnost za odločanje Pregled literature kaže več objavljenih znanstvenih ( decision-making capacity or competence, DMC). Izhajali so iz prispevkov, ki pa se razlikujejo glede na to, ali poudarjajo vlogo že objavljenih ugotovitev ki sta jih zapisala Grisso in razuma ali čustev pri odločanju. Proces odločanja je zapleten in Applebaum [8] pri opredelitvi štirih poglavitnih dejavnikov. natančnejšo povezavo zaznavanja lastnosti z emocionalnega Razumevanje pomeni sposobnost dojemanja z zdravljenjem oziroma racionalnega vidika bi lahko ugotavljali tekom povezanih informacij. Ocenjevanje je povezano s sposobnostjo nadaljnjega raziskovanja. Joffe (2003) pa v objavljenem delu razpoznavanja posledic bolezni in koristi zdravljenja. (3) poroča o čustveni vsebini odziva na tveganja, vključno z Presojanje pomeni sposobnost racionalne obdelave informacij, zdravstvenimi tveganji. tudi pri primerjavi tveganj in koristi zdravljenja. Dokazovanje Osnovni raziskovalni problem je bil, da zaznavanje pa se povezuje s sposobnostjo za komuniciranje. Hermann idr. posameznih lastnosti zdravil brez recepta ni dovolj raziskano, [7] pa so poudarili tudi pomen čustev in vrednote v procesu čeprav vpliva na vedenje pacientov in lahko posredno vpliva na odločanja o zdravju. izide zdravljenja. Rezultati ugotovitev lahko pripomorejo pri Hermann idr. [7] so prikazali drugačen vidik vloge čustev, komuniciranju strokovnjakov s področja zdravja s splošno posebej bolj intenzivnega čustvenega odziva oziroma javnostjo. Zavedanje o čustvenih in racionalnih vidikih neustrezne čustvene reakcije. Raziskovalci soglašajo s trditvijo, zaznavanja lastnosti zdravil in poznavanje pripisane da je pri odločanju prevladujoč proces čustvovanja. pomembnosti posameznih lastnosti zdravil brez recepta bi Posamezniki morajo upoštevati čustva, jih priznavati kot pripomoglo k učinkovitemu komuniciranja in posredno k pomembne informacije, jih povezovati s preteklimi izkušnjami uspešnosti zdravljenja. in opredeliti, ali bo vedenje na osnovi takih izkušenj v Hipoteza: Neželenim učinkom zdravil brez recepta se prihodnje omogočalo dobro počutje. Če pa je čustven odziv pripisuje večja relativna pomembnost kot prednostim zdravil. intenziven, se zmanjša zmožnost za razumevanje in Resnejši neželeni učinki se v primerjavi z drugimi neželenimi posvetovanje. Sposobnost za odločanje je povezano s primerno učinki zaznavajo kot bolj tvegani. 139 stopnjo vključitve čustev. Pomanjkanje ali presežek čustev pa telesne temperature, ki sta simptoma bakterijskega ali virusnega predstavlja težavo. obolenja ali drugih bolezni. Drugo zdravilo brez recepta pa Raziskovalci upoštevajo različne nevrološke mehanizme v vsebuje tri učinkovine, to so paracetamol, psevdoefedrinijev organizmu, ki vplivajo na čustvene oziroma racionalne procese hidroklorid in dekstrometorfan hidrobromid. To zdravilo ima ter sodelujejo pri odločanju o zdravju oziroma zdravilih. Prav širše indikacijsko območje od prvega, poleg znižanja povišane tako pripisujejo različen pomen in vpliv racionalnih oziroma telesne in lajšanja bolečin izboljša simptomov bakterijske ali emocionalnih procesov na odločanje. Iz določenih raziskav [3, virusne infekcije v nosu ter za olajša kašelj. 4] je razvidno, da se odločanje o tveganjih v večji meri V navodilih za uporabo smo kodirali trditve, ki smo jih povezuje z emocionalnimi procesi. umestili v tri skupine lastnosti. Skupina lastnosti, ki opisuje učinkovitost zdravljenja. zajema tri nivoje lastnosti in sicer 3 ZASNOVA IN METODA RAZISKAVE O olajšanje bolečine, lajšanje dihanja in zamašenega nosu ter lajšanje kašlja. Druga skupina lastnosti prav tako zajema ZAZNAVANJU LASTNOSTI ZDRAVIL prednosti zdravljenja, poleg znižanja povišane telesne BREZ RECEPTA temperature tudi dve lastnosti, ki sta povezani s komplianco zdravil: zdravila se zlahka zaužijejo in enkrat dnevno 3.1 Izhodišča odmerjanje. V skupini lastnosti, ki zajema možne neželene Odločanje pacientov o medikamentoznem zdravljenju je učinke, je prva lastnost izpuščaj, srbenje in omotičnost. Druga področje, ki je še premalo raziskano. Ne le pravilna struktura lastnost so težave s srcem, tretja pa težave z dihanjem. besedila o zdravju in zdravilih, ampak tudi ustrezno Naslednja skupina lastnosti vključuje tri nivoje cene, ki razumevanje teh informacij pomembno prispeva k temeljijo na realnih cenah izbranih zdravil. pričakovanim rezultatom zdravljenja. V tej raziskavi smo preučevali preference respondentov o lastnostih zdravil brez recepta. Skupine lastnosti so bile 4 POGLAVITNI REZULTATI RAZISKAVE povezane s prednostmi zdravila, neželenimi učinki in ceno Z analizo smo dobili več rezultatov. S pomočjo računalniškega zdravil. Določili smo, katerim lastnostim so respondenti programa smo določili pogostnost izbire posameznih lastnosti pripisali največjo pomembnost – učinkovitosti, komplianci, in pomembnost, ki so jo respondenti pripisali lastnostim neželenim učinkom oziroma ceni. oziroma skupinam lastnosti. 3.2 Conjoint analiza 4.1 Izbira lastnosti Conjoint analiza je sodobna metoda z zanesljivimi rezultati. S Sprva smo določili delež izbire posamezne lastnosti s strani conjoint analizo raziskovalci ugotavljajo odločanje respondentov. V skupini z učinkovitostjo zdravila brez recepta respondentov. V vprašalniku so navedeni različni scenariji, na so respondenti v povprečju največkrat (v 22 %) izbrali olajšanje osnovi katerih respondenti tehtajo med posameznimi nivoji bolečine in lajšanje dihanje pri zamašenem nosu [10]. To lastnosti glede na preference. Respondenti z odgovori pomeni, da so izmed vseh prikazov tega nivoja lastnosti ovrednotijo različne značilnosti oziroma lastnosti izdelka po respondenti ti dve lastnosti izbrali v 22 % primerov. V manjši pripisani pomembnosti. V vedno večji meri se ta metoda meri so respondenti izbrali olajšanje kašlja. V drugi skupini uporablja na področju raziskovanja informacij o zdravilih. lastnosti je bila lastnost, ki opisuje znižanje povišane telesne Conjoint analiza je vrsta evalvacije, pri kateri se uporablja temperature, izbrana v 25 % primerov, kar je presegalo izbiro vprašalnik, da bi določili tehtanje med lastnostmi in nivoji lastnosti, ki so se povezovale s komplianco. Hi-kvadrat lastnosti in ugotovili preference pacientov za določene izdelke statistična analiza je pokazala, da je razlika med posameznimi oziroma lastnosti izdelkov [9]. Tekom odgovarjanja na lastnostmi v prvi in drugi skupini lastnosti signifikantna. vprašanja se respondentu prikažejo različne kombinacije V skupini lastnosti z možnimi neželenimi učinki je bila vprašanj z lastnostmi, med katerimi izbira. Računalniška lastnost, ki opisuje izpuščaj, srbečico in omotičnost, izbrana v obdelava podatkov omogoča določitev preferenc in določitev 35 % in so jo v povprečju torej respondenti zaznali kot manj zaznane pomembnosti lastnosti izdelka. tvegano kot težave z dihanjem, ki so jih respondenti izbrali v 17 % in težave s srcem, ki so jih respondenti izbrali le v 7 %. 3.3 Razlika med izbirami posameznih lastnosti v tej skupini je bila Izvedba raziskave prav tako statistično pomembna. V četrti skupini s ceno kot V raziskavo je bilo vključenih 85 respondentov. 68 žensk in 17 lastnostjo je bila pričakovano največkrat izbrana najnižja cena moških. Starostna struktura respondentov kaže, da je bilo 40,0 (4,5 EUR), v 22 %. V manjšem deležu (20 %) je bila izbrana % respondentov mlajših od 30 let, 38,8 % starejših od 50 let, cena 6,5 EUR, v najmanjšem deležu (18 %) pa je bila izbrana 21,2 % oseb pa je imelo med 30 in 50 let. cena 8,5 EUR. Izbrali smo navodili za uporabo dveh zdravil brez recepta, ki sta na slovenskem tržišču. Navodila za uporabo zdravil brez 4.2 Zaznana pomembnost lastnosti recepta so uradni dokument, ki jih odobri JAZMP (Javna Ugotavljali smo tudi pomembnost, ki so jo respondenti pripisali agencija Republike Slovenije za zdravila in medicinske posameznim skupinam lastnosti. Primerjalno največjo pripomočke). Učinkovina v enem izmed zdravil je paracetamol. pomembnost so respondenti pripisali skupini lastnosti o možnih Zdravilo se uporablja za lajšanje bolečine in znižanje povišane neželenih učinkih, ki je po pomembnosti presegala pripisano 140 pomembnost obeh skupin lastnosti, povezanih s prednostmi Osnovna ugotovitev naše raziskave je, da je bila skupini zdravila, torej učinkovitosti in komplianci zdravil. Primerjalno lastnosti, ki se povezujejo z neželenimi učinki, pripisana večja najmanjšo pomembnost so respondenti pripisali ceni. pomembnost kot skupini lastnosti, ki opisujejo prednosti zdravil brez recepta, to je učinkovitost in dobro komplianco teh zdravil. Kot posebej tvegane so respondenti zaznavali resnejše neželene Tabela 1: Povprečna pripisana pomembnost skupin učinke. Ceni zdravil pa, nasprotno s pričakovanji, respondenti lastnosti niso pripisali velike pomembnosti, morda tudi zaradi razmeroma majhne razlike med cenovnimi nivoji in razmeroma Št. skupine Skupina lastnosti Pripisana majhnega stroška. lastnosti pomembnost Na osnovi rezultatov naše raziskave zaključujemo, da bi lastnosti (%) bilo v ustni in pisni komunikaciji s pacienti koristno naslavljati 1 Prednost: učinkovitost 14,61 neželene učinke zdravil brez recepta in ovrednotiti in zdravila racionalizirati njihovo dejansko tveganje, posebej glede na 2 Prednost: komplianca, 17,12 prednosti jemanja zdravil brez recepta. učinkovitost Ne glede na objavljene teorije o prevladujočem racionalnem 3 Možni neželeni učinki 59,05 ali emocionalnem odločanju velja, da na odločanje vplivajo 4 Cena 9,22 racionalni in emocionalni mehanizmi. Natančnejša določitev Skupaj 100,0 emocionalnega ali racionalnega vidika pripisane pomembnosti lastnosti pa bi bila izvedljiva tekom nadaljnjega raziskovanja. V V raziskavi smo pridobili in analizirali še druge rezultate, ki tej fazi raziskovanja le predvidevamo, da se možna tveganja bodo predvidoma v prihodnje objavljeni. Poleg navedenih zaradi jemanja zdravil brez recepta v večji meri povezujejo z lastnosti smo ugotavljali tudi preference z ozirom na posamezne vplivom čustev, tudi na osnovi ugotovitev predhodnega blagovne znamke oziroma lastniška imena zdravil brez recepta, raziskovanja [3, 4]. Odločanje pa je celovit proces, na katerega tudi na večjem vzorcu respondentov. učinkuje več dejavnikov in koristilo bi nadaljnje raziskovanje. LITERATURA 5 RAZPRAVA IN ZAKLJUČEK [1] Pravilnik o oglaševanju zdravil. Uradni list RS, št. 105/08, 98/09 – Izhajali smo iz trditve, da neželenim učinkom respondenti ZMedPri, 105/10 in 17/14 – Zzdr-2. DOI: http://www.pisrs.si/Pis.web/pregledPredpisa?id=PRAV3390. pripisujejo večjo pomembnost kot učinkovitosti, Kot posebej [2] Karin Kasesnik, Mihael Kline, Todd Gammie in Zaheer-Ud-Din Babar, tvegani se zaznavajo resni neželeni učinki. Rezultati raziskave 2016. Analyzing medicines information of over-the-counter medicines postavljeni hipotezi pritrjujejo. Predvidevali smo, da bodo ceni leaflets in Slovenia. Akademija MM (dec, 2016), 13 (26), 9-22. DOI: respondenti pripisali večjo pomembnost, kar pa rezultati https://assets.website- files.com/5bd6cecc10ba2a724f7b2f22/5ce3cc1fc86d1b6c6fc9d268_26.% raziskave [10] niso potrdili. 20Akademija%20MM.pdf. V sorodni raziskavi [11] so raziskovali preference o [3] Hélène Joffe, 2003. Risk: From perception to social representation. lastnostih zdravil brez recepta, predvsem za lajšanje bolečin. British Journal of Social Psychology (Apr 2003), 42 (1), 55-73. Ugotovili so, da sta cena in blagovna znamka najpomembnejši [4] Donald A. Redelmeier, Paul Rozin, Daniel Kahneman, 1993. lastnosti pri izbiri zdravila brez recepta. Ti rezultati se ne Understanding Patients’ Decisions. Cognitive and Emotional Perspectives. JAMA (jul, 2016), 270 (1), 72-76. DOI: skladajo z našimi rezultati, kjer ceni respondenti niso https://jamanetwork.com/journals/jama/article-abstract/407158. pripisovali velike pomembnosti. Vendar so Halme idr. [11] [5] Antoine Bechara, Hanna Damasio in Antonio R. Damasio, 2000. ugotovili razlike med respondenti glede njihovih preferenc za Emotion, Decision Making and the Orbitofrontal Cortex. Cerebral lastnosti zdravil brez recepta in jih na osnovi tega razvrstili v Cortex (mar, 2000) , Vol. 10 (3), 295-307. DOI: https://academic.oup.com/cercor/article/10/3/295/449599. pet skupin. Glede na to razvrstitev so določili, katera skupina [6] Alan Schwartz, Julie Goldberg in Gordon Hazen, 2008. Prospect theory, respondentov ceni pripisuje večjo pomembnost. V skupine so reference points, and health decisions. Judgement and Decision Making respondente razvrstili glede na to, ali upoštevajo predvsem (Feb, 2008), 3 (2), 174-180. DOI: http://journal.sjdm.org/jdm7823.pdf. učinkovitost, primerjalno nižjo ceno, blagovno znamko, ali pa [7] Helena Hermann, Manuel Trachesel, Bernice S. Elger in Nikola Biller- Andorno, 2016. Emotion and Value in the Evaluation of medical uravnotežene lastnosti; slednji skupini respondentov so Decision-Making Capacity: A Narative Review of Arguments. Front raziskovalci pripisali racionalno odločanje. V peto skupino so Psychol. (maj, 2016), 7, 765. DOI: raziskovalci uvrstili respondente, ki v veliki meri upoštevajo https://www.frontiersin.org/articles/10.3389/fpsyg.2016.00765/full. nasvet strokovnjaka, zdravnika ali farmacevta. [8] Thomas Grisso in Paul S. Applebaum. 1998. Assessing Competence to V isti raziskavi [11] so avtorji ugotovili večjo pripisano Consent to Treatment; A Guide for Physicians and Other health professiomnals. New York, NY: Oxford University Press. DOI: pomembnost lastnosti, ki se navezujejo na učinkovitost zdravil https://escholarship.umassmed.edu/psych_pp/314/. brez recepta (25 %) kot pri naši raziskavi, kjer je bila nekoliko [9] Deborah Marshall, John F.P. Bridges, Brett Hauber, Ruthanne Cameron, manjša kot 15 %. Vendar pa se je izbor lastnosti med Lauren Donnalley, Ken Fyie in F. Reed Johnson, 2010. Conjoint raziskavama razlikoval. Analysis Applications in Health – How are Studies being Designed and Reported? An Update on Current Practice in the Published Literature Guo idr. [12] so raziskovali preference in pripisano between 2005 and 2008. Patient (dec, 2010), 3 (4), 249-256. DOI: pomembnost izbranih lastnosti zdravil in ugotovili, da osebe https://pubmed.ncbi.nlm.nih.gov/22273432/. niso naklonjene neželenim učinkom, kar posebej velja za [10] Karin Kasesnik, Mihael Kline in Jani Toroš, 2020. Analysis of resnejše neželene učinke. Ti rezultati se skladajo z rezultati naše Medicines Attributes within Patient Infrormation Leaflets. V: Weis, Lidija (ur.), Koval, Viktor (ur.), As kerc Veniger, Katarina (ur.). raziskave Eastern European Conference of Management and Economics: 141 Environmental management and sustainable economic development: EECME 2020: proceedings of the 2nd international scientific conference: May 29, 2020, Ljubljana, Slovenia. Ljubljana: Ljubljana School of Business, 2020, 9-15. DOI: https://www.researchgate.net/profile/Mykola_Mykolaichuk/public ation342317836_Support_for_innovative_economic_development_by _the_banking_sector_challenges_for_Ukraine/links/5eed14b8a6fdcc 73be8d76ba/Support-for-innovative-economic-development-by- the-banking-sector-challenges-for-Ukraine.pdf. [11] Merja Halme, Kari Linden in Kimmo Ka a ria , 2009. Patients’ Preferences for Generic and Branded Over-the-Counter Medicines. An adaptive Conjoint Analysis Approach. Patient (dec, 2009), 2 (4), 243-255. DOI: https://pubmed.ncbi.nlm.nih.gov/22273245/. [12] Na Guo, Carlo A. Marra, J. Mark FitzGerald, R. Kevin Elwood, Aslam H. Anis, Fawziah Marra, 2011. Patient Preference for Latent Tuberculosis Infection Prevention Treatment: a Discrete Choice Experiment. Value in Health (Sept-Oct 2011), 14 (6), 937-943. DOI:https://www.sciencedirect.com/science/article/pii/S1098301511014 197. 142 Kognitivno–motivacijski model čustvovanja v vsakdanjem življenju Cognitive–motivational Model of Emotions in Everyday's Life Darja Kobal Grum Oddelek za psihologijo Filozofska fakulteta, Univerza v Ljubljani Aškerčeva 2, 1000 Ljubljana +38612411151 darja.kobal@ff.uni-lj.si POVZETEK druga modificirana in vprašanje je, kaj je pravo čustvo, ki ga posameznik doživlja. Tretji dejavnik je v besednjaku, kako V prispevku se ukvarjamo z vprašanjema, kaj so čustva in kakšna je vloga čustev pri našem vsakdanjem funkcioniranju. Pri tem nas opredeliti oz. s katerimi besedami opisati ustrezna čustva. Različne študije so poskušale prebroditi to vrzel s ti. vpeljavo »sodnikov«, zanima, katere psihološke entitete sodelujejo pri čustvovanju in pripomorejo k učinkovitemu in pozitivnemu delovanju. Postavimo največkrat študentov, ki so iskali najrazličnejše besede za hipotetični kognitivno–motivacijski model čustvovanja v opisovanje določenih čustev in skušali oblikovati nekakšen slovar vsakdanjem življenju, ki predstavlja podlago za empirično čustev. Nobena klasifikacija se ni izkazala za bolj objektivno od druge. Četrti razlog je v različnih teoretskih pristopih, ki so se raziskovanje tistih vidikov čustvovanja, ki pripomorejo k oblikovali skozi zgodovino psihologije, peti pa v nas samih, ki smo pozitivnemu vsakdanjemu delovanju. se s pomočjo vzgoje in težnje k prilagajanju okolju naučili KLJUČNE BESEDE potvarjati svoja čustva. Čeprav smo npr. žalostni, si v družbi »nadenemo« nasmeh, čeprav smo na nekoga jezni, zaradi Čustva, kognicija, motivacija, cilj, hipotetični model. neprimernosti izražanja jeze tej osebi, tega čustva ne izrazimo itd. [2]. ABSTRACT Čustva opredelimo kot duševne procese in stanja, ki izražajo In this article, we deal with the question of what emotions are and človekov vrednostni odnos do zunanjega sveta ali do samega sebe what the role of emotions is in our daily activities. In doing so, we [3]. Posameznik spozna osebe, dogodke in situacije ter jih s čustvi are interested in which psychological entities are involved in our ovrednoti, tako da jim subjektivno določi njihovo vrednost [3]. emotions and contribute to effective and positive functioning. We Čustva so torej kratkotrajni subjektivni, duševni, funkcionalni in set up a hypothetical cognitive–motivational model of emotion in ekspresivni pojavi, ki usmerjajo naše vedenje v smeri prilagajanja everyday life, which represents the basis for empirical research of ali neprilagajanja danim okoliščinam [3, 4]. To pomeni, da so those aspects of emotion that contribute to positive everyday čustva evalvacije in se pojavljajo ob objektih, ki so za posameznika functioning. pomembni [4]. Funkcionalno imajo čustva adaptacijsko funkcijo, kar pomeni, da omogočajo učinkovito prilagajanje okolju, delujejo KEYWORDS kot motivi, saj nas usmerjajo k objektom in situacijam, ki sprožajo Emotions, cognition, motivation, goal, hypothetical model pozitivna čustva, pomembno vlogo pa imajo tudi pri komunikaciji in uravnavanju socialnih odnosov [3]. Tudi na področju motivacije je razlag veliko, vendar se skladajo 1 UVOD v opredelitvi, da je motivacija: občutena napetost, ki je usmerjena k ali proti nekemu cilju; notranji proces, ki vpliva na smer, V literaturi obstajajo številne opredelitve čustev. Kompleksnost vztrajnost in intenzivnost k cilju usmerjenega vedenja; specifična njihovega definiranja ponazarjajo najrazličnejši poskusi potreba, želja ali hotenje, ki spodbudi k cilju usmerjeno vedenje [5]. kategoriziranja različnih opredelitev, med katerimi naj omenimo le Motivacija je torej psihološki proces, ki spodbuja in usmerja naše poskus Paula R. Kleinginna in Anne M. Kleinginna [1], v katerem vedenje [6]. sta avtorja zbrala več kot 100 različnih definicij čustev in jih Kognicija je izraz, ki se je v psihologiji pojavil razmeroma pozno, klasificirala v 6 kategorij. To so definicije, ki poudarjajo: fiziološke in sicer v 50. letih prejšnjega stoletja [7]. V nadaljnjih desetletjih vidike čustev, motivacijo in vedenje, funkcije čustev, razlikovanje pa je raziskovanje kognicije dobilo naslutene razsežnosti, še zlasti med drugimi pojavi čustvovanja, kot npr. razpoloženje, preference, s pomočjo spoznanj iz nevropsihologije, kar so omogočile tudi strast oz. hrepenenje, afekt itd., psihopatološke oblike čustvovanja kompleksne nevropsihološke tehnologije [4]. Kognitivni procesi so ter različne klasifikacije, kot so npr. pozitivne nasproti negativnim psihološki procesi, ki nam omogočajo odnos z okoljem, z njimi čustvom, ciljno skladne nasproti ciljno neskladnim ipd. sprejemamo in predelujemo informacije, ki jih pridobimo s Plutchik [2] opozarja, da je zmeda na področju definiranja čustev pomočjo različnih izvorov, kot npr. z zaznavo, izkušnjami, posledica več dejavnikov. Prvi je v močni prevladi behaviorizma, prepričanji ipd., nato pa jih pretvorimo v znanje. Kognitivni procesi ki je dominiral tja do 60. let prejšnjega stoletja in čustva niso bila so: občutenje, zaznavanje, učenje, spomin, mišljenje, jezik, govor predmet obravnave. Drugi je v psihoanalizi, ki je pokazala, da in zavest [4]. subjektivni opisi čustev niso nujno relevantni oz. da to, kar človek opisuje, da doživlja, ni nujno res. Nekatera čustva so potlačena, 143 V prispevku nas zanimata vlogi motivacije in kognicije pri našem pričakovanje. Pri samoodgovornosti ocenjujemo, koliko smo sami čustvovanju. Pri tem izhajamo iz Reevovega [8] razumevanja odgovorni za nastalo situacijo, pri osredotočenosti na problem povezanosti med čustvi, kognicijo in motivacijo, ki čustva in ocenjujemo, koliko lahko dano situacijo izboljšamo, ko smo kognicijo razlaga kot sestavna člena motivacije, v čustvih samih pa osredotočeni na čustva, ocenjujemo, koliko se lahko sami vidi indikator prilagojenosti vedenja. Veselje npr. kaže na socialno prilagodimo na nastalo situacijo, torej ali lahko spremenimo odnos vključenost in težnjo po doseganju ciljev, žalost pa, nasprotno, do nastale situacije, pričakovanje pa zajema oceno, ali lahko v napotuje na socialno izolacijo in odmik od ciljev. Pozitivna čustva prihodnje sami prispevamo k spremembi situacije. Vsakemu čustvu odsevajo angažiranost in zadovoljstvo z našim delovanjem in odgovarja specifična sekundarna ocena, ki jo Lazarus [9] motivacijskimi stanji, negativna pa opustitev in frustracijo v zvezi metateoretično imenuje ključne teme, povezane z dogodkom Gre z našim delovanjem in motivacijskimi stanji. Pozitivna čustva za tipične vsakdanje situacije, ki jih ocenjujemo glede na tipične odsevajo našo uspešno prilagojenost danim okoliščinam, negativna hevristične kognitivne sheme. Vsaka od teh situacij je podvržena pa kažejo, da se nanje nismo znali učinkovito prilagoditi. S te najprej primarnim, nato pa še sekundarnim procesom ocene, kar perspektive čustva nimajo enakega statusa v motivaciji kot potrebe posledično vodi do specifičnega tipičnega čustva. Tako naj bi in kognicije, ampak odločajo o tem, ali bo nek motiv sploh neugodne situacije odgovarjale ocenam ciljne pomembnosti, a zadovoljen ali ne [8]. Pozitivna čustva torej spodbujajo hkrati neskladnosti, ocene razpoložljivosti notranjih virov za zadovoljitev motiva, negativna pa ga preprečujejo. spoprijemanje s situacijo pa naj bi bile nizke. In obratno, pozitivne situacije naj bi se skladale z ocenami, ki so ciljno pomembne in skladne, zajemale pa naj bi tudi visoko vrednotenje razpoložljivih 2 KOGNITIVNE IN MOTIVACIJSKE notranjih virov oz. spoprijemalnih strategij [9]. RAZSEŽNOSTI ČUSTEV Sledi še proces terciarne ocene, ki ga Lazarus [9] imenuje ponovna ocena. Z njo presojamo pomen sekundarne ocene, pri Pri razlagi kognitivnih vidikov čustev nam je v pomoč ena od čemer se skušamo psihološko spoprijemati s psihičnim in fizičnim vodilnih kognitivnih teorij čustev ameriškega psihologa Richarda stanjem napetosti zaradi nastale situacije. V ponovni oceni Lazarusa [9], ki predpostavlja dvoje: angažiramo vse svoje notranje vire, ki nam pomagajo k blaženju a) čustva nastanejo kot posledica kognitivne ocene dražljaja oz. nastale napetosti ali pa celo omogočiti občutek ugodja in pozitivnih situacije čustev [9]. b) mediator med dražljajem in nastankom čustva je nezavedna avtomatična ocena Lazarus [9] razlikuje med znanjem in oceno. Znanje naj bi bilo 3 HIPOTETIČNI MODEL ČUSTVOVANJA V pogoj za oceno, saj ocena vedno vključuje subjektivno doživljanje VSAKDANJEM ŽIVLJENJU in pomeni osebno mnenje, ki je osnovano na ustreznem znanju. Znanje je torej nujen, a ne zadosten pogoj za nastanek čustva. Na osnovi zapisanega postavljamo hipotetični model čustvovanja v Ocena je lahko nezavedna ali zavestna, a svojo teorijo gradi iz vsakdanjem življenju, ki nam pomaga razumeti, katere psihične pomena zavestne ocene. Ocena je torej kognicija, na osnovi katere komponente in kako so vključene v naše vsakdanje funkcioniranje nastanejo čustva. Vsaka taka ocena je subjektivna in hevristična. in vodijo do bolj ali manj optimalnega delovanja. Za preverbo tega Brez kognicije ni čustva. Smith in Lazarus [10] prepoznavata dva modela postavljamo naslednjo hipotezo: tipa kognitivnih procesov, ki so povezani z nastajanjem čustev H1: Kognitivna skladnost med oceno cilja in oceno situacije a) procesi primarne ocene in ojača ciljno skladna čustva, izpolnjenost temeljnih potreb se zviša, b) procesi sekundarne ocene posledica je rast pozitivih vidikov jaza, kognitivna neskladnost med Procesi primarne ocene so tisti, s pomočjo katerih vrednotimo omenjenima ciljema vodi stran od cilja, negativna čustva se naravo situacije, v katero smo vključeni, pri čemer je ocena ojačajo, izpolnjenost temeljnih potreb se zniža, posledica je stres, situacije vedno anticipirana v oceni cilja. Procesi primarne ocene lahko pa tudi psihopatologija. so trije: - motivacijski pomen cilja Rast pozitivnih vidikov jaza - motivacijska skladnost s ciljem - samovključenost ali motivacija za oceno Motivacijski pomen in motivacijska skladnost sta po Lazarusu [9] primarni oceni, ki sta predstavljata temelj za razvoj visokega Ciljno Kognicija Cilj Avtonomnost psihičnega blagostanja, ki se kaže v tretjem primarnem procesu skladna j Kompetentnost ocene, to je v lastnem angažmaju za dosego cilja. Motivacijski čustva pomen je stopnja pomembnosti situacije za posameznika glede na Povezanost osebne cilje, motivacijska skladnost se nanaša na to, ali je situacija taka, da spodbuja ali zavira doseganje osebnih ciljev. Če je situacija Motivacija konstruirana kot motivacijsko pomembna, bo ocena situacije kot Ciljno motivacijsko skladne ali neskladne determinirala celotno valenco neskladna čustvene izkušnje [9]. čustva Če je primarna ocena podlaga za nastanek valence čustva in torej Neavtonomnost Neskladnost Nepovezanost odloča o tem, ali bosta za nas neka situacija in cilj prijetna ali ne, pa procesi sekundarne ocene sodelujejo pri specifični izraznosti čustva, se pravi, odločajo o tem, katero čustvo bomo doživeli in izrazili. Nanašajo se na procese kontrole nad situacijo in iskanje Stres lastnih virov za spoprijemanje z nastalo situacijo, če jo ocenimo kot pomembno. Gre za štiri sekundarne ocene: samoodgovornost, Slika 1: Kognitivno–motivacijski model čustvovanja v osredotočenost na problem, osredotočenost na čustva in vsakdanjem življenju 144 tako zagotovi preživetje. Kaj pa druga čustva? Za veselje npr. ni Lazarus [9] razlikuje čustva glede na skladnost ali neskladnost s nobenega dvoma: kot pozitivno in s ciljem skladno čustvo nas bo cilji: ciljno skladna čustva nas vodijo k cilju, ciljno neskladna pa usmerjalo k cilju, zato se bomo doživljali kompetentnejše in nas od njega odvračajo, čeprav si ga želimo doseči. Avtorjeva [9] učinkovitejše. Drugače pa je z jezo in gnusom. Jeza in njen perspektiva se v tej točki močno sklada z različnimi teorijami vedenjski korelat agresivnost nista skladna s ciljem, saj nas tako motivacije, še posebej z motivacijsko teorijo postavljanja ciljev doživljanje kot izražanje jeze vodita stran od želenega cilja [9, 12]. [11], ki opozarja na pomen ciljne motivacije pri našem mišljenju in Z jezo in agresivnostjo, ki jo usmerjamo navzven (ali navznoter), vedenju. Robert Franken [12] v knjigi Human motivation tvegamo, da cilja ne bomo dosegli, posledično pa se bomo počutili poglobljeno razlaga hedonizem, srečo, upanje, optimizem nekompetentne in nesposobne spoprijemanja s težavami [9, 12]. Pri pripadnost, navezanost in komunost, ki jih umešča med ciljno gnusu pa je bolj kompleksno. Gnus, ki ga doživljamo ob pogledu skladna čustva, ter strah, anksioznost, pesimizem, depresivnost, na npr. pokvarjeno hrano, nam pomaga, da se te hrane niti ne krivdo in sram, ki sodijo pod ciljno neskladna čustva. S cilji skladna dotaknemo niti je ne pojemo, torej se od cilja odmaknemo, to pa čustva nam pomagajo, da želene cilje dosežemo, naš občutek nam omogoči preživetje, naš občutek kompetentnosti pa se poveča splošne življenjske kompetentnosti se poveča. Če pa so čustva [16]. Če pa se nam npr. gnusi dotik osebe z nenalezljivo kožno neskladna s cilji, teh ciljev kljub želji, da bi jih dosegli, ne boleznijo in se tako cilju (osebi) izognemo, tvegamo izgubo dosežemo in naš občutek kompetentnosti se zniža. morebitnega kakovostnega medosebnega odnosa s to osebo, ki je V modelu predpostavljamo, da čustva omogočajo doseganje ali zaradi kožne bolezni ne pripustimo k sebi, pa čeprav ni nalezljiva odvračanje od cilja, pri čemer je bistvena ocena cilja. Če ocenimo, [16]. Posledično se naš občutek socialne kompetentnosti zniža, da je cilj za nas pomemben, se bo ojačala motivacija za doseganje naše nezadovoljstvo s samim seboj pa zviša. cilja. Pri tem se bodo pojavljala čustva, ki so skladna s tem ciljem, se pravi, ki nas vodijo k njegovemu doseganju. To so npr. veselje, ponos, optimizem ipd. Nastalo situacijo bomo doživljali kot 4 ZAKLJUČEK prijetno. Naše temeljne potrebe, kot so: potreba po avtonomnosti, Predlagani model čustvovanja, ki ga razlagamo z vidika potreba po kompetentnosti in potreba po povezanosti [13, 14] bodo v tem primeru zadovoljene in posledično bomo občutili psihično kognitivno-motivacijskih razsežnosti, je hipotetični prikaz gradbenih prvin in njihovega delovanja. Namen modela ni v zadovoljstvo in pozitivi vidika jaza se bodo krepili. Potreba po vključitvi vseh psiholoških razsežnosti, saj je to nemogoče, temveč avtonomnosti se kaže v težnji po usmerjanju lastnega vedenja s strani lastnih želja, izbir, ciljev in odločitev. Če je potreba po predvsem tistih, ki prispevajo v smeri rasti pozitivih komponent jaza bodisi v smeri doživljanja stresa in pojavljanja morebitnih avtonomnosti zadovoljena, doživljamo naše vedenje in posledice psihopatoloških pojavov. V nadaljevanju bo smiselno model tudi vedenja kot izbire, ki smo jih povzročili sami in nad katerimi drugi empirično preveriti, z namenom ugotoviti psihološke napovednike nimajo vpliva. Nasprotno pa se nezadovoljenost potrebe po optimalnega delovanja v vsakdanjem življenju. avtonomnosti kaže v nesamostojnosti in odvisnosti pri odločanju ter doživljanju zunanje kontrole nad našim mišljenjem, čustvovanjem in vedenjem [13]. Potreba po kompetentnosti se OPOMBA AVTORICE izraža kot težnja po učinkovitem delovanju na najrazličnejših življenjskih področjih, ki ga realiziramo v skladu s svojimi Prispevek je nastal v okviru raziskovalnega programa P5-0110, ki zmožnostmi in sposobnostmi. Ta potreba je zadovoljena, kadar v ga je financirala Javna agencija za raziskovalno dejavnost svojem okolju uspemo poiskati ustrezne izzive, s pomočjo katerih Republike Slovenije iz državnega proračuna. realiziramo razvoj svojih sposobnosti in učinkovitega funkcioniranja. Če pa izzive ocenjujemo kot preveč enostavne ali preveč zahtevne, se na ravni kompetentnosti ta potreba izkazuje kot LITERATURA nizko zadovoljena ali pa celo nezadovoljena. Potreba po [1] Paul R. Kleinginna in Anne M. Kleinginna, 1981. A categorized list of kompetentnosti se povezuje z občutkoma samoučinkovitosti in emotion definitions with suggestions for a consensual definition. Motivation samozaupanja, kar posledično vodi do visokega samospoštovanja and Emotion, 5, 345-379. [2] Robert Plutchik, 2000. Emotions in the Practice of Psychotherapy: Clinical in psihičnega blagostanja [13, 14]. Potreba po povezanosti oz. Implications of Affect Theories. American Psychological pripadnosti pa se kaže kot težnja po izražanje naklonjenosti, Association. https://doi.org/10.1037/10366-000 [3] Carroll E. Izard, 2010. The many meanings/aspects of emotion: Definitions, sprejemanje, zaupanje v druge [13, 14]. functions, activation, and regulation. Emotion Review, 2(4), 363–370. 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Contemporary Cognitive Sciences, 17(8), 367–368. https://doi-org.nukweb.nuk.uni- Educational Psychology, 25, 54 – 67. lj.si/10.1016/j.tics.2013.06.001 146 Motor learning and cortical plasticity: TMS motor mapping using the pseudorandom walk method Eva Koderman Jos van der Geest, Carolin Gaiser Maarten Frens Department of Neuroscience Department of Neuroscience Department of Neuroscience Erasmus University Rotterdam – Erasmus University Rotterdam – Erasmus University Rotterdam – Erasmus MC Rotterdam Erasmus MC Rotterdam Erasmus MC Rotterdam Netherlands Netherlands Netherlands koderman.eva@gmail.com j.vandergeest@erasmusmc.nl m.frens@erasmusmc.nl c.gaiser@erasmusmc.nl ABSTRACT multiple joint movements could help improve design of therapies. Motor recovery after stroke relies on the ability of the primary M1 plays a key role in the control of movement. Movement motor cortex (M1) to functionally reorganize and adapt the research has recently shifted from the traditional view that M1 existing muscle synergies. M1 reorganization can be measured controls limb muscles individually, towards the postulate that by mapping the cortical muscle representations using M1 controls limbs as whole segments [3]. It is suggested that this transcranial magnetic stimulation (TMS). A recently developed control is done via specific predefined modules, termed muscle mapping technique, the pseudorandom walk method, synergies, that the central nervous system utilizes to accomplish significantly reduces time needed to perform TMS mapping a motor task. By using muscle synergies, instead of controlling without sacrificing the reliability of the measurements. Due to each muscle individually, the central nervous system alleviates this faster technique, it is now possible to map several muscles at the computational burden of the movement execution [4]. once, which was not viable before with the traditional mapping In the proximal-distal muscle synergy, activation of both method. Furthermore, motor mapping of the proximal Medial shoulder and forearm muscles are involved in a common motor Deltoid (MD) and the distal Brachioradialis (BR) muscle using cortical circuit in an integrated manner [5]. Activity-dependent this technique has not yet been performed. Therefore, the aim of couplings of networks are observed after extensive training of this study is to investigate the use of pseudorandom walk method coordinated movements with these muscles [6]. Such changes in to measure the training-induced plasticity of the M1 while taking muscle synergies, when neurons adapt to an unfamiliar task, these two muscles into account. First, we will perform the might reflect similar changes that occur during recovery from baseline TMS motor mapping. Second, the participants will go moderate stroke [7]. One way to measure such change is by TMS. through a six-week training period in a complex motor learning task performed with their non-dominant hand. After this training TMS and the pseudorandom walk method period, we will determine the training-induced plasticity by comparing the baseline and the post-training measurements. A TMS is a valuable tool to study M1 plasticity. This can be done control group will be included to control for the reliability of the by comparing the location, size, and excitability of cortical measurements. Further, we will determine the training-induced muscle representations before and after intervention [8]. The change in the muscle synergies by comparing the overlap in TMS stimulation produces motor evoked potentials (MEPs) in cortical muscle representations. Finally, we will explore the the muscles that can be measured with electromyography (EMG) training effect on the non-trained dominant hemisphere. We (Figure 1B). By observing their latency and amplitude it is hypothesize to observe a training-induced change in the motor possible to determine the cortical area that is connected with the maps and an increase in the overlap between the two muscle muscle of interest (Figure 1C). Plasticity can be determined by representations in the training group. Based on the intermanual an increase in the number of cortical sites where MEPs are transfer we expect to find a training-induced effect on the induced [8]. An increase in the mean MEP amplitude measured dominant hemisphere. at the most responsive cortical site, called the hotspot, can indicate an increase in cortical excitability [10]. KEYWORDS Muscles can be mapped at rest [11] or during low-level activity [12]. Low-level contraction permits the observation of MEPs at Motor learning, plasticity, transcranial magnetic stimulation, a lower rate of stimulation [12], especially for proximal muscles pseudorandom walk, primary motor cortex that are difficult to map at rest [13]. Distal muscle representations tend to be larger than proximal ones, and larger on the dominant 1 INTRODUCTION side, contrary to proximal muscles [9]. Motor learning of a complex upper limb task leads to a common control of the One of the most common impairments after stroke is hemiparesis proximal and distal muscles [8]. This results in an expansion of - weakness of one entire side of the body [1]. Patients' recovery the muscle representations, an increase in their muscle relies on the motor system's capacity for functional representation overlap, and an increase in MEP's size [8,9]. reorganization [2]. A better understanding of the primary motor Similar changes can be observed not only in the trained but also cortical (M1) reorganization and its' influence on the coordinated in the contralateral hemisphere [14], although some studies did 147 not observe that [9]. This reorganization of the non-trained hemisphere can be extremely useful for patients with hemiparesis for whom it is difficult to train the impaired side. Therefore, further research is needed in order to better understand how intermanual transfer in complex motor learning occurs. Changes occurring as a result of motor learning can be measured using various TMS methods to map muscles of interest. In the traditional mapping method, multiple TMS stimuli are used at predefined grid points on the scalp at M1 to measure MEP size. Such mapping can take between 15 up to 60 minutes for one muscle [15]. A new pseudorandom walk method was recently developed that takes less than 5 minutes without sacrificing reliability [15,16,17]. In this method, one does not need to repeatedly place the coil in a predefined position when delivering the stimuli (Figure 1A). The starting point for the delivery of the stimuli is at the hotspot, out of which consecutive stimuli are delivered in eight straight lines. The lines are then connected creating an ellipsoid. The rest of the stimuli are randomly applied within this ellipsoid [17]. Overall aim and key objectives The aim of this project is to map the proximal MD muscle and the distal BR muscle using the pseudorandom walk method. Figure 1: An illustration outlining the creation of a TMS map These maps will be used to measure plasticity in M1, induced [15]. after extensive training of a complex motor task. The complex motor task will be a darts-throwing task, in which all joints in an A: The traditional mapping method on the left and the upper limb are involved in a specific coordination pattern and pseudorandom walk method on the right. B: A square grid with each stimulation site is matched with the recorded EMG. MEP’s timing of proximal and distal muscles [7,3]. Changes in white matter can be induced after a minimum of six-week repetitive peak-to-peak value is extracted. C: The surface is fitted through training [4]. Accordingly, participants will train darts at home for the 3D position data cloud to create a 2D plane. The 2D position data are matched with the MEP data to fit the surface map. a period of six weeks using their non-dominant hand. The non- dominant hand has a lower level of baseline performance that can improve significantly more than the dominant hand, suggesting 2 METHODS that the plasticity might be greater [18]. We will compare cortical muscle representations and their overlap before and after Participants training. The key objective is to map the MD and the BR muscle We will measure two homogeneously matched groups of healthy representations using the pseudorandom walk method. participants based on their gender and age. We will include male Supporting objectives are to determine the training-induced and female participants aged between 18 and 45 years old. The plasticity of the M1, the training-induced changes in muscle sample size will be 30 participants per group (Cohen’s d = synergies, and the training-induced effect in the dominant 0.7419, power= 90%; = 0.05, according to area sample size hemisphere. We hypothesize that there will be a significant calculations [17]). All participants will be right-handed as increase in the experimental group in the motor map area, measured by the Edinburgh inventory [20]. Participants will not volume, a change in the centre of gravity of the muscle be recruited if they report having any metal implants in the representations, and a change in the mean MEP amplitude after surrounding area of the head or any history of epilepsy. training. We further hypothesize to observe an adaptation of the existing muscle synergies in the experimental group as shown by Experimental protocol the increase in the overlap between muscle representations. We expect to observe changes not only in the non-dominant Both groups will be measured twice with a six-week period in hemisphere but also in the dominant hemisphere. between. Control group will not perform any training in throwing Because of a significant reduction in time needed to perform darts. The measurements at each session will include TMS motor the measurements, motor mapping can now be used not only in mapping and mean MEP acquisition of MD and BR on both research but also in clinical practices. Additionally, hemispheres, as well as a measurement of darts performance understanding how the M1 reorganization after training occurs (Table 1). could help design better treatments for stroke patients. 148 Table 1: A scheme of the experimental protocol be instructed to throw 15 darts and to aim for the center. The dartboard will have 10 concentric circles worth 10 points for the Session 1 Training Session 2 center and 1 point for the outer-most layer. period The participants in the experimental group will do training sessions at home. The place of the training was determined based Experimental TMS Darts training TMS on COVID-19 measures. This way the participants are not taking group motor (6 weeks, motor higher risks for infection by participating in this study (e.g. mapping 15 – 20 mins, mapping increased use of public transport). They will receive three darts, 60 – 80 as well as several papers with the same dartboard design as used throws) in the test. The holes in the papers will be considered as proof of training. Each training session will last 15 – 20 minutes and MEP MEP consist of 60 – 80 throws. They will be asked to perform the acquisition acquisition training consistently over the whole period and to keep a diary of their performance. Control group Darts test No training Darts test Outcome measures For the key objective, four parameters from the TMS motor maps of each muscle will be calculated - the area, volume, and center of gravity (cog) in two dimensions. Additionally, the mean MEP TMS measurements amplitude at each muscle hotspot will be calculated. The effects of the training-induced plasticity of M1 will be The muscle motor maps will be determined by monophasic TMS determined using the outcomes from the key objective. The pulses with a posterior-anterior current direction with the coil repeated measures ANOVAs will be fitted to each variable handle pointing 45° from the midsagittal line. The EMG separately to evaluate group (between factor: experimental vs electrodes will be placed on the MD and BR muscles in a belly- control) and session (within factor: baseline and post-training). tendon montage. Participants will be seated with their hands Additionally, a comparison of the baseline and post-training relaxed on the table. First, the head of the participant will be co- darts test scores will be done on both groups to determine the registered to a stock MRI scan. Second, the hotspot, the location effect of training. with the largest MEPs, will be estimated using the pseudorandom Training-induced change in muscle synergies will be acquisition with 80 pulses and 2s interval [15]. The stimulation measured by first superimposing the cortical motor maps of the intensity will be set to 50% of the maximum stimulator output two muscles and measuring their overlap. Then, the change in (MSO) and increased with 5% MSO if there will be no the overlap will be determined using the repeated measures measurable MEPs after 15 pulses. Furthermore, the resting motor ANOVA to investigate the interaction between groups (control, threshold (RMT), which is the lowest stimulator intensity with a experimental) and sessions (baseline, post-training). 50% probability to produce the MEP at the hotspot, will be The contrast between the map areas of the dominant versus determined. EMG responses with a peak-to-peak amplitude non-dominant hand will be compared between baseline and post- 0.05mV, between 5 and 45ms after stimulation, will be training using a paired t-test to determine if there is an overall considered MEPs. Finally, the motor maps will be acquired with effect on both hemispheres. a stimulation intensity of 110% RMT [17]. The pseudorandom walk method will be performed as described previously [17]. This measurement will be done on both hemispheres for both 3 CONCLUSION muscles in each session and will take approximately 30 minutes This research project exploits the novel TMS mapping procedure per hemisphere. Additionally, after motor mapping, 40 TMS to further validate it on upper-limb muscles that haven’t been pulses will be applied at the hotspot to obtain mean MEP mapped yet using the pseudorandom walk method. Furthermore, amplitudes, which will take approximately 5 minutes per using this technique, the project also explores the effect of hemisphere [10]. extensive motor learning on the M1 plasticity. The motor We will first pilot the motor mapping of the MD and BR learning is approached holistically by analyzing motor maps, cortical representations under resting conditions before the MEPs, motor performance, interhemispheric transfer, and the experiment is carried out. We will switch to measurements proximal-distal muscle synergy. The latter also adds to the performed under low-level active conditions if the motor developing paradigm of muscle synergies and explores ways in mapping under resting conditions yields unreliable results [13]. which the upper limb is controlled as a whole. Results from the project will contribute to our understanding of the proximal- Test and training protocol distal synergy and its’ involvement in reaching movements. The participants in both groups will do a test of dart-throwing Moreover, the results will contribute to a better design of skills at both sessions. The participants will stand with the left rehabilitation therapy for patients with M1 impairment. Using foot on a black line on the floor set at 2.4m from the dartboard. the pseudorandom walk method, the therapy could become more The center of the target will be 1.73m above the floor. 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[19] Sawaki L, Butler AJ, Xiaoyan Leng X, Wassenaar PA, Mohammad YM, Blanton S, et al. Constraint-Induced movement therapy results in increased motor map area in subjects 3 to 9 Months after stroke. Neurorehabilitation Neural Repair 2008;22:505e13. https://doi.org/10.1177/1545968308317531. [20] Oldfield RC. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 1971;9:97–113. 150 Chronotopic Maps in Temporal Processing and Perception Shrikanth Kulashekhar Cognitive Neuroscience International School for Advanced Studies (SISSA) Trieste, Italy shrikanth.kulashekhar@sissa.it ABSTRACT preferentially for task durations (Fig. 1). Two Japanese monkeys were trained to perform an interval-generation task that Neurons maximally tuned to specific durations in the hundreds required them to determine a hold time of three different of milliseconds to seconds are widely observed in studies using intervals of 2s, 4s and 8s, before initiating a key release monkeys. These tuned neurons are observed in areas that are movement LED lights indicated the specific waiting times previously known to be involved in timing research—pre- before key release: yellow light indicated 2s; red light indicated supplementary motor area and basal ganglia. However, the role 4s; and blue light indicated. duration tuned neurons, in these brain areas, play in temporal processing remains unclear. In this review, I present and discuss evidence from recent neuroimaging studies that show the presence of a topographical organisation of duration tuned neuronal populations in the human brain. The studies, using ultra-high field fMRI, have found that the duration tuned clusters at the voxel level in the occipital, parietal and frontal areas, including the supplementary motor area (SMA), are topographically organized as duration maps—chronomaps. Duration tuning and chronomaps could thus serve as a functional mechanism for the encoding and representation of abstract stimulus features such as time. that the monkey had to wait at least 8s. KEYWORDS Adapted from Mita et al., Time perception, temporal processing, duration tuning, fmri, 2009 Figure 1: Raster displays and spike-density functions chronomaps, supplementary motor area illustrating selective neuronal activation during the 8-s task (a), 4-s task (b) and 2-s task (c). Mita et al. [6]. 1 DURATION TUNING While duration tuning in timing brain areas associated with Interval timing refers to the behavior of perceiving, estimating, interval timing is well observed, the neuronal mechanisms and representing durations in the hundreds of milliseconds to linking the areas to the perception, estimation and minutes range crucial for human behavior, in decision making, representation of durations remain unknown [1,2,3]. One speech processing, motor activity and music perception [1]. possible link between duration tuning to temporal processing Studies using functional magnetic resonance imaging (fMRI) could be that duration tuned neurons in the SMA, tuned to have found brain activity in certain key brain regions to be different durations, are topographically organised as functional correlated with interval timing behavior. These areas include maps. Such functional maps could then provide a mechanism supplementary motor area (SMA), intra parietal sulcus, basal for the perception, estimation, and representation of durations. ganglia, and cerebellum [1,2,4,5]. Electrophysiological studies Could such a topographic organisation of duration tuned on monkeys have found neurons from these timing brain areas neurons exist in the human brain? If so, could such a to exhibit duration tuning [6,7]. When neurons are tuned, they topographic organisation be studied non-invasively in humans? preferentially fire for specific task durations. Mita et al. [6] found that neurons in the monkey pre-SMA (human SMA) fire 2 REPRESENTATION OF ABSTRACT STIMULUS FEATURES THROUGH MAPS Permission to make digital or hard copies of part or all of this work for personal or Representation of stimulus features through topographically classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and organised sensory maps is well known, such as, the tonotopic the full citation on the first page. Copyrights for third-party components of this maps in the auditory cortex or the retinotopic maps of the work must be honored. For all other uses, contact the owner/author(s). occipital cortices. Could a similar topographical organisation of Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). abstract stimulus features such as time and numerosity exist? 151 Further, could such a topographical organisation be studied was observed even in a control condition when subjects were non-invasively in humans? instructed to focus only on the spatial aspect of the stimuli and Harvey et al. [10] using ultra high-field fMRI (at 7 Teslas) ignore their temporal properties. showed the existence of topographically organized numerosity Protopapa et al. [8] connected the previously reported maps in the human parietal cortex (Fig. 2). Numerosity refers to neuronal duration tuning in monkeys’ medial premotor cortex the size of a group of objects. Participants in the study were [6,7] to a representational format in humans. Although previous presented with visual stimuli of varying numerosity. The duration tuning seen in monkeys were exclusively associated results showed that parts of the cortical surface corresponded with motor-timing behaviour, Protopapa et al. [8] showed the to specific numerosity, in a topographical manner increasing presence in human premotor cortex of a duration tuning from the medial to lateral ends. The results provided evidence mechanisms in a purely temporal perceptual task. that higher-order abstract features and their topographical A recent study, Harvey et al. [11] has added to the evidence organizational principles could be studied non-invasively in on chronomaps, and the topographic organization of stimulus humans. frequency. In the study, high field fMRI (7 Teslas) data from volunteers were acquired while they were presented with a rapid succession of visual stimuli varying in duration, frequency, or both. The resulting data were analyzed using a population receptive field approach [9]. Topographic organization of voxels that were maximally responsive to stimulus duration and frequency was observed in ten different Slika cortical regions, from occipital to parietal to frontal lobe. The duration and frequency maps were observed in both the hemispheres. Another intriguing finding of the study was that the orientation of the maps was found to be variable unlike, the fixed, anterior-posterior orientation from Protopapa et al. [8]. Thus, Harvey et al. [11] added to the evidence of existence of topographic maps linked to abstract stimulus features of Adapted from Harvey et al., 2013 numerosity, time and frequency. Figure 2: High-field fMRI data was acquired while subjects were shown visual stimuli of varying numerosity. Numerosity maps showing preferred numerosity increasing from the medial to lateral ends (white lines) of the region of interest (ROI) (black and white lines). Harvey et al. [10]. 3 REPRESENTATION OF DURATIONS THROUGH CHRONOTOPIC MAPS Like the topographical organization of numerosity, could task durations have a similar map-like organization? Protopapa et al. [8] provide the first evidence for a topographical representation of durations in the human supplementary area. Protopapa et al. [8] used data from ultra-high field fMRI (at 7 Teslas) and showed the results to be independent of task design and analysis approaches. In Experiment 1 of the study, volunteers participated in a visual, temporal discrimination task, where Adapted from Protopapa et al., 2019 subjects had to compare and respond if the second stimulus lasted shorter or longer then the first. The resulting data were Figure 3: Chronotopic maps showing the topographic analyzed using a general liner model (GLM) approach. While in organization of duration-sensitive vertices in bilateral SMA Experiment 2 of the study, participants performed a visual, with the progression in the rostro–caudal direction, with temporal, and spatial discrimination tasks. In the temporal task, vertices sensitive to the shorter duration (vertices in warmer subjects had to compare and respond which of the two colors) located in the anterior and those sensitive to the presented stimuli lasted longer. While in the spatial task, they longer duration (vertices in colder colours) in the posterior judged which of the two stimuli underwent the largest change SMA. A, anterior; L, left; P, posterior; PCG, precentral gyrus; in orientation. The data were analyzed with neural population R, right; SMA, Supplementary Motor Area. Protopapa et al. [8]. receptive field approach [9]. Chronotopic maps, topographic organization of durations in the range of 0.2 to 3s, was observed in the SMA both in the left and right hemispheres (Fig. 3). The 4 PROPERTIES OF CHRONOTOPIC MAPS progression of the maps was seen in a fixed, rostro–caudal direction, with vertices sensitive to the shorter duration located Protopapa et al. [8] and Harvey et al. [11] were successfully in the anterior and those sensitive to the longer duration in the able to show the existence of chronotopic maps. The two studies posterior SMA. Chronomaps were also found in a task helped characterise the interesting properties of chronomaps: independent manner: topographic organization of durations chronomaps exist in both cerebral hemispheres; chronomaps 152 exhibited variable orientations in their topographical REFERENCES organisation; chronomaps exist in multiple brain areas; [1] Buhusi CV, Meck WH 2005. What makes us tick? chronomaps organise in a task-independent manner; and Functional and neural mechanisms of interval timing. finally, chronomaps are linked to temporal perception and Nat Rev Neurosci 6:755–765. performance. 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Population panel), does the spatial position of the green clusters remain receptive field estimates in human visual cortex. the same or change in the new chronotopic map? If the green Neuroimage Jan 15 39 (2),647–660. clusters retain their spatial position, then the durations are DOI: https://doi.org/10.1016/j.neuroimage.2007.09.034 organised in an absolute manner. If they change their spatial [10] Harvey, B.M., Klein B.P., Petridou N., and Dumoulin, S.O. position based on the duration range the durations are 2013. Topographic Representation of Numerosity in the encoded in a relative manner. Human Parietal Cortex. Science 341, 6150: 1123-1126 DOI: 10.1126/science.1239052 In summary, there is growing evidence that chronomaps [11] Harvey, B.M., Dumoulin, S.O., Fracasso, A., and Paul, J.M. could provide a possible mechanism for the encoding and 2020. A network of topographic maps in human representation of durations associated with temporal association cortex hierarchically transforms visual processing and perception. Despite the difficulty to link the timing selective responses. Curr. Biol. 30, 1424–1434. voxel level chronomaps in humans to the duration tuned DOI: https://doi.org/10.1016/j.cub.2020.01.090 neurons in monkeys, these new findings are influencing and contributing to the field of temporal cognition. 153 Being in Brackets: A First-Person Exploration of the Phenomenological Method of Epoché Viktorija Lipič Faculty of Arts; Center for Cognitive Science at the Faculty of Education University of Ljubljana Ljubljana, Slovenia viktorija.lipic@gmail.com ABSTRACT exists as it is perceived even if there is no one to direct attention to it or perceive it [3]. This article is an excerpt from the ongoing research exploring the The basic method of the phenomenological approach is to experience of carrying out the phenomenological method of direct one's attention from what the experience is assumed to be epoché from the first-person perspective. First, we outline the about to the observation of the experience itself, as it is given in state of the field and then dive into the first-person exploration, consciousness. In order to avoid succumbing to our everyday describing the method used in gathering our experiential data. embeddedness in the natural attitude, we must bracket our After that, we focus on presenting a data-derived first-person presuppositions, values, judgments and opinions about the world. model that describes the experience of epoché as a diachronic To do this, we employ a particular gesture of awareness – the process, comprised of five phases: 1) The pre-epoché phase and epoché. Husserl [1] asserts that the epoché enables a return to the experience of the natural attitude shifting; 2) Entering the “the things themselves”, to the world as we directly experience experiential phase of the epoché; 3) The experiential phase of the it. In performing the epoché, we put in brackets, or “turn off” the epoché; 4) Exiting the experiential phase of the epoché; and 5) whole world as we normally experience it. The task is to re- The post-epoché phase and how the natural attitude is awaken us to recognize the meaning we bestow upon our experienced after the epoché. experiences. As Maurice Merleau-Ponty [4, p. xv] puts it, performing the epoché does not mean to withdraw from the KEYWORDS world or the phenomena, but to “slacken the intentional threads Phenomenology, first-person research, epoché, natural attitude which attach us to the world and thus bring them to our notice”. 1 INTRODUCTION 1.1 State of the art in contemporary first-person To better understand our enterprise, we must first familiarize research ourselves with the concept of the “natural attitude”. In Ideas I, The definition of the method of epoché as well as the question of Edmund Husserl [1] introduces the natural attitude as our its importance in phenomenology and the possibilities of everyday assumption that the world exists independently of our implementation outside philosophical fields have been the source conscious awareness. In this attitude we take the world as always of many debates (e.g. [5,6]). Moreover, contemporary already present, prior to any reflection. Expanding on this discussions [5,7] point to a lacking definition of the concept. In conceptualization, in Eugen Fink’s “Sixth Cartesian Meditation” addition to problems of interpretation, there is also the question [2, p. 166], Husserl goes on to say: “In the natural attitude, in of how the realization of such a state takes place from the first- which for ourselves and for others we are called and are humans, person perspective (i.e. what is it like for me, the experiencing to everything worldly there belongs the being-acceptedness: subject, to perform the epoché). Similarities between the concept existent in the world, in the world that is always existent of the epoché and various Eastern practices have also been beforehand as constant acceptedness of a basis. So, also man’s illuminated in recent decades, such as the yoga practice of being is being in the world that is existent beforehand. In prāṇāyāma (breath control) [8] and Samatha-Vipassanā phenomenology, this being-beforehand is itself a problem.” meditation [9]. This everyday forgetfulness thus permeates our everyday life. Due to the uncertainty that permeates the field and the various We operate on the basis of natural naivety, assuming that reality interpretations about what epoché is and how to carry it out, we exists ‘out there’ and is waiting to be discovered and explored. have decided to investigate the experiential process from a first- This reality is supposed to be independent of our experience and person perspective in the hopes of providing more clarity and Permission to make digital or hard copies of part or all of this work for personal or being able to better distinguish what it is we are talking about classroom use is granted without fee provided that copies are not made or distributed when we talk about the practice of epoché. for profit or commercial advantage and that copies bear this notice and the full In this article we broadly focus on the following questions: citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). what is it like to come into contact with the experience of epoché Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia and what are the characteristics of carrying it out from a first- © 2020 Copyright held by the owner/author(s). person perspective. We present the diachronic process involved in performing the method of epoché, focusing on a) how an 154 individual moves away from and back towards being immersed 3 RESULTS in the natural attitude; b) how an individual relates to her own The findings presented below are a tentative illustration of our experience and c) what changes in the process. research. Since the study is still ongoing, we have not yet carried out a systematic analysis of acquired descriptions and present 2 METHOD here merely an excerpt of data collected so far. Preliminary analysis of the transcribed texts focused on both The findings presented in this article are part of a broader study synchronic and diachronic dimension of the experiential in which we are exploring epoché with the micro- episodes and attempted to create an overview of which phenomenological interview method [10]. The aim of the micro- experiential moments were prevalent in all eight investigated phenomenological interview is to help co-researchers become journal entries and which were distinct. This has led us to aware of a past experience and access detailed descriptions of propose the basic shape of a data derived first-person model, that same concrete experience, enabling the coming into contact which frames epoché diachronically as a five-phase process. with previously unattainable dimensions of lived experience and Of particular note here is that these are preliminary findings cultivate an individual's reflection and retrospective reporting of meant to illustrate the experiential process of the co-researcher’s experiential data. individual experience and should be refined in future research with reports provided by other co-researchers to yield a more The co-researcher fruitful reflection of patterns and categories of carrying out Our co-researcher, a female aged twenty-seven, is trained in the epoché from a first-person perspective. micro-phenomenological method, has considerable phenomenological and first-person knowledge with more than 500 hours spent observing experience and participating in first- 3.1 Pre-epoché phase and the experience of the person and micro-phenomenological research (as interviewee natural attitude shifting and interviewer). She also has six years of meditative practice. This phase is characterized by a gentle awareness of the co- Selection of the explored experiences researcher’s surroundings (sensing them, but not engaging with What constituted the moment of epoché was partly decided prior them, letting them pass by). The experience of the natural attitude to gathering the data, based on prior theoretical knowledge of the shifting was in all interviews accompanied by a relaxed and components of epoché provided by Depraz et al. [11]. This view stable state of body and mind. In one particular interview it was was then modified during the study to incorporate the co- described as follows: researcher’s own individual perspective. The criterion for what constitutes the moment of epoché from the co-researcher’s “And as I stand there, I also hear people, this soft shuffling perspective was as follows: noticing a profound shift in the of the people around me, silent, soft movements of feet quality of one’s experience of the world and relating towards the shifting on the ground and shuffling on the ground. And world, characterized by a lack of judgment directed towards the there is this feeling in my body of stable ground. […] And world. I feel my body as a whole, just this being in the standing position. And a general calmness that comes with this Interviews and procedure feeling.” Altogether we have gathered nineteen journal entries describing experiences during meditative practice – either a Vipassanā meditation (with eyes closed), or a walking mindfulness 3.2 Entering the experiential phase of the meditation (with eyes open). After each meditation session, the epoché concrete moment of what was experienced was written in the The co-researcher has reported on experiencing an element of journal and later explored during the micro-phenomenological transition between the pre-epoché phase and the experiential interviews in more detail. The interviews were carried out with phase of the epoché, which could be faster or slower. In the investigators trained in the micro-phenomenological method. majority of the investigated experiences (6 out of 8), entering the Eight interviews were conducted on eight selected journal epoché started by spontaneously “slipping into” the experience, entries, which were judged by the co-researcher to be the most whereby the experience of epoché seemed to arise by itself. vivid experiences of epoché. Two of the interviews were Conversely, in the other two experiential episodes, there was a performed in Slovene, while the other six were conducted in slow transition which took place either by remembering what it English. The duration of the interviews ranged from 60 to 90 was like before and trying to follow that felt atmosphere, or by minutes. The interviews were audio recorded on a personal smart softly settling in the body (or a body part) and allowing the phone or a Zoom H4n audio recorder. sensation to come, gently holding it in awareness. The co- All of the investigated experienced have occurred within the researcher has reported on there being a feeling of tension in the past year. Five interviews were carried out within 24 hours of the body, which she was able to recognize and intentionally relax, experienced moment, two took place a few days after the for example: experience and one experiential episode was investigated a few months after the experience took place. “I relax the shoulders, I let them [the arms] slump next The interviews were transcribed in full. Relevant parts of the to my body. Then there is this very soft, slow interviews conducted in Slovene were translated into English for movement, with no pressure in it. As this relaxation of the purposes of this article. the upper part of the body and a move towards the 155 lower part takes place, I relax into this feeling. It is “I feel as if I am looking at a ‘picture’ in front of me, bodily, as I shift a bit with my shoulders, but also it is there is this lack of spatial depth in what I am seeing. attentional – not focusing directly, just letting things go And at the same time there is a feeling of seeing and flow down here [in the belly area].” through this ‘picture’, this sensation. It feels as though my visual field is a veil and has its own dimension of This settling into the (part of the) body was then followed by a depth and of spatiality being present in the natural, feeling of space being more open, as though: everyday world. But what I am sensing is that which is ‘beyond it’, ‘through it’ […] It is like another feeling “My body can relax into this openness. Like, my body of space around me that is at the same time dense, as a shape can flow into this [space], a boundary where filled, thick, light, flowing, all-encompassing. I feel my skin is can flow into this open, flowing, this spatiality as an atmosphere, it is primarily felt as shimmering, static feeling [felt as the boundary, a air around me. And it goes on, it is felt as though the space a few centimeters around her body and slowly visual field [the veil] has a certain stopping point – it entering the space further “away” from the body]. stops the perception on a certain point. But this denser There is this feeling of being just open and relaxed, spatiality is felt as limitless, it goes on, it feels as there is an openness at the sides.” limitless potentiality all around me.” The feeling described here as a shimmer, or a static-like feeling The phase of the epoché was in all instances also characterized in quality, was in the majority of cases (5 out of 8) experienced by a feeling of a primordial space. This space was experienced as a sensation of spreading that lent itself towards lessening the as having the quality of density, thickness and sometimes warm sense of bodily boundaries. air that is: “Not visible, it is a felt air, felt as oneness around me 3.3 The experiential phase of the epoché [the felt location], to the sides, everywhere around me.” We have found that the experiential phase of the epoché has a variety of dimensions often appearing together. Here we describe In three experiential episodes during meditation, in addition to a few that have occurred throughout our investigation. what was described above, a feeling of space as a “background The phase of the epoché was in all investigated experiences of holding” was identified. This background was felt by the co- characterized by a serenity and letting-be. The co-researcher was researcher as being held by space, which had a profound quality not actively searching for information or any type of stimulus in of darkness and thickness. the world, rather the atmosphere was experienced as a calmness The phase of epoché was in all investigated experiences also in being, an allowing of appearances. In six interviews a accompanied by the loosening of the sense of bodily boundaries profound aspect of epoché was a felt sense of stability. It was and dissolving the separation between what is inner and what is described as a feeling of “sitting in myself” in the interview outer, described in the interview situation as follows: situations, yet it is important to note that this experience had very little to do with the experience of bodily sensations. Rather, it “There was no more separation, there was nothing out related more to the feeling of the body as a whole, to the gestalt [there], there was just this blackness and this familiarity of the body. that was felt as and felt in this warm quality of blackness. Another aspect that permeated all of the investigated And just the location that is this space where I feel my experiences was no directedness of the co-researcher’s attention awareness to be and that is all.” towards the world or “towards the front of oneself”. In an interview it was described as: 3.4 Exiting the experiential phase of the epoché Exiting the experience of epoché has occurred spontaneously and “Being directed towards the back and also being aware unintentionally in the majority of the investigated experiences (6 of the spinal cord, of the position of the spine.” out of 8). The co-researcher has reported that the feeling of the world slowly began drifting back in as attention started to The active engagement of the co-researcher was felt only in the become more focused on the external world and she felt herself act of sustaining awareness on the whole bodily gestalt. This act getting more directed towards it. was in one of the interviews perceived as: In a few examples (4 out of 8 investigated experiential episodes), there was a profound feeling of no separation between “It is effortless and feels like just being there with the the co-researcher and the world during the experiential phase of awareness.” the epoché, which was later contrasted by a feeling of separation on returning to a more “natural”, habitual mode of being in the This type of awareness brought about a change in the co- world. There were also a few (2 out of 8) instances of researcher’s visual field, if the eyes were open (this has occurred intentionally exiting, or rather of a feeling of “having to return”, in 4 out of 8 investigated experiences). The world was perceived which was experienced as a desire, an anxiety or a nudge urging without its usual depth and was in the interview situation the co-researcher to return to the natural mode of being. described as follows: In all of the investigated experiences, a big part of exiting the epoché was for the co-researcher a felt sense of coming back to 156 her own body from the (above mentioned) primordial space. It mystical traditions. It would also be interesting to design studies was described as coming closer to a point where she feels herself which bracket all such traditional presuppositions. to be situated in space and the space around that area becoming thicker and more condensed. This condensed and thicker feeling started in a part of the body (the area of the torso; 5 out of 8 REFERENCES explored experiential episodes) or was felt as the whole gestalt [1] Husserl, E. 2012. Ideas: General introduction to pure of the body becoming denser and heavier (3 out of 8 experiential phenomenology. Routledge. episodes). [2] Fink, E. 1995. Sixth Cartesian meditation: The idea of a transcendental theory of method. Indiana University Press. Heaviness and denseness also appeared to allow a sharper [3] Luft, S. 2011. Husserl’s method of reduction. In The Routledge focus on the body in all of the investigated experiences of companion to phenomenology. New York, NY: Routledge. epoché, which began to separate the body of the co-researcher [4] Merleau-Ponty, M. 2012. Phenomenology of perception. from the rest of the world. As she started to become more actively Routledge. directed towards the world, stronger feelings of differentiation [5] Zahavi, D. 2019. Applied phenomenology: why it is safe to ignore the epoché. Continental Philosophy Review, 1-15. between form and background in the visual field become more [6] Morley, J. 2010. It’s always about the epoché. Les Collectifs du noticeable to her. For example, she reported her environment Cirp, 1, 223-232. began to hold more graspable and holdable possibilities, which [7] Kordes, U., Oblak, A., Smrdu, M. & Demsar, E. 2019. came to the fore as the feeling of her body also shifted towards Ethnography of Meditation: An Account of Pursuing Meditative Practice as a Tool for Researching Consciousness. Journal of the background: Consciousness Studies, 26(7-8), 184-237. [8] Morley, J. 2001. Inspiration and expiration: Yoga practice “I am able to “pick out” a particular tree from a myriad of through Merleau-Ponty's phenomenology of the body. different trees, able to direct myself towards it and focus Philosophy east and west, 73-82. [9] Depraz, N. 2019. 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In all of the investigated experiences she reported on there being an immediate feeling of an increase in calmness, gentleness, contentment and a slowness of being after every experience of epoché. But also, a much more lingering feeling resounded through her being, namely the feelings of presence and the openness of space. She reported on experiencing a profound awareness of how her awareness shapes the surrounding world and how she is, in the end, inseparable from her surroundings. 4 CONCLUSION In the article we have set out to enrich the traditional conceptualizations of epoché with in-depth descriptions of the first-person experiences of epoché elicited by micro- phenomenological interviews. In analyzing the experiential reports of performing epoché, we have made three notable observations. The first observation is a profound shift in the quality of experience, how one turns towards, notices and attunes herself to the world. The second and third observation are closely linked to the first one: the second one being a felt profound shift in how one experiences one's own existence, one's being in the world; and the third one being a profound shift in how the appearance of the world and its enclosedness appears to “the observer”. Our preliminary analysis gave us a foundation for which experiential dimensions could be considered and additionally developed in future studies with more co- researchers. In addition, it would be fruitful to consider such endeavors more thoroughly in the frame of contemplative and 157 A new study of expected human longevity Anže Marinko Klara Golob Ema Jemec anze.marinko96@gmail.com klara.golob19@gmail.com ema.jemec97@gmail.com Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia Urša Klun Matjaž Gams ursaklun10@gmail.com matjaz.gams@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT third model includes inhabiting neighbouring planets. The fourth model represents the "rare Earth" hypothesis [15]. For each model In this paper we for the fifth consecutive year estimate the we represent all possible predictions from the pessimistic (there longevity of human civilization based on the absence of observ- are no other civilizations besides us) ones to the optimistic (there able extraterrestrial civilizations. In addition to our previous are a few thousands civilizations) predictions with different prob- studies, in this paper we add three more models and test all possi- ability distributions to more accurately estimate longevity of ble values of parameters and distributions. If there are not many human civilization. In summary, we test 4 different models under advanced civilizations in our galaxy, as newest studies indicate, all circumstances (parameters, distributions). our longevity can again be estimated at up to 10 000 years. The consistency of studies may or even should shift focus of our civilization. KEYWORDS Human extinction, Drake equation, Civilization collapse, Rare 2 RELATED WORK Earth hypothesis There are various estimations of possible number of civilizations; some propose between 600 and 40 000 technological civilizations 1 INTRODUCTION in our galaxy [13]. The differences often stem from the number of After more than 50 years of searching for extraterrestrial civiliza- Earth-like planets in the habitable zone around stars. One of the tions there is only one thing we know for sure: we have not found newest studies found that there should be around 36 civilizations any yet. After scanning more than 10 millions stars [14] we have in our galaxy if estimated time for a planet to form an intelligent not found any extraterrestrial life and that could indicate that life (life that could communicate with others in our own Galaxy) the longevity of such civilizations might not be so long. While is between 4.5 to 5.5 billion years (like Earth), assuming that an we know that we will die someday, we do not act like this. On average longevity of civilizations is 100 years [16]. Using three the similar note we as civilization will also extinct someday in different principles, the paper by Engler and von Wehrden [3] the future and that future might not be so far. Do we realise that represented that number of civilizations that have likely arisen in we could be on the verge of the extinction? For that reasons the our galaxy to date is between 7 and 300. However, it is estimated question about the longevity of human civilization is directly that with our tehnology the likelihood of detecting intelligent linked to the cognitive science. life could be two orders of magnitude smaller in comparison to In our previous papers [9, 17] we approached the question the detection of primitive life [8] (by primitive life are defined "Where is everyone?" and presented the Drake equation that mostly microbes and multicellular life and intelligent life is tech- could potentially solve the issue. In the first paper [9] we pre- nologically advanced intelligence - species that are capable of sented and analysed Sandberg [10] interpretation of the Drake producing detectable signatures of their technology). Another equation [2]. In the last paper [17] we presented possible causes issue is the detection of their radio signals [7]. In detail, if there for human extinction and used the Drake equation to estimate are 5 civilizations, the chance of us detecting them is 0.012%, but longevity of human civilization. We concluded that our technical if the number is 300, the probability is 95%. A great number of un- civilization will most likely survive just another 10 000 to 20 000 detected civilizations in therefore unlikely. However, if longevity years. of civilizations is less than 100 000 years, the signals arriving In this paper we analyze three models. The second and the at Earth may come from distant civilizations long extinct [5]. third model are based on Drake equation with some adjustments. The extinction due to natural causes is less likely - one research The second model uses substantially less parameters and the shows that the yearly probability for that is most likely to be less than 1 in 87 000 using four different models [12]. Permission to make digital or hard copies of part or all of this work for personal As already mentioned, in our research we wanted to look the or classroom use is granted without fee provided that copies are not made or Drake equation from the other side. Using 4 different models of distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this the Drake equation with modifications we ask about the longevity work must be honored. For all other uses, contact the owner /author(s). of human civilization instead of the number of other civilizations Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia in our Galaxy. For that reason this research is unique and first in © 2020 Copyright held by the owner/author(s). this topic. 158 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Anže Marinko, Klara Golob, Ema Jemec, Urša Klun, and Matjaž Gams Table 1: Probability densities for the parameters in equa- is treated as another civilisation, therefore N corresponds to the tion (1). number of inhabited planets. The obtained equation is 4 𝑓 ∗ (𝐿 + 𝐸𝐿 ) = 𝑁 Parameter Distribution where E represents the estimated numbers of planets like Earth 𝑅∗ log-uniform from 1 to 100 10+𝑓 +𝑓 and is calculated as 𝐸 = 5.1334 ∗ 10 𝑝 𝑐 𝑆 (S is the density 𝑓 log-uniform from 0.1 to 1 − 𝑝 42 of the stars and equals to 4.7233 ∗ 10 ) and f is calculated as 𝑛 log-uniform from 0.1 to 1 𝑒 𝑓 = 𝑅∗ 𝑓 𝑓 𝑓 𝑓 . 𝑝 𝑒 𝑖 𝑐 𝑓 log-normal rate, described in paper [10] 𝑙 Results can be seen in Table 2, Figure 2 and Figure 3. 𝑓 log-uniform from 0.001 to 1 𝑖 𝑓 log-uniform from 0.01 to 1 𝑐 3.4 Model 4 𝑁 point values: 1 to 10 000 The fourth model is based on the "rare Earth" theory and assumes that - as name already suggests - Earth is a very unique and rare 3 ESTIMATING THE LONGEVITY OF planet. We used the equation 3 and combined it with the Drake equation again using probability distributions. HUMAN CIVILIZATION WITH FOUR BASIC MODELS ∗ 𝑁 = 𝑁 𝑛 𝑓 𝑓 𝑓 𝑓 𝑓 𝑓 𝑓 𝑓 (3) 𝑔 𝑝 𝑝𝑚 𝑖 𝑐 𝑙 𝑚 𝑗 𝑚𝑒 The Drake equation consists of several parameters: The parameters added to the Drake equation are ∗ 𝑁 = 𝑅∗ 𝑓 𝑛 𝑓 𝑓 𝑓 𝐿, • 𝑝 𝑒 𝑁 is the number of stars in the Milky Way galaxy, be- 𝑙 𝑖 𝑐 tween 250 and 500 billion, where 𝑅∗ is the rate of star formation per year, 𝑓 is the fraction 𝑝 • 𝑓 is the fraction of planets that are metal-rich, between 𝑝𝑚 of stars with planets, 𝑛 is the number of Earth-like (or otherwise 𝑒 1 and 10 percent, habitable) planets per star that has planets, 𝑓 is the fraction of 𝑙 • 𝑓 is the fraction of planets with a large moon, between 𝑚 habitable planets with actual life, 𝑓 is the fraction of life-bearing 𝑖 0.3 and 3 percent, planets that develop intelligence (technologically advanced civ- • 𝑓 is the fraction of solar systems with Jupiter-size planets, 𝑗 ilizations), 𝑓 is the fraction of intelligent civilizations that are 𝑐 between 5 and 10 percent, detectable and 𝐿 is the average longevity of such civilizations. • 𝑓 is the fraction of planets with a critically low number 𝑚𝑒 Finally, 𝑁 is the number of detectable civilizations. We used the of extinction events, between 1 and 10 percent. following equation for computing 𝐿 ∗ 𝑁 𝑓 𝑛 𝑓 𝑓 𝑓 𝑝𝑚 𝑔 𝑚 𝑗 𝑚𝑒 𝑁 L is then calculated as 𝐿 = . 𝑁 𝐿 = (1) Results can be seen in Table 2 and Figure 1. 𝑅∗ 𝑓 𝑛 𝑓 𝑓 𝑓 𝑝 𝑒 𝑙 𝑖 𝑐 with the probability densities and limits from Table 1. In Table 2, 4 EXPERIMENTS the third column "stabilization" denotes the point where probabil- 4.1 Single Models ity density stops decreasing, meaning that the major probability was up to this point. To simulate longevity estimates 𝐿, we randomly generated values of each parameter for a chosen number 𝑁 of advanced civiliza- 3.1 Model 1 tions in our galaxy (civilizations that transmit electromagnetic signals to space) using the predefined probability density. Then, The first model was already fully described in [17]. several derived graphs are generated, e.g. the one in Figure 1 3.2 Model 2 (presented for models 1, 2 and 4, while model 3 is similar to 1). The main part of this model was inspired by [4]. It represents a simplified version of the Drake equation - parameters are reduced in just two: an astro-physical (presents total number of habitable zone planets) and a bio-tehnical (represents probability that a given habitable zone planet has ever evolved a technological species). The motivation for the introduction of the model 2 was smaller number of variables to avoid numerical problems. We combined some parameters from the Drake equation and got the following equation: 𝑁 = [𝑅∗ 𝑓 𝑛 ] [ 𝑓 𝑓 𝑓 ]𝐿 = 𝑓 𝑓 𝐿 (2) 𝑝 𝑒 𝑙 𝑖 𝑐 𝑎 𝑏 • 𝑓 is the astro-physical probability 𝑎 • 𝑓 is the bio-tehnical probability 𝑏 Figure 1: Probability density function of log(L), i.e. ex- The longevity is calculated as 𝐿 = 𝑁 . Results can be seen in pected human longevity based on relative probability with 𝑓 𝑓 𝑎 𝑏 Table 2 and Figure 1. N = 10 for models 1, 2 and 4. 3.3 Model 3 Figure 2 and Figure 3 present the same relations as in Figure This model is based on [1]. The main upgrade from the original 1, but for model 3 and in different ways: Figure 2 presents a 3D Drake’s equation to this model is an added possibility to expand view in the logarithmic scale, Figure 3 presents linear view on civilization to neighbouring planets. Each newly inhabited planet the same relation. 159 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Table 2: Median and stabilization for different N for all 4 models. median stabilization N \ model 1 2 3 4 1 2 3 4 1 2 200 200 720 1 070 13 600 9 200 61 400 9 200 10 22 000 900 2 060 8 320 11 100 1 500 20 100 1 500 100 220 000 7 000 5 930 77 640 9 300 100 2 800 100 1000 2 200 000 70 000 19 570 763 190 5 800 20 300 20 10 000 22 000 000 700 000 65 000 7 588 330 / / 40 / 4.2 All Models Merged In this section we combine results of all 4 models simultaneously and each parameter under 5 different distributions (log-uniform, uniform, half-normal, log-normal distribution and distribution with the most of the probability close to the upper bound). The results are presented in the form of histograms. We compute new linearly independent space pretending that a histogram is a vector using PCA - Principal component analysis. It turns out that the three dimensions with the biggest eigenvalue are informative enough, therefore we can draw 3D figures. We compute some clusters using k-means algorithm and mean histogram for each cluster. Each cluster is approximated as a surface. 4.3 Results Figure 2: Longevity based on 𝑁 , side view for model 3. Figure 3: Longevity based on 𝑁 for model 3, N = 1, median = 720, stabilization = 61400. Figure 4: Transformed space clustered into 5 clusters. Each If we present the graph of probability densities in a linear dot is a histogram transformed to a new space using PCA. (as in Figure 3) instead of logarithmic scale, we get quite differ- We can see the first three dimensions of this space. ent impressions: the majority of possibilities for greater 𝑁 are at the left of the graph resulting in a faster decline and faster One point in Figure 4 corresponds to one histogram, and his- stabilization point. This relation is observable in Table 2 in the togram are clusters into splines of five different colors. The first third, "stabilization" column, which denotes when a decline is and the fifth cluster contain mostly histograms for the first and less than 1 percent in a corresponding 100 years. It is impor- the third model. All the other clusters consist of the second and tant to distinguish between stabilization and median: the median the fourth model. The expected human longevity will be higher presents a point dividing all simulations into two intervals that for these thee clusters. are equally frequent, and stabilization indicates the end of a steep In Figure 5 we present properties of the clusters by their means. dive. While the median is mainly linearly growing with the num- As expected the first and the fifth cluster have peak before the ber of civilizations, the stabilization decline presents the point others but later they are still higher because of a theoretical step where probability "tail" smaller than 1 percent. At 𝑁 = 1, the me- that gives some probability even to practically unimaginable 8 dian is smaller than the stabilization, and at 𝑁 = 100, the median values (numbers high as 10 years which is 20 times more than is bigger for all models. the occurrence of Australopithecus [6]). 160 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Anže Marinko, Klara Golob, Ema Jemec, Urša Klun, and Matjaž Gams [2] Frank Drake. 2015. The Drake Equation: Estimating the Prevalence of Extraterrestrial Life Through the Ages. Cam- bridge University Press. [3] John-Oliver Engler and Henrik von Wehrden. 2018. where is everybody?’ an empirical appraisal of occurrence, prevalence and sustainability of technological species in the universe. International Journal of Astrobiology 18(6):499- 505. doi: 10.1017/S1473550418000496. [4] A. Frank and W.T. Sullivan. 2016. A new empirical con- straint on the prevalence of technological species in the universe. Astrobiology, 16, 5, 359–362. doi: 10.1089/ast. 2015.1418. [5] Claudio Grimaldi, Geoffrey W. Marcy, Nathaniel K. Tellis, and Frank Drake. 2018. Area coverage of expanding e.t. Figure 5: Mean survival function for each cluster. signals in the galaxy: seti and Drake’s N. Publications of the Astronomical Society of the Pacific 130(987). doi: 10. Now we can compare a few distributions that are still different 1088/1538- 3873/aaac6a. enough based on their peak density from lower to upper bound. [6] Yohannes Haile-Selassie. 2010. Phylogeny of early Aus- tralopithecus: new fossil evidence from the Woranso-Mille 5 CONCLUSION AND DISCUSSION (central Afar, Ethiopia). Philosophical Transactions of the Royal Society B: Biological Sciences. 365 (1556): 3323–3331. Based on the research where several participants (general UK doi: 10.1098/rstb.2010.0064. public, general US public, Oxford students) were asked about [7] Marko Horvat. 2007. Calculating the probability of detect- their view on the possibility of the human extinction, results ing radio signals from alien civilizations. arXiv:0707.0011 show that they think it needs to be prevented [11]. [physics.pop-ph]. This research designed models of probability densities of the [8] Mansavi Lingam and Abraham Loeb. 2018. Relative likeli- longevity of human civilization in significantly more advanced hood of success in the searches for primitive versus intelli- ways compared to our previous studies. We generated all four gent extraterrestrial life. arXiv:1807.08879 [physics.pop-ph]. models such that we distribute each parameter by all five selected [9] Jurij Nastran, Beno Šircelj, Drago Bokal, and Matjaž Gams. distributions. To determine the realistic probability of longevity, 2018. Sensitivity analysis of computational models that Figure 3 is most relevant: after probability drops to low values dissolve the Fermi paradox. Informacijska družba, volume and remains so for a long period of time. If integrated over a A. long period of time, it can result in big values as "mean" shows [10] Anders Sandberg, Eric Drexler, and Toby Ord. 2018. Dis- in Table 2. But in reality, the long close-to-zero tail seems more solving the Fermi paradox. arXiv preprint arXiv:1806.02404. of a numerical curiosity. "Stabilization" is therefore the relevant [11] Stefan Schubert, Lucius Caviola, and Nadira S. Faber. 2019. indicator of civilization longevity. The psychology of existential risk: moral judgments about The models analyzed here all show that if there are more human extinction. Scientific Reports 9. doi: 10.1038/s41598- civilizations, we have lower probability of living longer (column 019- 50145- 9. stabilization). Regardless of 𝑁 and after initial fluctuations at the [12] Andrew E. Snyder-Beattie, Toby Ord, and Michael B. Bon- beginning, the curve of the longevity becomes static, monotonic, sall. 2018. An upper bound for the background rate of very slightly decreasing. From Figure 5 we can interpretate that human extinction. Scientific Reports 9:11054. doi: 10.1038/ even the most optimistic cluster (cluster 2) gives us result that s41598- 019- 47540- 7. we will survive more 100 000 years with half probability and [13] Robert Strom G. 2015. We are not alone: extraterrestrial more than million years with 5% chances. Based on all of the technological life in our Galaxy. Astrobiol Outreach 3: 144. clusters we can conclude that the highest probability is that we doi: 10.4172/2332- 2519.1000144. will survive at most 10 000 years. [14] Chenoa Tremblay and Steven Tingay. 2020. A SETI survey In summary, this paper is relevant because it shows that we of the Vela region using the Murchison Widefield Array: might not have a lot of time left, at least in terms of cosmic orders of magnitude expansion in search space. Cambridge timing. Maybe we can buy us some time by taking better care of University Press. doi: 10.1017/pasa.2020.27. the Earth or by starting to colonizing other planets, but the most [15] Peter Douglas Ward and Donald Eugene Brownlee. 2000. important thing is to start making more researches that could Rare Earth: Why Complex Life Is Uncommon in the Universe. possibly help to prevent the extinction of human civilization or Copernicus. at least reschedule it later in the future. [16] Tom Westby and Christopher J. Conselice. 2020. The as- ACKNOWLEDGMENTS trobiological Copernican weak and strong limits for in- telligent life. The Astrophysical Journal 896(1):58. doi: 10. We thank Institute Jožef Stefan for making this research possible. 3847/1538- 4357/ab8225. REFERENCES [17] Beno Šircelj, Laura Guzelj Blatnik, Ajda Zavrtanik Drglin, and Matjaž Gams. 2019. Expected human longevity. Infor- [1] David Brin. 1983. The ’great silence’: the controversy con- macijska družba, volume B. cerning extraterrestrial intelligent life. Quarterly Journal of the Royal Astronomical Society, 24, (August 1983), 283– 309. 161 Does sight provide insight into Alzheimer’s dementia? 1,2 ∗ Katarina Marjanovič 1,3 ∗ Matej Perovnik katarina.marjanovic@kclj.si matej.perovnik@kclj.si 1 Department of Neurology, University Medical Centre, Ljubljana 2 Faculty of Education, University Of Ljubljana 3 Faculty of Medicine, University Of Ljubljana Ljubljana, Slovenia ABSTRACT plan ahead and thus ameliorate caregiver burden. Furthermore, certain non-pharmacological interventions are more effective in Alzheimer’s dementia (AD) is the most common neurodegenera- the earliest stages of AD and early diagnosis can lead to early tive dementia. Its timely and early diagnosis is of great impor- involvement into drug trials [5]. Additionally, bearing in mind tance, as it allows patients to plan ahead and improve life quality that about 5–10% of patients with MCI progresses to dementia with different non-pharmacological approaches. Several biomark- per year [6], we can also highlight the importance of accurate ers, which allow for such a diagnosis, are already part of everyday diagnosis of Alzheimer’s disease and accurate identification of clinical routine. While their role in the patient’s assessment is MCI patients who will progress to AD. undoubtedly valuable, they bear certain limitations, such as in- vasiveness and price. A search for a novel, non-invansive and in- expensive biomarker is underway. Eye movements have recently been proposed as a promising candidate for such a biomarker. 2 DIAGNOSIS OF DEMENTIA Here, we offer a brief overview of both: the biomarkers most Diagnosis of dementia is inherently linked to firstly, ruling out typically used in the clinical setting, and the eye movements, potentially treatable causes and secondly, diagnosing the under- as tracked via eye tracker—a method, which already has a long lying neurodegenerative process. In this section, we will first tradition in the field of cognitive science. briefly address other, potentially treatable causes of cognitive im- KEYWORDS pairment and then present the biomarkers of the most common neurodegenerative cause of dementia—Alzheimer’s disease. Alzheimer’s dementia, early diagnosis, biomarkers, eye move- Individuals with cognitive impairment firstly undergo blood ments, eye tracking, structural MRI, lumbar puncture, FDG PET screening for systemic abnormalities (vitamin B , folate, thyroid- 12 stimulating hormone, calcium, glucose, complete blood cell count, 1 INTRODUCTION renal and liver function) and structural imaging with magnetic Dementia is a clinical syndrome that involves impairment in at resonance imaging (MRI) or at least computer tomography (CT) least two cognitive domains (i.e. memory, attention, executive to exclude other causes of dementia (i.e., tumor, abscess, stroke functions, visuospatial abilities or language) and interferes with or normal pressure hydrocephalus) [7]. Core diagnostic criteria individual’s ability to function in their daily activities [1]. It can for AD are still rooted in clinical presentation, meaning that the arise as a consequence of various pathophysiological processes physician can make an AD diagnosis even without the use of in the brain that start decades before the appearance of the first biomarker information [1]. Because clinical diagnosis of AD is cognitive symptoms. The most common cause of dementia is not in concordance with pathological diagnosis in around 30% of Alzheimer’s disease that causes 60 to 80% of all dementias [2]. cases [8], there has been a shift towards promotion of biomarker- Alzheimer’s dementia (AD) is a final stage of Alzheimer’s disease supported diagnosis in recent years [9]. Biomarker is a charac- whose pathological hallmark is accumulation of misfolded pro- teristic that can be measured objectively and reflects a certain teins: amyloid 𝛽 (A𝛽 ) and Tau protein in the brain, which in turn biological or pathological process [10]. Various biomarkers are cause synaptic dysfunction and neurodegeneration [3]. AD is usu- already a part of everyday clinical routine. ally preceded by symptomatic pre-dementia stage termed mild Structural MRI is a recommended and widely used imaging cognitive impairment (MCI), in which the physician can observe method that can be used to assess atrophy in medial and lat- cognitive impairment that does not interfere with individuals’ eral temporal lobe, medial parietal cortices and hippocampi— functional abilities [4]. structures that are affected early and disproportionally in AD. There is a common public misconception that early diagno- Atrophy reflects the loss of neurons and can be seen clearly as sis of AD is not essential due to the current lack of a disease- disease progresses, but patterns of atrophy often overlap between modifying drug. But such diagnosis is of paramount importance. different dementia syndromes and changes can be very subtle in Firstly, it allows people with dementia and their caregivers to early stages. Furthermore, structural MRI is useful for the assess- ment of the vascular burden—an important co-morbidity in AD ∗ Both authors contributed equally to this review. [11]. Two other commonly used biomarkers of AD are analysis Permission to make digital or hard copies of part or all of this work for personal of cerebrospinal fluid (CSF) and functional brain imaging with or classroom use is granted without fee provided that copies are not made or 18 2-[ F]Fluoro-2-deoxy-D-glucose and positron emission tomog- distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this raphy (FDG PET). Lumbar puncture is performed to obtain CSF work must be honored. For all other uses, contact the owner /author(s). from which concentrations of A𝛽 , phosphorylated Tau and to- 42 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia tal Tau proteins can be measured. Reduction in concentration of © 2020 Copyright held by the owner/author(s). A𝛽 protein (due to increase in extracellular binding in the brain) 42 162 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Marjanovič and Perovnik in CSF can be observed decades before appearance of first cogni- 3.1 Eye movements and their alterations in tive symptoms, but A𝛽 concentration reaches plateau already in 42 AD the pre-symptomatic disease stage [12] and is thus not a suitable Unlike the other methods, described above, eye movements, as biomarker of disease progression. Furthermore, lumbar punc- tracked and recorded via eye tracker, present a sensitive, non- ture is an invasive procedure with a non-negligible percentage invasive, and inexpensive method [22, 23, 15], which allows for of mild complications such as back pain or headache, however testing in a simple and everyday-like setup. As such, eye track- the percentage of serious complications is very low (< 1%) in ing presents an ideal method for testing patients with cognitive specialized institutions [13]. FDG PET is a non-invasive brain decline, since the tasks they perform during testing are relatively imaging modality that provides information about synaptic dys- natural and thus easily comprehensible, without complicated in- function, which precedes atrophy, and is commonly used in early structions. Additionally, the method is appealing to the patients detection and differential diagnosis of dementia. Furthermore, also due to the fact that they are simply sitting comfortably in it also provides an important insight into disease progression front of a computer screen, while their head is typically stabilized [14]. Because FDG PET imaging involves radiation exposure, it through a chin rest, allowing them to relax their posture without is not recommended to be performed more than once per year. compromising the accuracy of the recording. Additionally, FDG PET is a relatively expensive procedure [11]. In healthy individuals, who are not experiencing any kind of In summary, while the current biomarkers are able to detect processing difficulties, the typical oculomotor behavior can be AD in the earliest stages, they are either invasive (e.g., lumbar described with a series of eye movement measures. Here, we offer puncture) or relatively expensive (e.g., MRI, FDG PET). A discov- a description of two of them as an example. When we, for example, ery of a reliable, noninvasive and inexpensive biomarker would look at a presented picture, search for an object or read a text in thus greatly advance the availability of early diagnosis of AD [15]. font of us, we continuously make rapid linear eye movements—so The search for such an alternative biomarker has already begun, called saccades, which can reach velocities as high as 500° per and the research of the past two decades has yielded important second [24]. During a saccade, the sensitivity to visual input is advancements. In the next paragraphs we offer a short overview reduced, thus we essentially do not obtain new information from of one such potential biomarker—eye movements, as tracked via our environment while our eyes are moving [25]. In order to eye tracker. In order to do so, we first need to shift our focus obtain this information, we make a series of stops in between the away from the most commonly defined features of AD. saccades—so called fixations, which typically last about 250ms [25, 20]. During this time our eyes remain relatively still, focusing on the information that is available in the momentary foveal 3 VISON IMPAIRMENTS IN ALZHEIMER’S vision (i.e., the center of the visual field, with the highest visual DEMENTIA acuity) [26]. The role of the saccades is thus to move our eyes onto a new region of the processed stimuli, where we make a fixation As reflected in the clinical diagnostic criteria for AD, described to bring new informaton into our foveal vision, and consequently above, the primarily addressed disorders of AD are the disorders into our attention. of cognitive functioning [1]. However, a common, yet largely The main reason why eye tracking can so readily be used for ignored feature of AD are also alterations in sensory capacity, an early detection of the neurodegenerative alterations is that particularly in visual processing [16, 17]. These are of extreme it allows for a simple investigation of complex viewing behav- importance especially when talking about timely diagnosis of ior that humans automatically engage in when they are driven the AD, since they are present already in the early stages of the by top-down, goal-directed processes. Given the intimate link symptomatic disease [16, 17]. Possibly, these changes are often between the eye movements and cognition, any alterations in overlooked due to the fact that they are not present in all types the typical oculomotor behavior can thus be used to infer AD- of visual processing. For example, visual acuity, which is most related changes in cognitive processing [27]. Carefully selected commonly tested when an individual initially complains that tasks that trigger complex viewing behavior, in which atten- their vision is not quite right, is typically no more impaired than tion and its allocation, inhibitory control, working memory, or in healthy elderly individuals [16]. But additional deficits can be decision-making are required to successfully accomplish a goal, observed in other, more subtle types of visual processing, such thus present an ideal testbed for early detection of the AD, since as contrast sensitivity (i.e., the ability to distinguish gratings all these processes are altered already in the early stages of AD of varying spatial frequencies at different contrast levels) [16], [20]. Importantly, such tasks are already well-defined and well- color discrimination (i.e., ability to distinguish different shades explored in the frame of studies with healthy participants in the of colors) [18, 19], and eye movements [19, 20]. filed of cognitive science. Here, we offer a short overview of the Despite the fact that these deficits are traditionally still not patient’s performance in three such tasks: visual search, natural dealt with in clinical environment [21], the last two decades of reading and antisaccade task. interdisciplinary research have brought to light numerous new findings, particularly about the eye movement alterations in AD. 3.1.1 Visual search task. In essence, visual search task is goal- This field of studies has recently been gaining more and more directed search for a target (e.g., a specific object) among a num- attention, and has since largely progressed along two lines of ber of distractors in an environment [27]. Compared to healthy research: while the first one deals with correlation of the eye control participants, patients with AD exhibit delayed target de- movement alterations and the disease severity, the second one tection [27, 20], longer fixation durations [20, 28] and longer and focuses on the applicability of the eye movement alterations for less systematic exploration [29, 30, 28], which is often described early detection of cognitive decline [e.g., 19, 20]. In the remainder as stochastic [29]. of this abstract, we will address the latter in more detail, and explore the potential of the eye movements as possible biomarker 3.1.2 Natural reading task. Despite the fact that reading is an for diagnosis of AD. activity in which (literate) humans engage in on an everyday 163 Does sight provide insight into Alzheimer’s dementia? Information society ’20, October 5–9, 2020, Ljubljana, Slovenia basis and without much effort, this is a very demanding cognitive tailored to detecting and monitoring the disease at its specific task [31, 32, 33, 34]. Successful reading process demands not only stages, and to the specific needs of the patients with dementia, simultaneous processing of different linguistic information (e.g., who require natural and simple tasks, which do no trigger any letter identification, morphologic and semantic processing), but discomfort or risk of misunderstanding the task instructions. also precise coordination, attention allocation and planning (e.g., where and when will the eyes move in the text) [33]. 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Vision screening for alzheimer’s dis- 33, 1–13. ease: prevention from an ophthalmologist’s perspective (there is more to vision than meets the eye). The Perma- nente Journal, 8, 1, 15. [22] Trevor J. Crawford, Steve Higham, Ted Renvoize, Julie Patel, Mark Dale, Anur Suriya, and Sue Tetley. 2005. In- hibitory control of saccadic eye movements and cognitive impairment in alzheimer’s disease. Biological Psychiatry, 57, 9, 1052–1060. issn: 0006-3223. doi: 10.1016/j.biopsych. 2005.01.017. 165 Patterns of Mental Behavior During Psychological Task Performance Aleš Oblak† University of Ljubljana Ljubljana, Slovenia oblak.ales.93@gmail.com ABSTRACT 2 METHOD 18 participants (10 females) gave their oral consent to participate Psychological tasks are one of the main instruments used in in the study. The average age of participants was 27.2 (SD = 2.9). experimental sciences of the mind. Recent meta-psychological All the participants were right-handed. Except for one, all the discussions have shed light on the phenomenology, research participants were current or former students of cognitive science. design structure, and generalizability of psychological tasks. However, it remains unclear how psychological task The average total number of years of education for participants performance modifies consciousness. Subjective reports on the was 15.8 (SD = 1.15). The participants were informed ahead of experience of psychological task performance were gathered. A time that they will be participating in a psychological study. constructivist grounded theory approach was employed for The participants sat in front of a laptop, displaying a blank analysis. A number of patterns of mental behavior and screen. Throughout the study, the researcher sat behind them. experiential states associated with psychological task They received the following set of instructions: There will be an performance are discussed. image displayed on the computer screen for 10 seconds. I would like you to observe the image without doing anything with it or KEYWORDS performing any mental gestures upon it. All you have to do is to Psychological task, constructivist grounded theory, mental focus on it. behavior A randomly selected stimulus appeared on screen. There were four possible stimuli. They were all composed of a grid with some boxes filled in black, and other boxes left empty (i.e., 1 INTRODUCTION white). After 10 seconds elapsed, the participants were prompted Psychological tasks are one of the main instruments used in to report on their experience of observing the stimulus. experimental cognitive science. They are typically relatively The researcher guided the participant through the subjective simple, computerized activities, whereby mental phenomena are report. Initially, the participant was asked to provide a rough isolated and made measurable [1]. It has long been understood overview of their experience of the observation of the stimulus. that psychological tasks constitute a culturally specific and Afterwards, the researcher guided the participants through each artificially constrained context of inquiry [2, 3]. Recent salient event that was mentioned in the initial overview. The discussions have attempted to add to the meta-psychological and participant was asked open-ended follow-up questions regarding anthropological understanding of psychological tasks by each event until a precise description of how it had been explicating the general phenomenology associated with the experienced was achieved. To promote a detailed account, the performance of psychological tasks [1], their formal structure as researcher consistently recapitulated parts of the subjective it pertains to their research designs [4], their generalizability [5] report under discussion. The descriptions were considered valid, and in what manner participants respond to them [6]. if they were grounded in a) bodily feelings; b) sensory It has been noted by Froese and colleagues that specific types modalities; c) mental gestures; and d) attitudes. Descriptions of of complex systems are characterized by the theory-experience theoretical concepts, folk psychological assumptions, or gap; i.e., we cannot claim a priori as to how the complex system metaphorical ideas were considered invalid. will modify the structure of consciousness of the individual After each mental event was grounded in a concrete interacting with it [7]. In its original formulation, the theory- description of experience, a debriefing interview about the experience gap refers to novel systems, such as virtual reality. interview itself was conducted. The participants were asked However, it has recently been shown that psychological task about how they experienced the interview and the research performance is associated with a relatively large array of setting. If the participants reported an awareness of confabulating unexpected experiential states as well [8]. a specific aspect of the report or a social distance from the The goal of this study is to contribute towards the general researcher, the sample was discarded. Three samples were meta-psychological understanding of interacting with a removed. The entire interview was recorded on an audio psychological task in a research setup; i.e., what is the experience recording device. of performing a psychological task as such, rather than a specific psychological task. As the purpose of the psychological task is to elicit a specific cognitive function, this study is interested in the 3 ANALYSIS patterns of mental behavior when participants are exposed to any In total, 15 admissible samples were gathered. The samples were experimental setup. analyzed according to the principles of constructivist grounded 166 theory [9]. The audio recordings were transcribed verbatim. Mind-wandering (MW) refers to situations in which Descriptions of theoretical concepts, folk psychological participants engage in mental behavior that is unrelated to the assumptions, and metaphorical ideas were removed. The data nominal task performance but is itself not oriented towards a were analyzed via coding: general descriptive tags were assigned task. Participants engage in remembrance (i.e., contemplating to the concrete subjective reports. In order to minimize bias, a various memories from their own life), reverie (i.e., engaging in meaningful code was assigned to each line of the interview. The fantastical stories about their own life), planning (i.e., thinking data were coded inductively: the codes emerged from the text about the future), and, interestingly, theorizing about the nature rather than from the scientific literature. Each category was given and purpose of the psychological research design and/or the a name and specified according to a) its salient algorithmic structure of the code running the task itself. MW was phenomenological properties; b) relationships to other observed 6 times (on average 0.4 times per participant). categories; and c) meaningful quotes from the transcripts. Finally, ambiguity (AM) refers to moments of disengagement The data were coded on two levels: a) relational and b) from any explicit mental behavior. Participants find themselves experiential. The former refers to the abstract relationships unsure as to what they are supposed to do. AM therefore amounts between types of mental behaviors relative to how the to an attitude of searching for the appropriate mental behavior. participants performed the task. The latter refers to the categories AM was detected 14 times (on average 0.93 times per constructed on the basis of subjective reports relative to participant). participants’ bodily feelings; sensory modalities; mental gestures, and attitudes as they pertain to individual mental 4.2 Experiential categories behaviors. Qualitatively, the most salient aspects of experience in relation As individual samples displayed a high degree of variability to mental behavior were the sense of agency and attentional (i.e., experience rapidly changed from moment to moment), each dispositions. Three experiential categories of sense of agency sample was assigned a number of both relational and experiential were induced from the raw data: categories. Thus, a given category may have appeared more than a) willful; once within a single sample. The number of categories assigned b) automatic; to each sample depended on the variability of experience and and c) vetoable. thus varied from sample to sample. For the sake of parsimony, Willful sense of agency refers to the experience where relational categories - where variability was the highest - were participants felt that a particular event that occurred in their grouped together into typical patterns of mental behavior. These awareness was the result of their action. In total, willful sense of patterns are presented in Section 5 in the form of grounded agency was observed 15 times (on average 1.0 times per theory. participant). Automatic sense of agency refers to the experience where participants felt that a particular event that occurred in their awareness was something that happened to them. In total, 4 RESULTS automatic sense of agency was observed 19 times (on average, 1.27 times per participant). Finally, vetoable sense of agency 4.1 Relational categories refers to situations where participants felt that a particular event Four categories of mental behavior were induced from the data: that occurred in their awareness was something that was a) nominal task performance; happening to them; however, they had the capacity to continue b) constructed task performance; to enact this event or terminate it. Vetoable sense of agency was c) mind-wandering; observed 15 times (on average 0.4 times per participant). and d) ambiguity. Attentional disposition is an aspect of experience that refers Nominal task performance (NT) refers to situations in which to an attitude taken in attention to a particular object of one’s participants’ phenomenology is congruent with the perception. Based on this attitude, the object itself may be phenomenology expected by the design of the task. In the case of experienced differently. Three experiential categories of the simple observation task used in this study, nominal task attentional dispositions were induced from the raw data: performance refers to experiential states that amount to a a) progressive; disengaged, receptive observation of the stimulus. NT was b) receptive; observed 13 times (on average 0.86 times per participant). and c) distant. Constructed task performance (CT) refers to situations in Progressive attentional disposition is an aspect of experience which participants deviate from the task that was created by the wherein participants experience themselves going towards the researchers. Phenomenologically-speaking, constructed task psychological task. While mostly attentional, this experience can performance is characterized by goal-oriented mental behavior, be so salient that it is experienced as a force, located beyond however, the goal itself is something that the participants one’s body, going forward or bodily sense of leaning forward. constructed anew. As participants had a background in cognitive Progressive attentional disposition was observed 24 times (on science, they constructed a novel task because they were average, 1.6 times per participant). Receptive attentional distrustful of the researcher’s instructions. Thus, the tasks that disposition is an aspect of experience wherein participants were typically constructed were associated with well-known experience the psychological task coming towards them. While cognitive functions (e.g., pattern recognition, geometric analysis mostly attentional, this experience can be so salient that it is of stimuli, working memory). CT was observed 12 times (on experienced as a force, located beyond one’s body, pulling them average 0.8 times per participant). 167 away from the task, or a bodily sense of leaning backwards. AM . The participants feel that the psychological task is too Receptive attentional disposition was observed 10 times (on complex to be solvable. This feeling may be associated with average 0.67 times per participant). Distant attentional negative emotional valence. Based on these reports, another disposition is an aspect of experience wherein participants pattern of mental behavior is conjectured: breakdown. Ex experience an attentional disconnect from the task. Commonly hypothesi, breakdown refers to the pattern of mental activity that described as “looking but not seeing,” this experience may be so begins with AM and tends towards the experience of salient that the psychological task fades from participants’ informational chaos. In these cases, individuals cannot tie the awareness. Distant attentional disposition was observed six psychological experience to a mental strategy known to them times (on average, 0.4 times per participant). from everyday life [1]. Depending on the task design, this outcome may be undesirable. 5 GROUNDED THEORY Individual states relative to the performance of the psychological 6 CONCLUSION task did not appear in isolation. Rather, within a single The study represents a continuation of qualitative inquiries into performance, participants underwent a number of states of the meta-psychology of psychological task performance (e.g., mental behavior. The manner in which states followed each other Morrison et al., 2019). A grounded theory is proposed that may formed a number of patterns. These patterns are outlined in this assist in future understanding of psychological tasks, in section. Six patterns of mental behavior relative to the particular, what is the dynamics whereby they isolate the performance of the psychological task were detected: intended cognitive functions or an unrelated self-imposed task. a) simple coalescence; b) complex coalescence; c) simple tangentiality; REFERENCES d) complex tangentiality; [1] Hazel Morrison, Shannon McBriar, Hilary Powell, Jesse Proudfoot, e) digression; and Steven Stanley, Des Fitzgerald and Felicity Callard, 2019. What is a psychological task? The operational pliability of “task” in psychological f) separation. On the basis of reports from the literature, another laboratory experimentation. Engaging Science, Technology, and Society pattern of mental behavior is conjectured: 5(1), 61-85. 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It refers to experiences of extreme 168 Vpliv posturalnih perturbacij na stresni odziv pri človeku Effects of Postural Perturbations on Human Stress Response Carolina Petrič Jernej Čamernik Gregor Geršak Jan Babič Laboratorij za nevromehaniko Laboratorij za nevromehaniko Fakulteta za elektrotehniko Laboratorij za nevromehaniko in biorobotiko in biorobotiko Univerza v Ljubljani in biorobotiko Institut Jožef Stefan in, Institut Jožef Stefan Ljubljana, Slovenija Institut Jožef Stefan Fakulteta za elektrotehniko Ljubljana, Slovenija gregor.gersak@fe.uni-lj.si Ljubljana, Slovenija Univerza v Ljubljani jernej.camernik@ijs.si jan.babic@ijs.si Ljubljana, Slovenija carolina.petric@gmail.com POVZETEK KEYWORDS Namen tega dela je bil opazovati stresni odziv, ki se pojavi takoj Electrodermal activity (EDA), postural perturbations, stress po motnji stabilnosti. Zanimalo nas je i) kako se stresni odziv spreminja s spremembo smeri posturalne motnje in ii) če pride response do prilagoditve po več (devetih) zaporednih posturalnih motnjah. Za oceno stresnega odziva smo uporabili meritev 1 UVOD elektrodermalne aktivnosti. Analiza je pokazala, da se splošno vzburjenje ni spremenilo s spremembo začetne smeri motenj. Ko Zmožnost ohranjanja stabilne, pokončne drže med soočanjem z motnjami ravnotežja je kritična komponenta vsakdanjega pa se je smer posturalne motnje spremenila iz naprej v nazaj, so se udeleženci odzvali hitreje in močneje. Pri ponavljajočih se življenja. Motnje ravnotežja so lahko zunanje (npr. neravna posturalnih motnjah se je splošno vzburjenje zmanjšalo, podlaga, slaba osvetljenost okolice, obutev) ali notranje (npr. udeleženci pa so se po deveti zaporedni motnji odzvali hitreje in stanje ravnotežnega organa, posledice starostnih degenerativnih močneje. Nobena sprememba v tej pilotni študiji ni bila bolezni, utrujenost, posledice zdravil). Padci in poškodbe, statistično pomembna. Znanje, pridobljeno s tem delom, povezane s padci, predstavljajo globalno skrb za javno zdravje prispeva k boljšemu razumevanju stresnega odziva človeka na posturalne naših starajočih se družb [1]. Za nadzorovanje stabilnosti in orientacije človeškega telesa motnje. skrbi posturalni nadzorni sistem. Posturalna orientacija je KLJUČNE BESEDE definirana kot sposobnost vzdrževanja primerne poravnave med deli telesa in poravnave telesa glede na okolje [2]. Posturalna Elektrodermalna aktivnost (EDA), posturalne perturbacije, stabilnost ali ravnotežje telesa je sposobnost nadzorovanja posturalne motnje, stresni odziv, motnje stabilnosti središča mase (ang. Centre of Mass – CoM) oz. projekcije CoM ABSTRACT glede na podporno ploskev (ang. Base of Support – BoS) [2]. Podporna ploskev zajema območje pod predmetom ali osebo, ki The purpose of this work was to observe the human vključuje vsako točko stika, ki jo predmet ali oseba naredi s psychophysiological stress response, which occurs right after a podporno površino in vso površino vmes. Te točke stika so lahko stability disturbance. We were interested in i) how the stress deli telesa (npr. stopala ali roke) ali predmeti (npr. stol, na response changes with the change in direction of a postural katerem oseba sedi) [3]. perturbation and ii) if there is any adaptation after several (nine) Center mase - CoM je definiran kot točka v središču celotne consecutive postural perturbations. Electrodermal activity was mase telesa [4]. Določimo ga kot uteženo povprečje centrov mas used to assess the stress response. The analysis showed that the vseh segmentov telesa. CoM ni fizična spremenljivka, ampak general arousal did not differ with the change in the initial virtualna točka v prostoru, ki je odvisna od položaja vseh delov direction of perturbation. However, when the direction of telesa. CoM je ključna spremenljivka, ki jo nadzira posturalni postural perturbation was changed from forward to backward, nadzorni sistem [4]. subjects reacted faster and more strongly. In recurrent postural Središče pritiska (ang. Centre of Pressure – CoP) je vsota vseh perturbations, general arousal decreases, and subjects respond sil in navorov, ki jih povzroča telo na podporno površino [2]. Pri faster and stronger after the ninth consecutive perturbation. Since izgubi nadzora položaja telesa se projekcija CoM premakne iz this was a pilot study and only four healthy volunteers mej podporne ploskve. Meje stabilnosti predstavljajo območje, participated, none of these results were statistically significant. znotraj katerega lahko telo ohrani stabilno lego brez dodatne The knowledge gained from this work contributes to a better spremembe BoS. understanding of human stress response to postural Predhodni dokazi kažejo, da se lahko po nestabilnosti pojavi perturbations. simpatična modulacija, ki podpira hipotetično vključenost avtonomnega živčnega sistema (AŽS) v posturalno kontrolo [5, 6]. Simpatična modulacija oz. kompenzacijski posturalni odziv 169 je po motnji stabilnosti pomemben za ohranjanje ravnotežja in pas, ki omogoča priklop jeklenice. Jeklenica je bila del sistema preprečevanje padca. za izvedbo posturalnih motenj z določeno silo, ki jo generirata Avtonomni živčni sistem se deli na parasimpatično in dva električna servomotorja (Festo model EMMS-AS-100 z simpatično živčevje. Fiziološke posledice aktivacije nazivnim navorom 5,69 Nm). V pasu je bil nameščen tudi aktivni simpatičnega živčnega sistema so npr. pospešeno bitje srca, optični marker, ki je bil del optičnega sistema Optotrak 3D pospešeno in bolj globoko dihanje, razširjene zenice, povečan Investigator (Northern Digital Incorporated, Kanada. Frekvenca krvni tlak, upočasnjena presnova hrane, zakrčenost mišic ter vzorčenja: 1000 Hz), s katerim ocenjujemo položaj približka povečana prevodnost kože [7]. Našteti pojavi so del stresnega centra mase udeleženca. odziva. Nacionalni institut za javno zdravje je stres definiral kot: Pred začetkom eksperimenta smo vsem udeležencem podali »… normalen odziv posameznika, kadar je začasno enotna navodila o njihovi nalogi, ki je bila, da v primeru porušeno njegovo ravnovesje (telesno ali duševno) posturalne motnje poizkusijo ohraniti svoj položaj na mestu, kjer zaradi notranjih ali zunanjih vplivov (stresorjev). stojijo. Merjenje se je začelo z dvominutno stojo na dveh Stresorji so lahko pojavljajo v različnih oblikah. Lahko pritiskovnih ploščah (Kistler Instrumente AG, Winterthur, so manjši (npr. gneča na cesti) ali večji (npr. smrt v Switzerland. Frekvenca vzorčenja: 1000 Hz) za zajem začetnega družini), zunanji (npr. kratek časovni rok za določeno stanja. Prva motnja (prvi poteg jeklenice) je bila prožena ročno, delovno nalogo) ali notranji (npr. skrbi, črne misli), ko smo sami ocenili, da je vrednost signala EDA, izrisana v negativni (npr. prometna nesreča) ali pa celo pozitivni realnem času, razmeroma konstantna (ni več sunkovito naraščala (npr. rojstvo otroka). Enak dogodek bo nekomu ali padala). Vsaka naslednja motnja je bila ročno prožena, ko se predstavljal stresor, drugemu pa spodbudo, odvisno od je udeleženec umiril (relativno gledano glede na začetno stanje posameznikove osebnosti, izkušenj.« [8] vrednosti EDA). Motnje so bile izvedene v smeri naprej – nazaj. Kot stimulus, ki sproži stresni odziv opazovane osebe, lahko Vsi udeleženci so skupno prejeli deset motenj. Smer začetne sile obravnavamo tudi posturalno motnjo, ki vpliva na premik osebe je bila naključna, dva udeleženca sta začela z motnjami naprej in iz ravnotežja. V tej študiji nas je zanimalo, kakšni so dva nazaj. Preostalih devet motenj je bilo izvedenih v nasprotno psihofiziološki odzivi človeka ob nepričakovanih motnjah smer od tiste, s katero so udeleženci začeli. stabilnosti, da bi potrdili domnevno vključenost AŽS pri Profil generirane sile električnih servomotorjev, prikazan na posturalnem nadzoru. sliki Slika 1, smo časovno razdelili na tri dele v razmerju 3:2:1, Oblikovali smo naslednji hipotezi: i) stresni odzivi se kjer v prvem delu sila narašča, v drugem delu je konstantna in v razlikujejo glede na začetno smer posturalne motnje (H1) in ii) tretjem pojema. Amplituda sile je določena z enačbo: stresni odziv se spremeni po več (devet) zaporednih motnjah 𝑚 enake amplitude in smeri (H2). Če bi hipotezi potrdili, bi 𝐹 = 𝑚 ∗ 𝑔 ∗ 𝑘 = 𝑚 ∗ 9,81 ∗ 0,11, (1) 𝑠2 pridobili še dodatne informacije o opazovani povezavi med stresom in posturalnim nadzorom. Ugotovili bi, kako sprememba kjer F predstavlja amplitudo sile v N, m je masa v kg, g je smeri posturalne motnje in kako ponavljajoče posturalne motnje gravitacijski pospešek v m/s2, k pa koeficient, ki predstavlja delež vplivajo na stresni odziv. telesne mase preiskovanega udeleženca in je brez enote. 2 METODE 2.1 EKSPERIMENTALNI PROTOKOL Štirje mladi odrasli (povprečna starost; standardni odklon (SD): 22,3 leta, SD = 2,4 leta), dva moška in dve ženski, so prostovoljno sodelovali pri eksperimentu. Vsi so bili zdravi, brez nevroloških in mišičnih posebnosti. Kandidati so bili seznanjeni s potekom meritev in podpisali so izjavo o prostovoljni in zavestni privolitvi po poučitvi. Pred prihodom udeleženca sta bili izmerjeni temperatura in Slika 1: Profil uporabljene sile generirane na električnih vlaga v prostoru (povprečna temperatura = 24,3 °C; STD: 0,5 °C, servomotorjih. povprečna vlaga 42,2 %; SD = 1,9 %). Udeležence smo stehtali (povprečna teža = 65,6 kg; SD = 14,3 kg) in nanje namestili Konstanta 0,11 izhaja iz ugotovitev študije [9], kjer so izvajali merilno napravo za merjenje elektrodermalne aktivnosti (EDA) podobne posturalne motnje in uporabili koeficiente od 2,75 % do Shimmer GSR Plus (Shimmer Sensing, Dublin, Ireland. 22 % telesne mase. V rezultatih so predstavili, pri katerem Frekvenca vzorčenja: 504,3 Hz). Elektrodi za merjenje EDA sta koeficientu mora po povzročeni sili oseba narediti korak, da bili nameščeni na proksimalni prstnici kazalca in sredinca ohrani ravnotežje. Mejna vrednost, ko osebi še ni potrebno njihove nedominantne roke. Za preprečevanje motenj v signalu narediti koraka, je glede na njihove ugotovitve znašala 0,11 za elektrodermalne aktivnosti zaradi drgnjenja prstov smo jim motnje v smeri naprej. Za motnje v smeri nazaj smo sami uporabljena prsta (sredinec in kazalec) stabilizirali z lepilnim preverili mejno vrednost po principu preizkušanja, ki pa se je trakom. Med nameščanjem merilnih naprav so udeleženci izkazala za identično smeri naprej. Izbrani vrednosti koeficientov odgovorili na nekaj vprašanj o svojem splošnem počutju, kar jim za smeri naprej in nazaj k(naprej) = 0,11, k(nazaj) = –0,11. je omogočilo, da so se lahko privadili na laboratorijsko okolje in prisotnost vseh naprav. Udeležencem smo namestili še prilagojen 170 Slika 2: Rezultati analize EDA pri protokolu menjava smeri Slika 3: Rezultati analize EDA pri protokolu ponavljajoče motnje. motnje. 2.2 OBDELAVA PODATKOV IN ANALIZA pojavijo v manj kot 9 s od začetka naraščanja) pa do padca na vrednost nič. Nastavili smo tudi zavračanje vrhov, ki so manjši Merilnik Shimmer GSR+ za merjenje EDA zajema upornost od 10 kože v kΩ, zato smo najprej naredili pretvorbo upornosti v % največjega vrha. Parametri, ki smo jih pridobili za posamezno opazovano motnjo: prevodnost (v µS). To smo naredili zato, ker je prevodnost v µS - Število SCR-jev na motnjo je mera trenutnega standardna veličina za opazovanje stresnega odziva. Zaradi vzburjenja udeleženca in je število vrhov signala razlik v tonični komponenti, ki so posledica različnih prevodnosti kože. Vrednost nekaj SCR/min nakazuje, da medosebnih lastnosti, smo celoten signal EDA normirali na je udeleženec miren, vrednost nad približno 20 SCR/min začetno vrednost. Vzorčna frekvenca, ki smo jo uporabili za pa nakazuje na stanje vzburjenosti [11]. zajem tega signala, je bila 1000 Hz, nato smo jo pred začetkom - Latenca je časovno trajanje med začetkom dražljaja in analize zmanjšali na 100 Hz. Sledi segmentacija glede na začetkom prvega odziva SCR (v sekundah). dovedene posturalne motnje. Segment je bil definiran kot - Amplituda SCR je razlika med največjo vrednostjo, ki jo območje od začetka motnje do začetka naslednje motnje. doseže posamezen vrh, in vrednostjo pred začetkom Za nadaljnjo analizo smo uporabili program Acqknowledge odziva oz. naraščanja signala EDA. Iščemo povprečno 4.1 (Biopac Systems Inc., USA), ki nam omogoča takojšnji izris, in največjo amplitudo. raznovrstne transformacije in specifične analize različnih bioloških signalov. Najprej smo ločili signal na fazično in tonično komponento s funkcijo »Derive Phasic EDA from 3 REZULTATI Tonic«, ki uporabi visokoprepustni filter z mejno frekvenco 0,05 Hz, da pridobi novo fazično komponento iz podanega začetnega 3.1 Vpliv spremembe smeri posturalne motnje toničnega signala [10]. Uporabili smo algoritem »Locate SCRs«, na stresni odziv ki na podlagi pragovne vrednosti signala (v našem primeru 0,02 µS) v fazični komponenti poišče odzive prevodnosti kože (SCR), Za preverjanje H1 smo prvo in drugo motnjo izvedli v različnih, ki so definirani od trenutka, ko pulz EDA prekorači to pragovno nasprotujočih si smereh. Dva udeleženca sta začela z motnjo v vrednost v omejenem časovnem intervalu (npr. pulzi, ki se smeri naprej, nato pa sta prejela vse preostale motnje v smeri nazaj. Preostala dva udeleženca sta naredila ravno obratno. Na 171 sliki Slika 2 so prikazani rezultati analize EDA pri protokolu smo nakazali smernice za nadaljnje raziskave. Za zanesljivejšo menjava smeri motnje. Prva vrsta prikazuje število odzivov in bolj statistično značilno študijo bomo testirali več oseb. prevodnosti kože (SCR) [št. SCR/motnjo], druga vrsta prikazuje Eksperiment bi v prihodnje lahko razširili še z motnjami v smeri povprečno amplitudo odzivov prevodnosti kože (SCR) [µS], levo-desno in tako upoštevali, da se oseba v realnem okolju giblje tretja vrsta prikazuje največjo amplitudo odzivov prevodnosti v vseh smereh. Znanje o spremembah stresnega odziva med kože (SCR [µS]), četrta pa latenco [s] prvega odziva SCR. Vsi soočanjem s posturalnimi motnjami lahko prispeva k izboljšavi grafi prikazujejo vrednosti, ločene za prvo in drugo dovedeno aplikacij meritev stresa v realnem okolju in odpira nove možnosti motnjo. Parametri v prvem stolpcu so rezultati udeležencev, ki uporabe ter razumevanja človeškega telesa. so prejeli prvo motnjo v smeri nazaj. Drugi stolpec vsebuje rezultate udeležencev, ki so prejeli prvo motnjo v smeri naprej. ZAHVALA Stopnja splošne psihofiziološke vzburjenosti se s spremembo To delo je bilo financirano iz programa EU za raziskave in smeri začetne motnje ni razlikovala. Kljub temu pa vidimo, da so inovacije H2020 (št. 731540, An.Dy). se udeleženci ob spremembi naprej – nazaj pri drugi motnji hitreje in močneje odzvali, na kar nakazujeta zmanjšana latenca in večja vrednost stresnega odziva. LITERATURA [1] W. H. Organization, “Falls,” 2018. [Online]. Available: 3.2 Vpliv ponavljajočih posturalnih motenj na https://www.who.int/news-room/fact-sheets/detail/falls. [Accessed: 05- stresni odziv Jun-2019]. [2] D. A. Winter and PEng, “Human balance and posture control during Na vsakega udeleženca je bilo v eni smeri (naprej ali nazaj) standing and walking,” Gait Posture, vol. 3, no. 4, pp. 193–214, Sep. 1995, doi: 10.1016. izvedenih devet zaporednih posturalnih motenj iste amplitude, za [3] Physiopedia, “Base of Support.” [Online]. Available: https://www.physio- preverjanje H2. Ker je bila med prvo in drugo motnjo prisotna pedia.com/Base_of_Support. [Accessed: 31-May-2019]. sprememba smeri, smo za analizo ponavljajočih se motenj iste [4] A. P. Shumway-Cook and M.H. Woollacott, Motor control: translating research into clinical practice, 4th ed. 2012. smeri vzeli drugo in deseto izmed vseh motenj, ki predstavljata [5] B. E. Maki and R. S. Whitelaw, “Influence of expectation and arousal on prvo in deveto motnjo v isto smer (naprej ali nazaj). Na sliki center-of-pressure responses to transient postural perturbations.,” J. Vestib. Res. , vol. 3, no. 1, pp. 25–39, 1993. Error! Reference source not found. so prikazani rezultati [6] K. Sibley, “Autonomic Contributions in Compensatory Balance Control,” analize EDA pri protokolu ponavljajoče motnje. Prva vrsta 2009. prikazuje število odzivov prevodnosti kože (SCR) [št. [7] Elaine Nicpon Marieb, Human Anatomy & Physiology, 7th ed. New York: Pearson Prentice Hall, 2007. SCR/motnjo]. Druga vrsta prikazuje povprečno amplitudo [8] Nacionalni inštitut za javno zdravje, “Stres,” 2014. [Online]. Available: odzivov prevodnosti kože (SCR) [µS]. Tretja vrsta prikazuje https://www.nijz.si/sl/stres. [Accessed: 30-May-2019]. [9] J. Čamernik, M. Azad, L. Peternel, Z. Potocanac, and J. Babič, “Staying največjo amplitudo odzivov prevodnosti kože (SCR [µS]). Četrta on your feet: the effectiveness of posture and handles in counteracting vrsta prikazuje latenco [s] prvega odziva SCR. Vsi grafi balance perturbation,” Ergonomics, vol. 62, no. 5, pp. 657–667, 2019, doi: prikazujejo vrednosti ločeno za prvo in drugo dovedeno motnjo. 10.1080/00140139.2018.1559363. [10] J. Mariah Kremer, A. J. Macy, E. Peterlin, and B. Systems, Parametri v prvem stolpcu so rezultati udeležencev, ki so prejeli “AcqKnowledge ® 4 Software Guide For Life Science Research ponavljajoče motnje v smeri naprej. Drugi stolpec vsebuje Applications Data Acquisition and Analysis with BIOPAC Hardware Systems Reference Manual for AcqKnowledge ® 4.” Biopac Systems, rezultate udeležencev, ki so prejeli ponavljajoče motnje v smeri Inc., p. 805, doi: 10.7-10.11. nazaj. [11] S. Ranogajec and G. Geršak, “Measuring site dependency when measuring skin conductance,” Proc. Twenty-third Int. Electrotech. Comput. Sci. Splošna vzburjenost se je po devetih zaporednih motnjah Conf. , pp. 155–158, 2014. zmanjšala ne glede na smer perturbacije. Zmanjšanje splošne vzburjenosti je bilo manjše ob perturbacijah v smeri nazaj. Udeleženci so se hitreje in močneje odzvali na stimulus po deveti zaporedni motnji, na kar nakazujejo povišana povprečna in največja amplituda ter zmanjšana latenca. 4 RAZPRAVA Rezultati prvega dela nakazujejo, da so bili udeleženci po drugi motnji bolj vzburjeni, če so najprej izkusili posturalno motnjo v smeri naprej in nato še v smeri nazaj. Sklepamo, da je vzburjenost narasla po motnji v smeri nazaj, zato ker udeleženci niso imeli vizualnega nadzora nad okolico v smeri premika. Vizualni nadzor (vid) zagotavlja dodatne informacije o dogajanju v okolici. Iz rezultatov drugega dela sklepamo, da se po deveti zaporedni posturalni motnji vidi adaptacijo udeležencev na to posturalno motnjo. Zaradi majhnega števila udeležencev v tem pilotskem eksperimentu so naši rezultati omejeni in niso bili statistično značilni. Nekateri parametri sicer nakazujejo razlike med spremembo smeri posturalne motnje in izvajanjem več zaporednih posturalnih motenj, vendar ne moremo nobene hipoteze potrditi ali ovreči. Z eksperimentom 172 Facial skin temperature during deception Blaž Počervina Ajda Centa Gregor Geršak Fakulteta za elektrotehniko Pedagoška fakulteta Fakulteta za elektrotehniko Univerza v Ljubljani Univerza v Ljubljani Univerza v Ljubljani Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija blaz.pocervina@fe.uni-lj.si centajda@gmail.com gregor.gersak@fe.uni-lj.si ABSTRACT 2 METHOD Measuring peripheral tissue temperature is a well-known Research is based on an experiment with various measurements methodology to assess different physiological states of a body. It of physiological parameters. As a baseline method for is also widely used in a clinical environment. On the other hand, psychophysiological measurements, electrodermal activity measuring facial skin temperature for the identification of the measurements were used [9–12]. In the experiment volunteered psychological state of a person is not so common. This article 24 healthy participants, of those 15 men and 9 women aged from will provide information on non-contact measurements of facial 20 to 45 years old 23,9 ± 5,0. After reviewing the measured temperature in comparison with established psychophysiological parameters, we included data from 9 persons in further analyzes, measuring systems (electro-dermal activity and heart rate) for 24 because, due to incomplete data or inadequately measured participants. The experiment consisted of two different states of parameters. Monitoring parameters were: electrodermal activity, cognitive loads which were expressed through the narration of a skin temperature, and heart rate. Psychological evaluations were true and untrue story. During a narration, on selected regions of done through interviews and standardized STAI-X1 agitation interest (ROI), subjects were monitored using a thermographic questionnaires. camera. Although the results did not show statistically significant differences between the true and untrue story for facial thermal 2.1 ELECTRODERMAL ACTIVITY measurement (in inter-person and intra-person comparison), Electrodermal activity (EDA) is a dermal property that is caused some differences did appear. Results of this study showed, a by different responses in electrical characteristics of the skin critical approach using information on a camera's accuracy, [13]. EDA has two components, the skin conductance level human skin properties, and other technical concerns) is needed (SCL) and skin conductance response (SCR). SCL value when using facial temperature measurements with a describes the level of person psychological excitement, and SCR thermographic camera for a reliable evaluation of different is the number of responses to the stimulus. The peak amplitude psychological states or loads. is typically reached within 1 to 3 s after the onset of the response [14]. EDA was measured with Biopac MP150 system (BIOPAC KEYWORDS Systems, Inc., USA) and unit Biopac GSR 100C connected to Psychophysiology, thermal imaging, facial temperature, silver electrodes on index and ring finger pads of nondominant hand as shown in figure 1. EDA data was processed by BIOPAC deception AcqKnowledge 5.0 software. 1 INTRODUCTION TO THERMAL IMAGING Historically, body temperature measurement for monitoring illness was very important. In early examinations, physicians observed mud when applied to the skin, on areas over the tumor mud was drying faster. First clinical thermometer was developed by Carl Wunderlich in 1868 and its principle is still in use [1]. Thermal imaging camera was invented by Hungarian physicist Kalman Tihanyi in 1929 for anti-aircraft defense in Britain [2]. Firstly thermal imaging cameras were long been in use for specialized law enforcement and military applications and soon later by the fire services [3]. A major development of electronic sensors for infrared radiation was in the early 1940s with indium Figure 1: Illustrated human hand with corresponding antimonide, and the first medical images were made in London signals measured on finger pads. Electrodermal activity on in 1959 – 1961 by a technique called thermogram [1]. Articles the index and ring finger, heart rate on the middle finger, with thermal imaging correlating of psychophysiology are not so and skin temperature on the little finger common but some studies have proven that with thermal imaging one can detect deception or lie with great accuracy [4–8]. 173 2.2 SKIN TEMPERATURE neutral questions designed to relax participant. During this period participant also acclimatizes to room temperature. Skin temperature depends on the blood flow to the subcutaneous Participant is asked to tell two stories, one true and the other un- tissue. It may also depend on external factors such as exercise, true. The stories should last for a maximum of 2 minutes each ambient temperature, or medical condition. The temperature was and should relate to the events of participants previous day. The measured on a little finger pad of the non-dominant hand (Figure participants choose the order of true and untrue stories by 1). Contact temperature measurements were done with Biopac themselves. Before storytelling, a thermographic camera is set to SKT 100C connected to the thermocouple. Contactless skin recording. The recording was started remotely via a computer, temperature measurements were done with a black-body eliminating the disturbance of the experimenter. After calibrated Flir 650sc camera (FLIR Systems, USA). Camera uses storytelling was completed, participants revealed which story a microbolometer type of detector with a resolution of 640 x 480 was true and which not, at the same time, experimenter stopped pixels. The camera was positioned 1 meter in front of the all measurements. At the end of the experiment, participants re- participant. Emissivity was set to 0.98 [15]. We have analyzed solved the STAI-X1 agitation questionnaire. three main regions on the face. Size of regions of interest (ROI) were 2512 pixels for the forehead, 445 pixels for the nose, and 710 pixels for cheeks as seen in figure 2. Sampling frequency was set to 15 frames per second. Temperature was recorded as mean value with standard deviation for each ROI last 100 frames of each story and analyzed with FLIR ResearchIR Max software. Figure 3: Block diagram of experiment flow 3 RESULTS Measurements for forehead and nose were calculated with statistical Wilcoxon signed-rank test. Results showed that forehead temperature between untrue story (Mdn = 35.13) and Figure 2: Capture from video taken with Flir 650sc, marked true story (Mdn = 35.17) does not show statistically significant with positions of ROIs (red - forehead, blue - nose, green – cheeks) differences, Z = –0.451; p < 0.652; r = 0.101. Also, temperature of a nose between untrue (Mdn = 28.54) and true (Mdn =28.53) 2.3 HEART RATE did not show statistically significant differences Z = –0.568; p < 0.570, r = 0.127. For temperature of the cheeks we used two- The heart cycle is the action of the human heart from one tailed test for the dependent samples which showed us there is no heartbeat to another. The cardiac cycle consists of two periods of statistical difference between the untrue story M = 34.04; SD = time when the heart muscle relaxes and fills with blood (diastole) 1.77) and true story (M = 34.07; SD = 1.60) t(8) = –0.214; p = and the time of intense contraction and pumping of blood 0.836. (systole). Heart rate is stable in a healthy adult at a rate of For the EDA, two-tailed paired t-test did not show statistical between 60 and 100 beats per minute. Heart rate was measured difference between untrue story (M = 6.22; SD = 3.03) and true with Biopac module PPG 100C and an optical sensor placed on story (M = 5.78; SD = 2.59) t(8) = 0.627; p < 0.548. the middle finger pad of the nondominant hand (Figure 1). Heart For the finger temperature calculated with statistical rate and heart rate variability were processed with BIOPAC Wilcoxon signed-rank test we did not find statistical difference AcqKnowledge 5.0 software. between untrue story (Mdn = 24.49) and true (Mdn = 24.88) story, Z = –1.035, p < 0.301, r = 0.231. Also, we did not find 2.4 EXPERIMENTAL SETUP statistical difference for heart rate between untrue story (Mdn = Prior measurements, the experimenter records the temperature of 95.66) and true (Mdn = 93.12) story, Z= –0.339; p < 0.734; r = the room, prepares a statement, psychological questionnaires, 0.0759. and calibrates the electrodes to measure the electrodermal activity of the skin. Participant is invited to the room and is asked to turn off cellphone and any other potentially disturbing factors. 4 DISCUSSION Experiment begins with an introduction interview, sensors The major limitations of this study are: i) complexity of the placement on the participants hand (Figure 1), and STAI-X1 psychological phenomena under observation (lying is difficult to agitation questionnaire followed by the experimenter's general induce), ii) moving artefacts due to the physical movement of the 174 face, iii) small number of participants, errors in measurements [4] S. B. Hernán, B. H. L. Sandra, E. N. Carlos, and R. P. Andrés, (EDA electrodes, calibration interval of IR camera). “Detección de mentiras por medio del análisis de imágenes térmicas del Detecção de mentiras por meio de análise de imagens térmicas do,” Measurements were performed with different techniques to vol. 26, no. 44, pp. 47–59, 2016. prove different psycho-physiological responses between true and [5] S. Yue, K. Harmer, K. Guo, K. Adams, and A. Hunter, “Automatic untrue storytelling. The sample of 24 participants decreased to a blush detection in ‘concealed information’ test using visual stimuli,” total of 9 participants due to incomplete data or inadequately Int. J. Data Mining, Model. Manag., vol. 6, no. 2, pp. 187–201, 2014. [6] I. Pavlidis, N. L. Eberhardt, and J. A. Levine, “Seeing through the face measured parameters. For thermal camera measurements, we of deception,” Nature, vol. 415, no. 6867, pp. 35–35, 2002. excluded data of persons wearing glasses. Glass is not [7] D. A. Pollina et al., “Facial skin surface temperature changes during a transparent for IR waves, and the method for measuring ‘concealed information’ test,” Ann. Biomed. Eng., vol. 34, no. 7, pp. 1182–1189, 2006. minimum temperature of a nose compromised the measurements. [8] P. Tsiamyrtzis, J. Dowdall, D. Shastri, I. T. Pavlidis, M. G. Frank, and Also, there was a lot of face movement present in IR video and P. Ekman, “Imaging facial physiology for the detection of deceit,” Int. this made it difficult to determine temperature of an ROI. In some J. Comput. Vis., vol. 71, no. 2, pp. 197–214, 2007. cases, camera performed calibration and focus corrections when [9] N. Gržinič and G. Geršak, “Estimation of measuring uncertainty in psychophysiological measurements due to participants anxiety (Slo: recording in this case we excluded measurements for those Ovrednotenje merilne negotovosti v psihofizioloskih meritvah),” participants. For EDA measurements we excluded participants Elektroteh. 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Biol., vol. 18, no. 5, p. 307, Sep. 1973. 175 Cognitive, Psychological and Social Influence on Spread of COVID-19 Gašper Slapničar Vito Janko Tine Kolenik gasper.slapnicar@ijs.si vito.janko@ijs.si tine.kolenik@ijs.si Jožef Stefan Institute, Jožef Stefan Jožef Stefan Institute Jožef Stefan Institute, Jožef Stefan IPS Jamova cesta 39 IPS Jamova cesta 39 Ljubljana, Slovenia Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Mitja Luštrek Matjaž Gams mitja.lustrek@ijs.si matjaz.gams@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT section 3 and describe the data in Section 4. We continue with the methodology and experimental setup in Section 5, and conclude We investigated and confirmed the hypothesis that cognitive, with results and discussion in Section 6. psychological and social features of citizens in each country in- fluence the spread of COVID-19 more than any other semantic feature group. Additionally, we investigated five sub-hypotheses 2 RELATED WORK in regards to socio-psychological traits of people and the spread We focused on COVID-19 related work that deals with some prop- of COVID-19, confirming two and rejecting three. Finally, we at- erties of different world regions (typically countries) and com- tempted to obtain deeper understanding of our results by finding pares them to a target variable related to the spread of COVID-19 which individual features within the social psychology group are in that region – with the goal of establishing the relationship most important. between the two. Many authors defined the spread of the disease in different KEYWORDS ways. Most commonly researchers simply used the number of psychology, sociology, covid-19, machine learning, feature analy- daily infections as the metric, which has the weakness of being sis biased towards countries with higher population, but can be normalized per capita [1]. Some other options are also possible, 1 INTRODUCTION such as computing the reproductive rate of the virus, as proposed Since the spring of 2020, Coronavirus disease 2019 (COVID-19) by Gupta et al. [6]. has increasingly influenced our daily lives. The first wave of The country properties used to investigate the influence on infections started to manifest globally around March, and dif- virus spread were also varied. Most commonly, weather attributes ferent countries reacted differently and with different amounts were investigated [6], as well as indicators of development [1] of success in order to stop the early exponential growth. Coun- and demographics [8]. tries differ from one another in many aspects, such as weather, In terms of machine learning (ML) methods, classical regres- demographics, development, economic strength, etc. Another im- sion (e.g., linear regression) was used predominantly [6], while portant but often overlooked difference between countries is in others used traditional statistical approaches [8], testing for sta- the cognitive, psychological and social features of their citizens. tistically significant correlation between features and target vari- We argue that these are some of the most important factors that ables. might influence the spread of COVID-19, as they in turn influ- Despite the large amount of research conducted in regards ence how much people spend time with each other, how often to COVID-19, the aspect of cognitive, psychological and social they attend social and cultural events, etc. Thus, we focused on influence on the potential spread of COVID-19 has been poorly analysing these features in terms of their influence on spread of researched thus far, to the best of our knowledge. We aim to COVID-19 and their importance compared to other groups of investigate and highlight the importance of the aforementioned features. Additionally, we investigated the importance of indi- influences and hopefully motivate more researchers to consider vidual features that comprise the category of cultural features in this important area. an attempt to investigate if there is a single defining trait that dominates others. 3 RESEARCH HYPOTHESES The rest of this paper is structured as follows: we first inves- Unlike the various different influences on COVID-19 spread that tigate the related work in Section 2, then we list hypotheses in related works focused on, the aim of this study was to concentrate Permission to make digital or hard copies of part or all of this work for personal on human behavior in terms of their social psychology, or interac- or classroom use is granted without fee provided that copies are not made or tion between their cognitive and psychological features and their distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this social behavior. Generally, we believe that these significantly work must be honored. For all other uses, contact the owner /author(s). affect COVID-19 spread and should therefore be investigated to Information society ’20, October 5–9, 2020, Ljubljana, Slovenia further understand not only this particular pandemic, but the © 2020 Copyright held by the owner/author(s). influence of human behavior on pandemic in general. 176 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Slapničar, et al. Our primary research hypothesis is that human behavior sta- their group behavior. They have been found to correlate with a tistically significantly affects COVID-19 spread. Furthermore, we number of social phenomena (security, progress, environmental have five secondary hypotheses: outcomes, etc.) [7]. HCDT includes the following dimensions (we did not include Power distance as it did not relate to our (1) People with higher tendencies for social activities (higher goal of finding data that describes phenomena that lie between extraversion) correlate with higher COVID-19 spread. individual and group behavior): (2) People with higher tendencies for social compliance (higher agreeableness) correlate with lower COVID-19 spread. (1) Individualism-collectivism: describes how citizens of a (3) People with higher tendencies for being careful (higher country prefer and care for their in-group. conscientiousness) correlate with lower COVID-19 spread. (2) Uncertainty avoidance: describes how averse citizens of a (4) People with higher tendencies for group consideration country are to uncertainty. (lower individualism) correlate with lower COVID-19 spread. (3) Long-term orientation: describes how traditional citizens (5) People with higher tendencies for desire gratification (higher of a country are in terms of solving society’s questions indulgence) correlate with higher COVID-19 spread. and their proclivity for change and adaptation (higher score means more long-term thinking, more adaptation To investigate our research hypotheses, we turned to data and change). repositories with psychological, cognitive and social features (4) Indulgence: describes the degree to which citizens of a across countries. Since our final dataset will contain other fea- country seek desire fulfilling behavior. tures as well, those will be also investigated. The next section (5) Task- vs. person-orientation: describes preference of citi- describes this data. zens of a country towards tasks versus towards people. 4 DATA Data on B5 questionnaire answers, which was collected from As our aim was to use ML algorithms to investigate the potential Open-Source Psychometrics Project’s public database [9] (un- relationship between cognitive, psychological and social features der "Answers to the IPIP Big Five Factor Markers"), had to be of citizens and the spread of COVID-19 on per-country basis, additionally pre-processed for this research. We processed the we had to obtain and structure suitable data. The cognitive, psy- answers to the questionnaire to get individual personality pro- chological and social features were used as input features and files with the five dimensions for every person. Then we filtered were obtained for as many countries as possible. The spread of the data by only keeping the countries where we had 100 individ- the virus itself was modelled using several binary classes, which uals answering the questionnaire. Afterwards, we averaged the were the targets of our classification. scores by countries to get group personality profile, each country having five dimensions. 4.1 Features on social psychology Finally, we also considered data on levels of a nations’ strength of social norms – referred to as (cultural) tightness-looseness. To research our hypotheses, we did a limited literature review We used the tightness measure from Gelfand and colleagues [3]. to find data spread between features that describe individual The measure captures the strength of norms in a nation and the behavior and features that describes group behavior of societies tolerance for people who violate norms. The final dataset we as a whole. We selected three frameworks with which to work constructed contains 59 countries (meaning 59 instances) with in this research. To account for individual behavior, the Big Five 11 features. personality traits model [5] was selected, along with a feature The dataset can now be related to the hypotheses: 1) for sec- on preferred interpersonal distances [11]. To account for group ondary hypothesis 1, extraversion will be used for correlation; 2) behavior, Hofstede’s cultural dimensions theory [7] was selected. for secondary hypothesis 2, agreeableness will be used for corre- The Big five personality traits model (B5) identifies five or- lation; 3) for secondary hypothesis 3, conscientiousness will be thogonal dimensions which supposedly reflect an individual’s used for correlation; 4) for secondary hypothesis 4, individualism- personality and psyche. B5 is measured with a questionnaire. collectivism will be used for correlation; 5) for secondary hypoth- Extensive research has found significant statistical connections esis 5, indulgence will be used for correlation. with a number of human behaviors (decision-making, crime, vot- ing, health behavior, educational outcomes, etc.) [2]. B5 includes 4.2 Virus spread classes the following dimensions: We chose three distinct binary classes, each having two possible (1) Openness: describes how inventive or curious someone is. values: a country is considered positive if its infection rate, given (2) Conscientiousness: describes how careful, efficient or or- the chosen metric, is faster than half the countries analyzed. The ganized someone is. class value was always computed in country-specific time frame, (3) Extraversion: describes how outgoing or energetic some- starting when the testing was adequate in a country according one is. to the recommendation given by the World Health Organization (4) Agreeableness: describes how friendly or compassionate (WHO), and ending when at least 3 countermeasures of sufficient someone is. intensity were applied. This intensity was marked with an integer (5) Neuroticism: describes how sensitive or nervous someone in the range from 0 to 4 in the Oxford Covid-19 Government is. Response Tracker [12], and we took value 2 as the threshold. Data on preferred interpersonal distances comes from human spatial behavior research [11] and describes how comfortable 4.2.1 Daily number of infections (daily average). The first calcu- people are in regards to different distance boundaries when in lated metric was the daily number of infections, averaged over contact with other people. the appropriate time interval and normalized based on the coun- Hofstede’s cultural dimensions theory (HCDT) identifies six try population. This metric is the most intuitive and commonly orthogonal dimensions that describe a country’s values that drive reported. 177 Cognitive, Psychological and Social Influence on Spread of COVID-19 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia 4.2.2 Reproductive rate. The reproductive rate 𝑅 is a metric it computes how much each feature decreases the weighted im- 0 commonly used by virologists to determine the severity of an purity in this tree. This impurity decrease is then summed up infection. Simply put, it estimates how many new infected are over all the trees in the forest to form the feature importance. generated by each currently infected. We then summed feature importances within each previously To estimate the reproductive rate we used the SIR model [10]. defined group to compare the aggregate importance of groups. For details on the computation of the values, we refer the reader This was done for each of the three virus spread classes. to the original paper. 5.2 Individual feature importance 4.2.3 Exponential shape. The last metric we calculated was the Once we estimated feature groups importance, we turned our shape of the infection time series. An exponential shape indicates focus to analysis of individual features within social psychology that the number of infections is raising fast, and is likely to group. We investigated whether an individual or small set of continue. To determine if the growth is exponential, we fitted features dominate a group in regards to importance, or is the both a linear and an exponential curve to the data. After both importance rather evenly spread. We did this for each of the three were fitted, the one with the lower error was chosen as the better classes using three different methods. Additionally, this gives us fit. If the exponential fit was better, the class value for this metric information about specific best features within the group, which was positive. allows for potential expert interpretation. Once the class was determined, we could split the countries into infected, non-infected and those for which we do not have (1) RF feature importances: First, we again used the out- enough data, based on each of the three classes. An intuitive of-the-box feature importances of RF to compare the im- display of the split is shown in Figure 1, where countries are portance of individual features. colored based on the number of positive virus spread classes. (2) Statistical testing: Second, we used statistical tests de- pending on the type of feature (continuous, categorical, binary, normally distributed, non-normally distributed). The feature values of countries positive with respect to a class were compared to those negative with respect to a class. We used the T-test, Mann-Whitney U-test and Fisher- exact test, respectively, for continuous normal features, continuous non-normal features, and binary features. (3) Wrapper method: Third, we developed a custom feature selection wrapper method similar to the one used in our related work [4], which did the following: the features were first sorted using RF feature importance (as before). Then, if two features were correlated (Pearson coefficient > 0.7) we discarded the lower ranking one. We started by Figure 1: All countries, colored based on how many infec- using only the best feature for the classification. Then, we tion classes are positive. If all of them are positive, the iteratively added the next best one, but only kept it if it did color is light red, and conversely gets darker for every neg- not decrease the classification accuracy by more than two ative one. Countries without sufficient data are gray. Note percentage points. This method improves upon the first that the data is from spring 2020, showing only the early one by considering internal correlations between features. spread. The five secondary hypotheses were investigated using corre- lation analysis, by computing the correlation between the values 5 METHODOLOGY of the selected individual feature relevant for the hypothesis, and the daily average class. We did this to get a deeper understand- We first focused on testing our hypothesis of social psychology ing and potentially new knowledge of exactly which features feature group being among the most important in the spread of influence acceptance or rejection of our hypotheses. COVID-19 compared to other feature groups describing a country. After confirming our initial hypothesis, we then investigated 6 EXPERIMENTS AND RESULTS importance of individual features within this group. Aggregate RF feature importances for each group and each class 5.1 Feature group importance are given in Table 1. Looking at the average importance, we see that the social psychology group of features proved the most We obtained over 100 different country-describing features in important, alongside development, confirming our initial hypoth- order to compare them against the social psychology group, and esis. to investigate our primary hypothesis, which was that the so- The importances of top 5 individual features within the social cial psychology group is highly important. To do this, we first psychology group for all three classes is given in Table 2. The grouped all other individual features into the following semantic importances were evaluated using the three different feature groups: weather, travel, health, economy, development, geogra- importance methods described previously. phy, countermeasures. We then evaluated the importance of each Finally, the evaluation of our initial secondary hypotheses feature group using a Random Forest (RF) classifier. The model using correlation analysis is given in Table 3. was trained using all the features and individual feature impor- tances were obtained out of the box via the feature_importance 7 CONCLUSION property of the model, which is available in the scikit-learn im- plementation. In summary, this metric trains an RF classifier We investigated the cognitive, psychological and social influ- consisting of a number of different trees. When training a tree, ence on spread of COVID-19. Comparing against other semantic 178 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Slapničar, et al. Table 1: Aggregate feature ranking using RF feature score. showing high correlation between extroversion and individu- Values are normalized (sum to 1). alism and higher virus spread. This shows that the cognitive, psychological and social features are among the most important in relation to spread of COVID-19 and should be investigated Repr. rate Exp. Daily avg. Average more thoroughly. Weather 0.09 0.08 0.09 0.09 Social psychology 0.18 0.21 0.14 0.18 ACKNOWLEDGMENTS Travel 0.12 0.08 0.18 0.13 This work is part of the ongoing research at the Department of Economy 0.15 0.13 0.09 0.12 Intelligent Systems, Jožef Stefan Institute. It is a subset of a larger Development 0.16 0.18 0.12 0.18 COVID-19-related research, which is subject to potential future Geography 0.12 0.06 0.11 0.10 publications. The authors also acknowledge the financial support Health 0.11 0.19 0.11 0.14 from the Slovenian Research Agency (ARRS). Countermeasures 0.04 0.02 0.06 0.04 REFERENCES Table 2: Individual feature ranking using RF feature score, [1] Rodrigo M Carrillo-Larco and Manuel Castillo-Cara. 2020. statistical testing and wrapper method. Top 5 features and Using country-level variables to classify countries accord- corresponding scores are shown. ing to the number of confirmed covid-19 cases: an un- supervised machine learning approach. Wellcome Open Research, 5, 56, 56. RF feature importance (higher is better) [2] P.T. Costa and R.R. McCrae. 2013. Personality in Adulthood: Repr. rate Exp. Daily avg. A Five-Factor Theory Perspective. Taylor & Francis. isbn: Tightness (0.071) EST_perc (0.053) AGR_perc (0.032) 9781135459703. EST_perc (0.014) Masculinity (0.017) Individual. (0.024) [3] Michele J Gelfand, Jana L Raver, Lisa Nishii, Lisa M Leslie, OPN_perc (0.013) Individual. 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Oxford covid-19 government re- groups of features describing countries, we showed that the social sponse tracker. https://github.com/OxCGRT/covid- policy- psychology group has the highest feature importance alongside tracker. development. Additionally, we found that there is no single dom- inant feature in our set of 11 in the social psychology group, but instead the importance is spread among several. We also used correlation analysis to confirm two out of our five hypotheses, 179 Od orodja do umetnika From Tool to Artist Neža Marija Slosar Filozofska fakulteta, Univerza v Ljubljani Ljubljana, Slovenija neza.m.slosar@gmail.com POVZETEK odveč razmišljanje s perspektive, da kot civilizacija nismo na povsem novem prelomu. V prispevku se ukvarjam z odnosom med umetnostjo in umetno Na spletni strani združenja UI-umetnikov je kot začetnik na inteligenco (v nadaljevanju tudi UI). Podrobneje se ukvarjam z časovnici UI umetnikov naveden Thomas Bayes, ki je "z uporabo odnosom med orodjem pri umetniškem ustvarjanju in samim matematike razvil okvir za sklepanje o verjetnosti dogodkov, ustvarjalcem. To me pripelje do vprašanja avtorstva ter upoštevajoč pogoje ali druge dogodke, ki lahko na dogodek primerjavo med umetniškim ustvarjanjem kot obrtjo ali kot vplivajo. Zahvaljujoč njegovemu delu je Bayesov sklep vplival produktom umetniškega genija (tudi Genij)1. na pristope pri strojnem učenju in predstavlja enega najzgodnejših mejnikov na časovni premici umetne KLJUČNE BESEDE inteligence.(op. prev. p.) [4]" Njegova spoznanja so nato v 50. umetnost, umetna inteligenca, avtorstvo, ustvarjanje, orodje letih prejšnjega stoletja nadgradili in so vplivala tudi na razvoj računalništva – v tem času, in sicer leta 1950, pa je tudi ABSTRACT pomemben avtor Isaac Asimov izdal zbirko kratkih zgodb I robot, In this paper, I deal with the relationship between art and v kateri se poigrava z možnimi scenariji inteligentnih strojev v artificial intelligence (hereinafter also AI). I deal in more detail prihodnosti. with the relationship between the tool in artistic creation and the V zadnjem času beležimo še nekaj pomembnih mejnikov, in creator himself. This brings me to the question of authorship and sicer so leta 2018 na dražbi prodali sliko UI, ki se je učila od a comparison between artistic creation as a craft or as a product številnih umetnikov, za 432.500 $. AIVA velja za prvega of artistic genius. virtualnega umetnika, čigar dela so registrirana kot avtorska (z avtorskimi pravicami) pri SACEM (Société des auteurs, KEYWORDS compositeurs et éditeurs de musique – Združenje glasbenih art, artificial intelligence, authorship, creation, tool avtorjev, umetnikov in založnikov). Dokončanje 10. simfonije Ludwiga van Beethovna s pomočjo UI pa pričakujemo v letu 2020. 1 Umetna inteligenca na področju umetnosti Sprva želim orisati zgodovinski preplet med umetniškim ustvarjanjem in razvojem umetne inteligence ter opozoriti na 2 Umetna inteligenca – orodje ali umetnik ključne mejnike na tem polju. V osnovi umetniška dela temeljijo na fikcionalnosti in možnosti ustvarjanja dogodka, sveta, ki nastane pod točno določenimi, zapisanimi pogoji, kar definira literarna teorija. Da ne gre za željo po napovedovanju prihodnosti ali izdelovanju čim bolj natančnih modelov prihodnosti, ampak bolj za umetniško obdelavo informacij o družbi in svetu ter z domišljijo kreiranje najrazličnejših svetov. Zato tudi ne preseneča uporaba oz. povezovanje umetne inteligence z razvojem tehnologije in umetnosti, četudi se na prvo roko zdi umetnost zelo konvencionalna. Takšno prepričanje je morda nekoliko naivno, saj je že samo risanje na stene, ohranjanje snovne kulturne dediščine zahtevalo uporabo novih tehnologij, zato morda ni Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and Slika 1: Shematični prikaz rekurzivne nevronske mreže, na the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). kateri temelji delovanje UI. [16] Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 1 Pri tem je genij razumljen po konceptu Denisa Diderota, ki ga je oblikoval v 18. stoletju. [11] 180 Za začetek se mi zdi za razumevanja samega koncepta binarne pomemben z vidika, da nam dejstvo, da nekaj lahko okličemo za opozicije med umetnikom in orodjem potrebno izpostaviti zavestno entiteto, takoj preseže pojmovanje tega kot samega temelje tega odnosa, ki nas lahko v nadaljevanju pripelje do orodja. Z drugimi besedami, če lahko UI v katerem koli smislu natančnejše opredelitve razmerja med njima. V osnovi je jemljemo za kaj več kot le orodje, predhodi vprašanju, če lahko pomembno, da umetniki vedo, s čim delajo in kaj so prednosti in UI okličemo za umetnika, za nekoga (nekaj), ki ustvarja iz slabosti tega. Nevronske mreže so danes najbolj napredni strojni lastnega navdiha oz. predvsem lastne želje po ustvarjanju. Pri "možgani" in osnova delovanja v razvijanju umetne inteligence, tem tudi ni zanemarljivo vprašanje, ki si ga je zastavil Hartman, saj "imajo sposobnost razločevanja in izločevanja informacij iz profesor angleškega jezika in kreativnega pisanja na Connecticut kompliciranih in nejasnih vzorcev" [18]. Katarina Mramor College New London, in sicer: " čemu in komu bi bil tak program opozarja tudi na njihove kritične točke – učni primeri, ki morajo [ki bi generiral poezijo samostojno (iz nič)] sploh potreben" [15]. biti zelo pozorno izbrani, saj je od njih odvisno, kaj bo končen V združenju UI-umetnikov na vprašanje, če so lahko stroji rezultat nevronske mreže. Učne primere izbirajo ljudje, zato je kreativni, odgovarja umetnik Ahmed Elgammal, ki se ukvarja s treba biti pazljiv, da nenamerno ne vnesemo preveč črno belih točno tem področjem. Ahmed Elgammal izhaja iz ideje, da primerov, ki bi temeljili na kupu subjektivnih predpostavk, ki se strojev ne moremo imenovati za inteligentne, dokler ti ne bodo jih mogoče niti ne zavedamo in lahko vsebujejo problematične razumeli in ustvarjali tudi "kulture" (vizualno, zvočno umetnost, etične odločitve; česar se potem nauči tudi nevronska mreža in literaturo in šale). jih nadalje širi brez problematiziranja, dokler se v praksi (npr. Izhodišče za stroje se loči od človeka po tem, ker lahko UI pravu, varnosti …) odločitve ne izkažejo za problematične ali prečeše čisto vse, kar je kadar koli nastalo, v nasprotju s vsaj vprašljive. človekom lahko pozna čisto vsa dela ter ve informacije o Tudi združenje umetnikov UI se ukvarja s problematičnimi nastanku, kritike in razlage, ki so ob tem nastale. Vendar se točkami v interakciji med umetno inteligenco ter človekom. Pri Elgammal zaveda, da ta baza in potem posnemanje še ne pomeni tem združenje nagovarja neodgovorjena vprašanja, kjer vidi ustvarjanje nečesa novega, kar želi doseči s svojimi projekti. izzive na področju definiranja vrednot (kaj so človeške in kaj so Nadalje pa na vprašanje, kako želi to doseči ponudi odgovor, ki nečloveške), obdelavi oz. naboru podatkov, ki jih damo učiti pravzaprav ponovno vodi k razvoju orodij. UI predstavi nevronskim mrežam, varnosti osebnih podatkov ter samem predvsem kot partnerja (z moje perspektive še vedno orodje), ki delovanju nevronskih mrež. [5] bo umetniku (človeku) odkrivalo nove umetniške poti in ideje. Nekateri znanstveniki na naštete izzive odgovarjajo zelo To utemelji s primerom fotoaparata, ki je pomenil zelo proaktivno in programirajo "okvirje" oz. načela, ki naj bi pomembno revolucijo sprva v vizualni umetnosti, kasneje pa poskrbela za "samoodgovorno vedênje" UI. Primer slednjega je veliko širše – zvok, film, fotografija … Tako naj bi tudi raziskovalni center "The Institute for Ethical AI & Machine tehnološki razvoj v prihodnje nudil revolucije v umetnosti, Learning", ki je formalno stacioniran v Veliki Britaniji, vendar vendar če natančno beremo, še vedno govorimo o pripomočkih, ga sestavljajo raziskovalci, prostovoljci različnih strok (inženirji ki jih upravlja in si jih želi, razvije, potrebuje človek. [1] strojnega učenja, podatkovni znanstveniki, pisci pravilnikov in Ob tem, ko smo s pomočjo namere in želje po umetniškem profesorji skupine STEM2, humanisti in družboslovci). Njihova ustvarjanju skušali pokazati, da je za to potrebna zavest; se pri vizija je: "Minimizirati tveganja UI in omogočiti njeno polno tem kot še bolj problematično pokaže pomembno filozofsko delovanje znotraj okvirjev, ki zagotavljajo etični in zavedni vprašanje svobodne volje. Na tem mestu moj cilj ni raziskovati razvoj projektov, povezanih z UI na vseh področjih delovanja, v širine tega vprašanja, ampak na podlagi petih Hodgsonovih vseh industrijskih panogah" (The Institute for Ethical AI & trditev ugotoviti, v kolikšni meri te veljajo za sodobno umetno Machine Learning). inteligenco. 2.1 Vprašanje zavesti in svobodne volje – kako "Kaj torej pomeni 'govorjenje o svobodni volji'? preseči Kakšne so zdravorazumske intuicije o svobodni orodje volji? Intuicije človeka, ki ni filozof ali kognitivni Kljub izjemnemu tehnološkemu napredku še vedno ostaja odprto znanstvenik, in ni pristranski. Hodgson (2005) meni, vprašanje, ki si ga znotraj kognitivne znanosti zastavljajo da bi taka oseba podala naslednji fenomenološki znanstveniki, programerji, filozofi …, če bomo lahko kadar koli opis, kako je biti svoboden, zavesten akter umetno inteligenco razumeli povsem samostojno, neodvisno, (Hodgson, 2005, p. 3): samozavedno. Torej, če bomo vedno lahko govorili le o vse bolj - Zavedamo se izbiranja odločitev. - Imamo občutek, da smo mi začetniki naših dejanj. dodelanih, izboljšanih in uporabnih orodij (človeka) ali dejansko - Včasih tehtamo alternative, včasih sledimo o nečemu/nekomu, ki je zmožen tega "samoustvarjanja", navadam. ustvarjanja iz sebe v ideji bolj kot v izvedbi, saj takoj, ko - Zavedamo se posledic dejanj, ki smo jih storili. preidemo na zmožnost nečesa izvesti, že govorimo o (bolj ali - Imamo se odgovorne za svoja dejanja" [17]. manj samostojnem) orodju. Kot najbolj znan primer poskusa odgovora na to vprašanje je Turingov test, kjer naj bi se stroj Na podlagi zapisanega ne moremo najnovejšim nevronskim obnašal tako "človeško", da bi pretental samega človeka. Na področju filozofije tako pridemo do problema mrežam pripisati niti ene od petih trditev zares, saj se nevronska (upravičenja) zavesti. Odgovor na to je v pričujočem prispevku mreža še vedno niti ne zaveda, ampak skuša čim bolj učinkovito 2 STEM je angleška kratica za Science (naravoslovne znanosti), Technology (tehnologija), Engineering (strojništvo) and Mathematics (matematika). 181 izvršiti ukaz, opraviti nalogo. Po drugi strani, pa bi zelo težko o umetniku, ampak o človeškem pripomočku, ki ga razvijalci sploh v umetnosti lahko rekli, da ne gre pri ustvarjanju za razumejo kot del razširjene kognicije (človeka), saj ima podobno svobodno voljo umetnika. funkcijo delovanja pri pisanju glasbe, kot jo lahko ima npr. zemljevid na telefonu pri orientaciji. Trenutno najbolj znan projekt je dokončanje Beethovnove 3 Kje se konča programiranje in začne desete simfonije, kar bodo naredili s pomočjo umetne umetnost? inteligence. Informacija o tem se je razširila konec leta 2019, Če se na tem mestu ne ukvarjamo s tem, kako čustva vplivajo na simfonijo pa naj bi izvedel simfonični orkester 28. aprila 2020 v odločanje, ne moremo prezreti dejstva, da je v umetnosti v ozadje Bonnu (rojstnem mestu skladatelja). Zaradi pandemije je bil postavljeno samo razumsko reševanje nalog, saj postane zgolj koncert odpovedan, novic o tem, kako napreduje ta projekt, pa racionalnost v okviru umetnosti banalna. Na umetnost se že mi ni uspelo zaslediti. Nekaj vzorcev komponiranja UI je moč dolgo več ne gleda zgolj obrtniško, ampak se ji pripisuje estetsko slišati na spletni strani: vlogo in vpliv "čustev na čustva". Pravzaprav je včasih telekom.com/de/konzern/themenspecials/special-beethoven- merodajna uspešnost prevoda ustvarjalca, da čim uspešnejše jahr-2020/beethovens-unvollendete. Pri projektu sodeluje oz. je preda svoja občutja. Razvoj UI zaenkrat temelji na sodelovalo (poleg vseh strokovnjakov UI) veliko število prepoznavanju človeških čustvenih odzivov na podlagi fizičnih muzikologov in poznavalcev Beethovnove glasbe in obdobja, znakov (prepoznavanja gest, obraza, glasu, …), kar je še daleč zato je projekt skrbno nadzorovan in voden tudi s strani od človeške empatije in predvsem daleč od čustvenega umetniške stroke, ki opozarja na nepogrešljive dele. Želja je doživljanja oz. odzivanja same UI. namreč pokazati, da je pri tovrstni uporabi stroj lahko tako dober Je pa razvoj umetne inteligence poleg inovativnosti v in učinkovit kot človek, saj tovrsten pristop predstavlja za umetnosti prinesel tudi ogledalo, saj nam nudi reflektivni številne konvencionalne klasične strokovnjake zelo grob poseg, premislek o tem, kdaj umetnost preseže obrtniškost, kdaj preseže ki nima možnosti za uspeh. programiranje, do katere mere so ljudje, ki ustvarjajo z UI Na tem mestu se lahko vprašamo, zakaj smo prepričani, da programerji, kdaj pa postanejo umetniki oz. ali lahko tudi umetno bi človeški obrtniški prepisovalci, dokončevalci umetniških del inteligenco okličemo za umetnico? Kdaj delo upraviči estetsko bili uspešnejši od UI, saj gre v obeh primerih za zelo podoben funkcijo3, da ga lahko imenujemo umetnost? način učenja (nadaljevanja vzorca glede na pravila in vhodne Konkretno lahko odgovore iščemo pri samih dosežkih UI podatke), pri čemer lahko strojni algoritmi hkrati obdelujejo in zadnjih let. Oktobra 2018 je bil v Timu objavljen članek, kjer delajo z veliko več (specifičnimi) podatki kot učenci, ki so to piše, da so na dražbi Christie's prvič prodali delo, sliko, ki jo je počeli pred stoletji. Ob tem se ne ukvarjamo z vprašanjem Genija ustvarila UI. Prodali so jo za 45-kratnik izhodiščne cene (za – torej, v čem je genialnost samega Beethovna in zakaj on to je, 432.500 $). Slika nosi naslov Portret Edmonda Belamyja. medtem ko ostalim njegovim sodobnikom to ni uspelo – ampak Algoritem se je učil na 15.000 portretih različnih slikarjev od 14. povsem obrtniškim vprašanjem, nadaljevanje glasbenega vzorca, do 20. stoletja, v desni spodnji kot pa se je tudi podpisal – v ležeči kjer mnogokrat ni nujno potreben kreativni proces, ampak gajici je izpisal svoj algoritem [21]: predvsem natančnost. Zato sem mnenja, da se mora včasih tudi človek zavedati svojih omejitev oz. egoizma. Z uporabo UI lahko 𝑚𝑖𝑛 𝑚𝑎𝑥 𝔼𝑥[log⁡(𝐷(𝑥))] + 𝔼𝑧[log⁡(1 − 𝐷(𝐺(𝑧)))] 𝐺 𝐷 tudi v umetnosti odkrivamo nove, še nepoznane svetove, pri čemer se moramo tako, kot se zavedamo vseh omejitev UI, Nadalje predstavljam projekt AIVA (Artificial Intelligence zavedati tudi svojih, človeških. Virtual Artist). V opisu piše, da gre za virtualno umetnico, ki je zmožna komponiranja glasbenih podlag za filme, video igre, oglase in nasploh prosti čas. Algoritem se je učil od številnih del 4 Zaključek klasičnih skladateljev (Mozarta, Beethovna, Bacha, …), iz česar V prispevku sem orisala veliko podpodročje kognitivne znanosti se je razvil model, ki naj bi razumel, kaj je glasba. Ta model – uporablja Aiva za komponiranje povsem edinstvene glasbe. Aiva umetno inteligenco – in jo umestila v kontekst umetniškega ustvarjanja. Ugotovila sem, da z vključevanjem UI v umetnost je postala prvi virtualni umetnik, katerega stvaritve so avtorsko priznane s strani združenja SACEM. Na u postaja ta interdisciplinarna v širšem smislu, kot je bilo to do radni spletni strani dodajajo, da ti dosežki ne pomenijo, da bo Aiva zamenjala sedaj, saj zahteva tudi veliko tehnološkega, programerskega znanja. Vračajo se številni etični pomisleki, do kateri glasbenike, skladatelje, ampak gre za nadaljevanje sodelovanja h se je treba med človekom in strojem. Ustvarjalci menijo, da komponiranje opredeliti, ter filozofske predpostavke, ki se jih mora zavestno z UI omogoča nove pristope v glasbi. Zato jo tudi oglašujejo za sprejeti, zato da se lahko UI nadalje uspešno razvija. primerno za vse vrste uporabnikov (od preprostih poslušalcev, Ključno in osrednje vprašanje prispevka je bilo, ali je lahko umetna inteligenca, ki ustvarja, že sama po sebi umetnik? Ali novincev v komponiranju do profesionalnih glasbenikov) – AIVA asistira pri kreativnih procesih človeka, tako kot so v smo že presegli uporabo stroja kot orodja ali je ta še vedno v zgodovini veliki umetniki imeli svoje učence, lahko imajo domeni človeka in njegovega uporabljanja? zdajšnji umetniki UI pomočnike, ki jim pomagajo skrajšati čas V samem bistvu še ne moremo govoriti o samostojni umetni za dokončanje skladb. Aiva lahko komponira v že ustaljenih inteligenci, ampak govorimo o vse bolj in bolj izboljšanih stilih ali po vzoru "vpliva", ki ga naložimo sami orodjih, človeških pripomočkih, katerim v vsakem primeru [3]. Če kritično predhodi človek (kot programer ali s podatkovno bazo, iz katere presodimo prebrano, lahko ponovno ugotovimo, da ne govorimo 3 Sklicujem se na definicijo estetske funkcije po Romanu Jakobsonu, ki jo je opredelil v Lingvistiki in poetiki. 182 se UI uči), pri čemer lahko dopustimo misel, da so tudi ta orodja [8] 2020. Beethoven-Jahr 2020. Telekom. (september 2020). že del razširjene kognicije https://www.telekom.com/de/konzern/themenspecials/special-beethoven- , saj odpirajo tudi v svetu umetnosti jahr-2020. povsem nove pristope, načine dela in svetove, ki jih do sedaj še [9] 2020. CHAI. Center for Human-Compatible AI. https://humancompatible.ai/. [10] James Crowder. Artificial Psychology: The Psychology of AI. ResearchGate. nismo videli. Karas v svoji diplomski nalogi: marec 2012. https://www.researchgate.net/publication/235219143_Artificial_Psychology_ "smiselnost računalniških generatorjev poezije vidi The_Psychology_of_AI. [11] predvsem v obliki 'pametnih orodij', s katerimi človeški Hebert Dieckmann. 1941. Diderot's Conception of Genius. Journal of the History of Ideas, 2, 2, 151–182. doi:10.2307/2707111. pesnik ustvarja poezijo, narejeno s pomočjo [12] Sašo Dolenc, 2017. Kako zgraditi umetne možgane. Kvarkadabra. (avgust računalnika: 2017). 'Kot povsod drugje, hibridni pristop https://kvarkadabra.net/2017/08/kako-zgraditi-umetne-mozgane/. [13] 2007. External cognition. EduTech Wikipedia. (november 2007). združuje (domnevno) najboljše vseh različnih svetov. http://edutechwiki.unige.ch/en/External_cognition. Računalniki kljub napredku UI še ne 'razumejo' jezika, [14] Mathieu Foulkes. 2019. AI puts final notes on Beethoven's Tenth Symphony. Tech Xplore. (december 2019). https://techxplore.com/news/2019-12-ai- kot ga razumemo ljudje, toda po isti logiki se ljudje beethoven-tenth-symphony.html. težko primerjajo (z računalniki, op. p.) po lahkotnosti [15] Jure Karas. 2016. Računalniško generiranje poezije. Diplomsko delo. Ljubljana: Filozofska fakulteta igranja na polju jezika.'" [15] [16] Cory Maklin. 2019. LSTM Recurrent Neural Network Keras Example. towards data science. (junij 2019). https://towardsdatascience.com/machine-learning- Ob tem je takoj sledilo še vprašanje, kdaj lahko govorimo o recurrent-neural-networks-and-long-short-term-memory-lstm-python-keras- example-86001ceaaebc. resnični umetnosti, o umetniškem delu. Čeprav je to vprašanje [17] Olga Markič. 2011. Kognitivna znanost: filozofska vprašanja. Maribor: Aristej, prisotno, odkar rečemo nečemu umetnost oz. od začetka [18] Katarina Mramor. 2007. Nevronske mreže. Seminarska naloga. Ljubljana: človeštva, se je pokazalo, da nam nudi svež pogled ravno umetna Fakulteta za matematiko in fiziko. [19] Nikolaj Pečenko. 2006. Zgodovina osebnih računalnikov. Monitor. inteligenca, saj se kot očitno pokaže, da ne moremo soditi samo https://www.monitor.si/clanek/zgodovina-osebnih-racunalnikov/122478/. po končn [20] Bojan Ploj. 2017. Umetna inteligenca - Nevronske mreže (3.del). ResearchGate. em izdelku, da lahko UI ustvarja določene generične https://www.researchgate.net/publication/315897957_Umetna_inteligenca_- izdelke enako dobro ali še boljše kot ljudje. Zato moramo _Nevronske_mreze_3del. odgovore ponovno iskati v sami funkciji umetniškega dela in [21] Casey Quackenbush. 2018. A Painting Made by Artificial Intelligence Has Been Sold at Auction for $432,500. Time. 26. oktober. avtorja, iskati moramo pri izvoru in namenu ustvarjanja in ne https://time.com/5435683/artificial-intelligence-painting-christies/. zgolj presojati rezultata. V luči tega se je v zaključku izrisal še [22] Maddy Shaw Roberts. 2019. Beethoven’s unfinished tenth symphony to be en premislek, in sicer po ponovni človeški samorefleksiji – completed by artificial intelligence. Classic fM. (December 2019). ali je https://www.classicfm.com/composers/beethoven/news/computer-completes- sploh nujno, da UI jemljemo kot konkurentko in nanjo gledamo unfinished-tenth-symphony/. kot človek na človeka, ali gre mogoče za nov odnos? [23] Richard Routledge. 2018. Bayes's theorem. Encyclopaedia Britannica. http://www.britannica.com/topic/Bayess-theorem. [24] 2020. SACEM. https://www.sacem.fr/en. [25] 2020. Science, technology, engineering, and mathematics. Wikipedia. 5 REFERENCE (januar 2020). https://en.wikipedia.org/wiki/Science,_technology,_engineering,_and_mathe [1] 2020. AIartists. https://aiartists.org/. matics. [2] 2020. AIArtists. Creative Tools to Generate AI Art. https://aiartists.org/ai- [26] Jonathan Shaw. 2019. Artificial Intelligence and Ethics. Harvard Magazine. generated-art-tools. (januar-februar). https://harvardmagazine.com/2019/01/artificial-intelligence- [3] 2020. AIArtists. Ethical AI Resources. https://aiartists.org/ai-ethics. limitations. [4] 2020. AIArtists. Timeline of AI Art. https://aiartists.org/ai-timeline-art. [27] 2020. The Institute for Ethical ML. The Responsible Machine Learning [5] 2020. AIArtists. Unanswered Questions About AI. Principles. https://ethical.institute/principles.html. https://aiartists.org/unanswered-questions. [28] 2020. Uredniki Encyclopaedie Britannica. Thomas Bayes. Encyclopaedia [6] 2020. AIVA. https://www.aiva.ai/. Britannica. https://www.britannica.com/biography/Thomas-Bayes. [7] 2019. Artificial intelligence puts final notes on Beethoven's '10th Symphony' . [29] Aleš Uršič. 2012. Evolucija nevronskih mrež. Diplomsko delo. Ljubljana: The japan times. (december 2019) Fakulteta za računalništvo in informatiko, https://www.japantimes.co.jp/culture/2019/12/13/entertainment- [30] Vladimir Zwass. 2019. Neural network. Encyclopaedia Britannica. news/artificial-intelligence-puts-final-notes-beethovens-10th-symphony/. https://www.britannica.com/technology/neural-network. 183 Social Media Use & Digital Stress Among Adolescents Simon Šalomon Dayana Hristova MEi:CogSci Faculty of Psychology University of Ljubljana University of Vienna Ljubljana, Slovenia Vienna, Austria simon.salomon@protonmail.com dayana.hristova@univie.ac.at ABSTRACT psychological distress and various negative effects or emotions connected to it [5][6][7][8]. This is a case study presenting ways in which adolescents perceive social media as a stressor, at the empirical example of Snapchat. Despite the overall positive or neutral reception of 2 THEORETICAL BACKGROUND social media, in semi-structured expert interviews (N=6), Viennese adolescents shared about various stressful experiences 2.1 Social media as stressors that can be summarized under the following categories: feeling A stressor can be described as a trigger that afflicts an smothered by peer pressure to be constantly available online/ organism and is capable of causing internal physical, mental and respond to messages; being upset over losing a streak or being emotional responses. Social media can be understood as a social scolded for it; being annoyed when receiving pointless content stressor defined as any environment that an individual considers and feeling as if they spend too much time online. These stressors demanding, challenging, or in any way threatening [9]. are discussed with regard to existing digital stress and Snapchat A growing body of literature on the intersection between Streaks literature, with a particular focus on the issue of social and clinical psychology shows possible connections or maintaining closeness between peers online. correlations between the new information and communication technologies – social media platforms, and an increased risk of KEYWORDS emotional problems, e. g. psychological distress [5][6][7][8][10]. social media, digital stress, Snapchat, gamification Considering SNS’s pivotal role in the life of adolescents, it is crucial to scrutinize the effects of social media usage on youth (SMU), as well as their evaluations of their own SMU. 1 INTRODUCTION By removing ’’ spatial and time constrains that were inherent 2.2 Social media & psychological distress among in traditional methods of communications’’, social networking teens sites (SNS) are nowadays becoming the primary medium for a The term psychological distress refers to an ‘‘ unpleasant plethora of activities, such as accessing information, passing feeling or emotion often characterized by symptoms of time, working on one’s representation of reality and depression and anxiety’’, e. g. loss of interest, sadness, communicating with peers [1]. SNS such as Facebook, Instagram restlessness [11]. Usually described as ‘‘non-specific mental and Snapchat are attracting billions of daily active users of all health problem’’, it covers a wide spectrum, ranging from ages and shape communication cultures especially among the so ordinary feelings of vulnerability and negative emotions to fears called “digital natives” [2] - adolescents growing up with social or problems that can become disabling [12]. media as one of the default ways to connect to others. The section below describes evidence from psychological Adolescence is a particularly sensitive period for ’’ personal and research that social media platforms, may be experienced as social identity formation’’ [3], and, nowadays social media are stressors potentially leading to psychological distress and various being integral part of this development and teens’ social negative effects associated with it [10]. experience in general. Seeking to shed light on the role social Keles et al. did a systemic review of the influence of social media play in the emotional life of youths, we investigate which media on depression, anxiety and psychological distress in aspects of gamified social media [4] are perceived as stressful by adolescents [7]. Although the link between social media usage them. Based on an analysis of six semi-structured expert and mental health problems is not always straightforward, their interviews with Viennese adolescents, this paper presents research clearly indicates ‘‘ a meaningful relationship between situations, in which adolescents experience social media as a social media use and depression’’ [13]; ‘‘ a statistically source of stress, which could potentially lead to experiencing significant relationship between social media use and depressive symptoms in children and adolescents’’ [14]; ‘‘ a correlation between problematic use and psychological distress in Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed adolescents and young adults’’ [15]. for profit or commercial advantage and that copies bear this notice and the full A combination of various causes such as unrealistic citation on the first page. Copyrights for third-party components of this work must expectations of one’s own performance, heavy SMU, specific be honored. For all other uses, contact the owner/author(s). Information Society ’20, October 5–9, 2020, Ljubljana, Slovenia changes in adolescents’ brain linked to ‘‘ limited capacity for self- © 2020 Copyright held by the owner/author(s). regulation’’ and ‘‘ vulnerability to peer pressure’’ makes teens particularly vulnerable group for potential experience of negative 184 effects or emotion, e. g. lack of control, sadness, frustrations, order to offer this availability, “some are on the phone all the fears etc. [7]. time” which irritated our informants. A participant reported that Agrawal and Singh did a systematic review of research related to she was feeling stressed out because friends insisted on social media and psychological distress among adolescents. They maintaining the Snapchat streaks, counting the consecutive days conclude that the results ‘‘ clearly indicate that (frequent) use of of snapping, which requires the conscious effort of recalling to social networking sites is directly related to psychological snap at least once per day with no preset expiration date – the distress among youth’’ [5]. With that in mind, we believe it is streak partners are trying to keep the streak going for as long as crucial to investigate youth’s social media experience and to possible, often reaching years of ongoing maintenance. Our analyze the ways in which they may perceive social media as a informant shared that the feeling of compulsion spoiled her stressor. appreciation for Streaks: “in the end I didn't feel like it and felt compulsion, I thought it was stupid”. - losing streaks: adolescents report being mildly upset 3 METHODS themselves when losing a streak, as well as their peers being The analyzed data is a randomly selected subset (N=6, 15-18 upset by a streak loss: “One was already mad that he had lost the years old, the average age of participants was 16.33, SD=1.10) streaks. It wasn't with any of them that they would never speak of a larger set (N=26) of semi-structured expert interviews with again, but yes, there was something”. “Losing” the gamified Viennese adolescents in which they reported on their social challenge is reported to incite frustration though it is rather game- media use, with a focus on Snapchat. The interviews focused on related than full-blown negative emotions. Commonly, the the practice of participant’s daily routine with social media: their intensity of the reaction is proportional to the height of the streak specific actions, skills and SMU experience. The participation in - the higher the streak, the more severe the loss: “With two the individual interviews (60-90 minutes) was voluntary and a friends of mine, one was really very pissed off, she had 300 signed parent consent form was collected from each informant. streaks or something, abnormal, and the other didn't send back”. The data were anonymized and relevant quotes were translated - receiving “pointless” content: feelings of annoyance and to English for the purposes of this publication. The interviews frustration upon receiving boring or pointless content. were coded (in Atlas.ti) using a modified grounded theory Adolescents complained of annoyance at receiving pictures of approach [16]. The analysis then focused on the codes related to floors, walls, good morning / good night pictures and black ways in which youths experiences social media as stressful. pictures, all mostly are aimed at keeping Snapchat Streaks. Since the Streaks counter only quantifies the number of days of snapping, but has no criterion as to the quality of content sent, 4 RESULTS our informants said that they receive pictures containing “just the In line with previous research [17], our data reveals the near ground or something like that. Just to keep the streak, they sends omnipresence of social media use in our participants’ daily lives, something stupid”, “just take the cell phone and take pictures of and especially to communicate with their peers. All participants what's there, floor, table, it doesn't matter”. According to them, regarded social media use as regular means to connect with this happens because “you don't have much to communicate others daily, be it about school obligations, setting up meetings, about and you only do it because of the streaks”. Although they passing time, or bonding with peers. Their overall impressions send and receive such messages, adolescents conclude that about social media usage were positive or neutral. Connecting “those are the unnecessary snaps”, “they think it s stupid but still with others on social media was seen as one of the main ways to do it”. communicate and as such its fundamental functions remained - too much time spent online: Participants reported being largely unquestioned. However, in agreement with previous aware that time spent on social media platforms corresponds to research [18], our data also indicates that youths reported about less real-life activities involvement and school disturbance, due both positive and negative experiences on the platforms. to e.g. the constant checking for new messages or content. When Participants associated SNS, and Snapchat in particular, with asked how much time he spends on social media, an informant mostly positive effects on their everyday life, e.g. as digital answered “Far too much, I don't know, six or more hours a day. media enable their daily communication with peers outside of I use it far too much”. Another adolescent shares that, although school or with friends from other countries. Nevertheless, five they were still active on social media, SMU was proven to be too out of six participants reported experiencing stress related with much for them in their busy daily life: “That was the time with their use of social media. We will now present the main the school work, I had to learn a lot and in the evening I was categories of SMU related stressors that we encountered in our already very tired, and with the last of my strength I was able to data (with respective empirical examples): feeling smothered, snap but it was too much for me”. Yet another contemplates to losing Streaks, receiving pointless content and feeling they spend limit her SMU time: “Maybe I would restrict it, I like YT very too much time online. much, but it takes a lot of time. With IG there are videos that will - feeling “smothered” [17]: the pressure of compliance in the be presented to you, 30 min + I should stop that. YouTube and form of being constantly available to others. The pressure to be Instagram rob me most of the time. Time is actually wasted available is also linked to expectations of “responding because I could use it better … I often think the day could be immediately” and, should this expectation not be met, peers more productive”. would also actively comment on it: “people have already told me In addition to these main categories, individual participants that I don't answer”. Hence, our informants were stressed out by also mentioned feeling: envious of others’ streak count and social the pressure for instant availability in form of in-short-time status; disappointed over inappropriate videos or pointless replying to texts or snaps. It also seems critical to note that in arguments online, or being bored by receiving pointless 185 repetitive content. In the following section, we are going to the discussion. The discussion about how much digital media is discuss the main categories in more detail. too much [20] seems to perpetuate itself to contemporary discussions of how much time makes up for a balanced social media use [21]. The adolescents in our sample go one step further 5 DISCUSSION by contemplating actively changing their social media The main types of stress we derived from the data – such as consumption to mitigate aforementioned excessive expenditure feeling smothered, losing Streaks, receiving pointless content of time resources. and spending too much time on social media – highlight different To sum up, the aforementioned types of stress are sparked by relational aspects of online communication with peers. It is the desire to form a close relationship on social media and by its evident that informants’ experience of stress sprouts not from implications: the time, effort and quality of involvement needed hostile interactions with peers (e.g. cyber bullying) but are for this. The need or wish to be involved in their peer’s online commonly caused by aspects of ‘‘ maintaining closeness in social life daily likely comes from adolescents’ offline desires to digital space’’ [17]. Feeling smothered is caused by excess in ‘‘ attract others’’, ‘‘ gain acceptance’’ and ‘‘ fit in’’ and ‘‘ keep in the extent to which one is or should be making themselves touch’’ [22][23][24][25]. In this, the very principles may be available for communication with peers: how quickly they considered an extension of pre-existing concerns over the ways should respond to messages, how often should they check the and extent of closeness to peers. phone, whether one should try to commit to longitudinal projects However, specific social media features such as Snapchat’s such as Streaks that require daily effort [4] [19]. Weinstein & gamification element Streaks impose further specific constraints Selman [17] discuss this stressor in its duality – as controlling on rules of social conduct. In order to preserve the streak, one and expressing desire for closeness. They report that while needs to snap and receive or view at least one picture or video closeness is mutually desired and the content of messages is not within the frame of each day (24 hours), thereby adding further problematic, “the sheer quantity of the messages is itself time pressure to the communication. While our participants do described as a burden” (ibid). get involved with Streaks, the practice also adds more stress to Being upset because of losing streaks or being scolded at for their already complex temporal landscape of online interaction, it are reactions to losing the shared project in which the daily requiring them to be available round the clock and respond right effort was invested. Keeping a streak consciously is a task that away after receiving a message. These contemporary challenges requires both partners’ devotion and daily effort and can, hence, structure daily routines and experiences and, hence, need to be spark a sense of solidarity and intimacy [19]. That is why, the studied in more detail by researchers. abandonment of the gamified challenge of maximizing the Streak count might be seen as a sign of not caring about the other person’s importance or feelings, which then requires the 6 CONCLUSIONS negotiation of the relation between peers (e.g. apologizing, In post-industrial cultures, social media and its use are breaking contact). nowadays becoming a days-to-day feature in the life of Youths are not only concerned when relations prompt individuals and especially adolescents. These online platforms constant availability and “overdoing communication” till one represent an important tool of communication with their peers, starts feeling smothered. Conversely, they express concerns over as well as a major part of youth’s social experience. the drop in the quality of communication such as the one signaled The goal of the study was to better understand SMU aspects by reciving “pointless” content. Being annoyed at boring or which can be perceived as stressful by adolescents. While our meaningless content one receives can be hedonic (being annoyed research was based on self-report measures, posing the risk of that the content one views is not entertaining) or relational (being bias, and was limited by small sample size, which cannot be upset over the inadequate communication which that signals representative and generalized to a larger adolescent population, disrespect towards the relationship). The latter may cause it offers a categorization of stressors: feeling smothered, losing worries over interpreting the signs or the need to re-negotiate the Streaks, receiving pointless content and feeling they spend too relationship (by discussing it, dropping contact online or offline, much time online; all of which stem from the wish to uphold or both). Hristova et al. report that the so called “streak snaps” closeness online. Based on the importance of the role that social (an umbrella term for black pictures, goodnight pictures etc. sent media plays in most adolescents’ lives nowadays, we emphasize not as a part of conversation but for the purposes of gamification) the importance of further exploration of the stress-inducing are perceived as less valuable than snaps sent within a aspects of maintaining online closeness. conversation. They report that adolescents often drop their streak with people who send them the gamified snaps without being involved in a conversation or asking one how they are doing [19]. 7 ACKNOWLEDGMENTS Adolescents exhibit metacognition concerning the extent of A special thank you goes out to the Vienna Cognitive Science their social media use, as exemplified by their worry over Hub for the support of the project called Difficulty and strategies spending “too much time” on social media and realizing that in emotion regulation. this robs them of their time for other tasks they would find more “productive”. This type of psychological distress is connected to an estimated excessive personal investment (time, effort, 8 REFERENCES attention), leading SMU to be perceived as threatening [9]. It is [1] Fotis, J. N. (2015). 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(1982). Perspectives on the past and 637–654 future of psychiatric epidemiology. Americal Journal of Public Health, 72(11), 1271- 1279 [13] Best, P., Manktelow, R., & Taylor, B. (2014). Online communication, social media and adolescent wellbeing: A systematic narrative review. Children and Youth Services Review, 41, 27–36. 187 Special Sciences: Still Not Reducible after All These Years Tadej Todorović Janez Bregant Faculty of Arts Faculty of Arts University of Maribor University of Maribor Maribor, Slovenia Maribor, Slovenia tadej.todorovic@gmail.com janez.bregant@um.com ABSTRACT coming to opposite conclusions. The first pair, Shapiro and Polger [10] come to the conclusion that MR is very rare in nature, The paper introduces the problem of multiple realizability (MR), whereas Aizawa and Gillet [11] come to the conclusion that MR followed by the examination of conditions for MR, as presented is rather omnipresent. How is this possible? Throughout the by various philosophers working on it. They arrive at opposing paper, we will use Shapiro and Polger’s (S&P) example of conclusions regarding MR despite accepting similar criteria for corkscrews to illustrate the mentioned curiosity. In the end we it. The paper analyses their conditions and compares them to will introduce an explanation of it which is in the same time also Fodor’s original motivation for MR. An alternative solution to an alternative solution to the Fodor’s original problem of MR. the Fodor’s problem, which also explains the aforementioned different conclusions, is introduced. 2 SIMILAR CONDITIONS: DIFFERENT KEYWORDS CONCLUSIONS Multiple realizability, special sciences, reductionism, In short, S&P argue that for MR to be an obstacle to metaphysics. psychophysical reduction, the realizers have to be “different in ways that are relevant to their performing the same function” 1 HISTORY AND CRITERIA FOR [10]. What this means is that not just any difference will do. They MULTIPLE REALIZABILITY develop criteria for MR that are comprised of four necessary and jointly sufficient conditions (As and Bs represent the two The most influential argument of the 20th century against candidates for MR, e.g. pain in Martians and pain in humans, and psycho-neural identity theories in philosophy of mind is probably S1 and S2 designate distinct taxonomic systems, e.g. psychology the multiple realizability argument. The argument, first and neurophysiology): “(i) As and Bs are of the same kind in advocated by Putnam [1][2] and later by Fodor [3][4], can be model or taxonomic system S1. (ii) As and Bs are of different succinctly summarized as the thesis claiming that the same kinds in model or taxonomic system S2. (iii) The factors that lead mental kind can be realized by different physical kinds (or more the As and Bs to be differently classified by S2 must be among simply, that the same mental state can be realized by different those that lead them to be commonly classified b S1. (iv) The physical states). The ubiquitous example in philosophy of mind relevant S2-variation between As and Bs must be distinct from is the example of pain: pain can be realized by some neural/brain the S1 intra-kind variation between As and Bs” [10]. state in humans, by some other neural/brain state in reptiles, by We can illustrate how these criteria work in practice using some other neural/brain states in Martians etc. So, according to corkscrews, a paradigmatic example used by S& P [10]. To fulfill proponents of the multiple realizability thesis (MRT), the mental the first two criteria, the MR candidate corkscrews A and B have kind pain can be realized by various physical kinds. The kind to be classified as the same by one taxonomic system, and as pain therefore, cannot be reduced to a single neural kind, and it distinct by a lower-level taxonomic system, thus being ‘same but follows that identity theory regarding the mind-body problem is different’ [10]. The third criteria is not as straightforward: two false. differently coloured corkscrews are not MR because colour is not The MRT seemed to go unchallenged throughout the second causally relevant to performing the function of the corkscrew part of the 20th century; however, it has recently been (does not meet condition iii). On the other hand, two different problematized by various authors in philosophy of mind (Kim kinds of corkscrews, a winged and a waiter’s corkscrew, which [5], Bechtel and Mundale [8]; Shapiro [9] [5], Polger [6]). There use different mechanisms to remove a cork, do count as MR, are many approaches to argue against MRT, but the most because they perform the desired function in different ways. So, important one seems to be defining when kinds are in fact to fulfill the third criterion, the corkscrews A and B have to multiply realized. Two sets of authors (among others) have perform the same function in different ways. The fourth presented their criteria for multiple realizability (MR), with both condition is a safeguard that prevents intra-kind realizer differences to count as MR, namely, if, e.g. two winged Permission to make digital or hard copies of part or all of this work for personal or corkscrews had levers that were of a different length, then the classroom use is granted without fee provided that copies are not made or differences in length would translate into differences in function distributed for profit or commercial advantage and that copies bear this notice and – perhaps a really sturdy cork could only be removed by a the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). corkscrew with a longer lever. However, Aizawa and Gillet (A&G) developed different Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). criteria for MR, namely: “A property G is multiply realized if and 188 only if (i) under condition $, an individual s has an instance of (the structures of the eyes is virtually the same, only the material property G in virtue of the powers contributed by instances of is different), and Shapiro (and Polger) [10] would agree that it is properties/relations F –F to s, or s's constituents, but not vice not a case of multiple realizability, whereas Fodor and Block [13] versa; (ii) under condition $* (which may or may not be identical (and Aizawa and Gillet [11][12]) would argue that it is. to $), an individual s* (which may or may not be identical to s) Gillet further argues that the flat view, which S&P adopt, is has an instance of a property G in virtue of the powers not what some proponents of MR, Fodor and Block, had in mind. contributed by instances of properties/relations F* –F* of s* or If that is the case, then S&P’s argument, so says Gillet, is moot, s*'s constituents, but not vice versa; (iii) F –F ≠ F* –F* ; and (iv), as it rests on the wrong view of realization (i.e. flat instead of under conditions $ and $*, F –F and F* –F* are at the same dimensioned). That is obviously correct: if Fodor had the scientific level of properties” [11]. dimensioned view in mind, then S&P’s attempts to refute the flat The first two conditions are similar: two corkscrews are in a view of MR is sterile. certain state, removing corks (property G), which is, in the first However, things are not as simple as they seem. A&G subject, realized by some physical realizer (F –F), and by a allegedly adopt the ‘correct’ view of realization, yet their different physical realizer (F* –F*) in the second (or the same) conclusions about special sciences are far from that of Fodor’s. subject. The third condition states that the two realizers are not Namely, they imply that “multiple realization simply does not the same (F –F ≠ F* –F*). Since G is realized ‘in virtue of the establish the methodological autonomy of cognitive science” powers contributed’ by F –F or F* –F*, this excludes irrelevant [11]. This is a strange consequence, considering that the Fodor’s properties (similar to S&P’s approach, the colour in the project as stated in his article, “Special Sciences: Still aforementioned cases). The first three conditions are roughly the Autonomous After All These Years” was to show that special same as in S&P’s criteria. Furthermore, the fourth condition only sciences are autonomous [4[4]. Of course, just because A&G’s states that the analysed physical realizers should be at the same conclusions differ from Fodor does not mean that their account scientific level of properties. This criterion is, of course, “usually of MR is incorrect, but claiming that they interpreted Fodor implicitly accepted as a shared background condition in earlier correctly should be taken with a grain of salt: especially discussions of multiple realization in the sciences” [11]. considering that Fodor’s main conclusion, the autonomy of Even though the criteria are similar, the conclusions could not be special sciences, does not follow from their account. However, more different: one side argues that two corkscrews made of one could argue that a case that would satisfy S&P’s MR criteria different materials, e.g. aluminium and steel, are not multiply would probably secure autonomy in psychology in Fodor’s sense. realized, whereas the other side says that they are. Why? One S&P otherwise argue for a modest identity theory, partly because possible answer is offered by Gillet [12], where he argues that no positive case (regarding mental kinds) that would pass their S&P, compared to A&G, use a different view of realization. criteria has been presented so far. [10] What, according to them, Namely, S&P adopt the flat view of realization, whereas A&G their position implies for the autonomy of psychology is a adopt the dimensioned view. different story, beyond the scope of this article. Shapiro concludes that, “Steel and aluminum are not different Nevertheless, the purpose of the paper is not to dwell in realizations of a waiter's corkscrew because, relative to the exegetical debates. However, revisiting the problem behind the properties that make them suitable for removing corks, they are motivation for Fodor’s project might be instructive. Fodor has identical. The fact that one corkscrew is steel and the other two reason why special sciences are (probably) MR and aluminum is no more reason to characterize them as different autonomous. First, there are natural kinds that do not correspond realizations than the fact that one might be yellow and the other to physical kinds, because we can make interesting red”[7]. Whereas Gillet argues that, “For with one corkscrew the generalizations about events that have distinct physical properties/relations of steel molecules result in the powers descriptions; moreover, the physical descriptions of these events, individuative of the property of removing corks, while in the whether they are similar or not, are entirely irrelevant to the truth other corkscrew the distinct properties/relations of aluminium of the generalizations [3]. Second, the problem for reductionism atoms play this role. We should carefully mark that this judgment is that physical laws are exceptionless, and laws of special accords with the criterion-for only properties/relations that result sciences are not. If special sciences are reduced to physical in the powers of the realized property are taken to be relevant to sciences via bridge laws, and physical laws and bridge laws are MR” [12]. exceptionless, how can the laws of special sciences have exceptions? “In short, given the reductionist model, we cannot consistently assume that the bridge laws and the basic laws are 3 FODOR’S PROJECT exceptionless while assuming that the special laws are not” [3]. 1 The case is analogous to Putnam’s famous example of It seems that Fodor tries to solve the following problem: how mammalian and octopus’s eyes. Putnam [2] claims that the can the laws of special sciences be reduced to physical laws, if differences in materials are not relevant to the realized function the former are not exceptionless, whereas the latter are? Fodor 1 Fodor defines natural kinds in terms of laws, “roughly, the natural kind predicates of a science are the ones whose terms are the bound variables in its proper laws” [3]. 189 offers two solutions, “we can give up the claim that the special a faster processor and will realize the program faster (this does laws have exceptions or we can give up the claim that the basic not mean that we cannot imagine, or that there do not exist, any laws are exceptionless” [3]. Both options are undesirable: circumstances where two distinct computers can perform the obviously, special laws have exceptions, and going down the same aspect of a program in the same way, but the totality of their path of physical laws having exceptions also seems like a very functions in various contexts will not be isomorphic). dangerous path. However, we believe that there is a third path: to The same seems to hold for generalizations in special deny that special sciences predicates pick out natural kinds (i.e. sciences: instead of listing countless similar but minutely to deny that they are genuine laws). different laws/kinds, psychologists ignore some details that are irrelevant and idealize others to develop powerful generalizations that are extremely useful. The very fact that they 4 THE GRANULARITY PROBLEM AND idealized and abstracted (or coarse grained) means that they are SPECIAL SCIENCES no longer describing natural kinds (as there are too many to Bechtel and Mundale [6] offered an explanation of why MR describe), but they gain in simplification and generalization. This seems so intuitive in philosophy of mind. They claim that also explains why special science laws have exceptions: they do philosophers have used different grains when establishing MR, not always work precisely because they are abstracted and i.e. they used a coarse grain in identifying mental kinds and a idealized laws of countless similar but not identical phenomena, very fine grain when identifying physical kinds. Whereas and finding out which details are irrelevant and which important Bechtel and Mundale claimed that this is only characteristic of is an extremely difficult task. philosophers, we would like to expand the claim and argue that using coarser grains for higher order sciences is literally what enables us to make interesting and useful generalizations about 5 CONCLUSION the world. Let’s illustrate this with corkscrews. Both camps Does this mean that special sciences do not accurately describe (S&P and A&G) seem to be familiar with the granularity the world? Yes, and no. Yes, because, strictly speaking, they argument, yet their approaches do not seem to reflect that. Both disregard details and idealize others to form powerful, use a very fine grain to identify physical kinds, but neither pays informative, and useful generalizations. No, because the world is much attention in setting the conditions for identifying the same too complex to talk about it accurately. Are special sciences mental kinds. reducible to physical sciences, i.e. are type identical Take the two different kinds of corkscrews (of which both psychological states reducible to type identical neurological S&P and A&G agree that they are MR). Are they functionally states? No, but not because they are multiply realized, but isomorphic, i.e. do they perform the same function in all because there are no type identical psychological states: contexts? Imagine we have to work in very low spaces, say you psychological states (and other special sciences predicates) are want to open a bottle of wine in a box that is only 5 cm taller than useful abstractions (as Davidson has shown, but for another the bottle: the winged corkscrew will not do the job, whereas the reason [14]), that enable us to generalize about states that are waiter’s corkscrew will. Even though the corkscrews perform a minutely distinct, but, for all intents and purposes, identical. similar (or even the same) function in most situations and contexts, they differ in some. And if they differ in some, they cannot be functionally isomorphic. Similar for the aluminium REFERENCES and steel corkscrew: they differ regarding the temperature of the [1] Hilary Putnam, 1967. Psychological Predicates . In Art, Mind, and cork removal (e.g. at 800 ºC) The melting point of steel is 1370 Religion. University of Pittsburgh Press, Pittsburgh, 37-48. [2] Hilary Putnam 1975. The Nature of Mental States. In Mind, Language and ºC, whereas the melting point of aluminium is 660.3 ºC. Reality – Philosophical Papers, Volume 2. Cambridge University Press, Therefore, the two corkscrews will not be functionally Cambridge, pp. 429-440. DOI: https://doi.org/10.1017/CBO9780511625251.023. isomorphic in all contexts, which, if they are natural kinds, [3] Jerry Fodor 1974. Special Sciences, or: the Disunity of Science as a should be the case. Yes, the differences are extremely small, one Working Hypothesis. Synthese 28, 2 (Oct, 1974), 97-115. could say irrelevant, but they do exist. However, we ignore them DOI: https://doi.org/10.1007/BF00485230. [4] Jerry Fodor 1997. Special Sciences: Still Autonomous After All These (or we use a coarser grain) because they are so minute and rare Years. Philosophical Perspectives 11 (1997), 149-163. that they are completely irrelevant compared to the extreme DOI: https://doi.org/10.1111/0029-4624.31.s11.7 [5] Jaegwon Kim 1992. Multiple Realization and the Metaphysics of usefulness of the powerful generalizations that we acquire, if Reduction. Philosophy and Phenomenological Research 52, 1 (March, these differences are cast aside. They are similar enough, which 1992), pp. 1-26. enables us to use these generalizations with great proficiency. DOI: 10.2307/2107741. [6] William Bechtel and Jennifer Mundale 1999. Multiple Realizability This is not exclusive to corkscrews (or to special sciences). Revisited: Linking Cognitive and Neural States. Philosophy of Science 66, Even the most textbook example of MR is vulnerable to such 2 (June, 1999), pp. 175-207. DOI: https://doi.org/10.1086/392683. granularity. Take a mechanical and an electronic computer, [7] Lawrence Shapiro 2000. Multiple Realizations. The Journal of Philosophy which are both realizing a Turing machine, i.e. they are 97, 12 (December, 2000), pp. 635-654. functionally isomorphic. Note that we are again applying a very DOI: 10.2307/2678460 [8] Lawrence Shapiro 2004. The Mind Incarnate. MIT Press, Cambridge, narrow context in which they are functionally isomorphic. If we MA. add a massive magnet to both computers, the mechanical [9] Thomas Polger 2004. Natural minds. MIT Press, Cambridge, MA. DOI: https://doi.org/10.7551/mitpress/4863.001.0001. computer will still perform the function, whereas the electronic [10] Thomas Polger and Lawrence Shapiro 2016. The Multiple Realization will not. Take two distinct electronic computers: one might have Book. Oxford University Press, Oxford. DOI: https://doi.org/10.1093/analys/anx078 190 [11] Ken Aizawa and Carl Gillet 2009. Levels, Individual Variation, and Massive Multiple Realization in Neurobiology. In The Oxford Handbook of Philosophy and Neuroscience, Oxford University Press, New York, pp. 539-581. DOI: 10.1093/oxfordhb/9780195304787.001.0001. [12] Carl Gillet 2003. The Metaphysics of Realization, Multiple Realizability, and the Special Sciences. The Journal of Philosophy 100, 11 (November, 2003), pp. 591-603. DOI: 10.2307/3655746. [13] Ned Block and Jerry Fodor 1972. What Psychological States are Not. The Philosophical Review 81, 2 (Apr, 1972), 159-181. DOI: 10.2307/2183991 [14] Donald Davidson 1970. Mental Events, In Essays on Actions and Events, Oxford: Clarendon Press, New York, NY, 1980, pp. 207-225. 191 192 Zbornik 23. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2030 Zvezek C Proceedings of the 23rd International Multiconference INFORMATION SOCIETY – IS 2020 Volume C Odkrivanje znanja in podatkovna skladišča - SiKDD Data Mining and Data Warehouses - SiKDD Uredila / Edited by Dunja Mladenić, Marko Grobelnik http://is.ijs.si 5. oktober 2020 / 5 October 2020 Ljubljana, Slovenia 193 194 PREDGOVOR Tehnologije, ki se ukvarjajo s podatki so v devetdesetih letih močno napredovale. Iz prve faze, kjer je šlo predvsem za shranjevanje podatkov in kako do njih učinkovito dostopati, se je razvila industrija za izdelavo orodij za delo s podatkovnimi bazami, prišlo je do standardizacije procesov, povpraševalnih jezikov itd. Ko shranjevanje podatkov ni bil več poseben problem, se je pojavila potreba po bolj urejenih podatkovnih bazah, ki bi služile ne le transakcijskem procesiranju ampak tudi analitskim vpogledom v podatke – pojavilo se je t.i. skladiščenje podatkov (data warehousing), ki je postalo standarden del informacijskih sistemov v podjetjih. Paradigma OLAP (On-Line-Analytical-Processing) zahteva od uporabnika, da še vedno sam postavlja sistemu vprašanja in dobiva nanje odgovore in na vizualen način preverja in išče izstopajoče situacije. Ker seveda to ni vedno mogoče, se je pojavila potreba po avtomatski analizi podatkov oz. z drugimi besedami to, da sistem sam pove, kaj bi utegnilo biti zanimivo za uporabnika – to prinašajo tehnike odkrivanja znanja v podatkih (data mining), ki iz obstoječih podatkov skušajo pridobiti novo znanje in tako uporabniku nudijo novo razumevanje dogajanj zajetih v podatkih. Slovenska KDD konferenca pokriva vsebine, ki se ukvarjajo z analizo podatkov in odkrivanjem znanja v podatkih: pristope, orodja, probleme in rešitve. FOREWORD Data driven technologies have significantly progressed after mid 90’s. The first phases were mainly focused on storing and efficiently accessing the data, resulted in the development of industry tools for managing large databases, related standards, supporting querying languages, etc. After the initial period, when the data storage was not a primary problem anymore, the development progressed towards analytical functionalities on how to extract added value from the data; i.e., databases started supporting not only transactions but also analytical processing of the data. At this point, data warehousing with On-Line-Analytical-Processing entered as a usual part of a company’s information system portfolio, requiring from the user to set well defined questions about the aggregated views to the data. Data Mining is a technology developed after year 2000, offering automatic data analysis trying to obtain new discoveries from the existing data and enabling a user new insights in the data. In this respect, the Slovenian KDD conference (SiKDD) covers a broad area including Statistical Data Analysis, Data, Text and Multimedia Mining, Semantic Technologies, Link Detection and Link Analysis, Social Network Analysis, Data Warehouses. 195 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Janez Brank, Department of Artificial Intelligence, Jožef Stefan Institute, Ljubljana Marko Grobelnik, , Department of Artificial Intelligence, Jožef Stefan Institute, Ljubljana Branko Kavšek, University of Primorska, Koper Aljaž Košmerlj, Qlector, Ljubljana Dunja Mladenić, Department of Artificial Intelligence, Jožef Stefan Institute, Ljubljana Inna Novalija, Department of Artificial Intelligence, Jožef Stefan Institute, Ljubljana Luka Stopar, Sportradar, Ljubljana 196 A Dataset for Information Spreading over the News Abdul Sittar Dunja Mladenić Tomaž Erjavec Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia abdul.sittar@ijs.si dunja.mladenic@ijs.si tomaz.erjavec@ijs.si ABSTRACT Table 1: List of events Analysing the spread of information related to a specific event in Selected events Other events (ordered by popularity) the news has many potential applications. Consequently, various Football Basketball, Baseball, Boxing, Tennis, Cycling systems have been developed to facilitate the analysis of infor- Earthquake Floods, Tsunamis, Landslides, Hurricane, Volcanic eruptions mation spreading, such as detection of disease propagation and Global warming CO2 emissions, Chemical consumption identification of the spreading of fake news through social media. The paper proposes a method for tracking information spread over news articles. It works by comparing subsequent articles via limited availability of datasets containing news text and metadata cosine similarity and applying a threshold to classify into three including time, place, source and other relevant information. classes: “Information-Propagated”, “Unsure” and “Information- When a piece of information starts spreading, it implicitly not-Propagated”. There are several open challenges in the process raises questions such as: of discerning information propagation, among them the lack of (1) How far does the information in the form of news reach resources for training and evaluation. This paper describes the out to the public? process of compiling corpus from the Event Registry global me- (2) Does the content of news remain the same or changes to dia monitoring system. We focus on information spreading in a certain extent? three domains: sports (i.e. the FIFA World Cup), natural disas- (3) Do the cultural values impact the information especially ters (i.e. earthquakes), and climate change (i.e. global warming). when the same news will get translated in other languages? This corpus is a valuable addition to currently available dataset This paper presents a corpus that focuses on information to examine the spreading of information about various kind of spreading over news and that hopes to answer some of the above events. questions (This corpus is published as an online resource at ). We present the use of a news repository to produce a corpus KEYWORDS and then analyze information propagation. We present a novel Datasets, Information propagation, News articles methodology for automatically assembling the corpus for this problem and validate it in three different domains. We focused 1 INTRODUCTION on a combination of rich- and low resource European languages, Information spreading has received significant attention due to in particular English, Portuguese, German, Spanish, and Slovene. its various market applications such as advertisement. did the in- Three different types of events are targeted in the data collection formation about a specific product reach to the public of a specific procedure to potentially involve different information spreading region? This could be one of the significant research questions. behaviors in our society. These events are sports (FIFA World Research in this area considers influential factors in the process Cup, 2,695 articles), natural disasters (earthquakes, 3,194 articles), of information spreading such as the economic condition of a and climate change (global warming, 1,945 articles). The three specific area related to how textual or visual content is helping to types of events were chosen based on their popularity and diver- advertise a product. Information spreading analytics can also be sity. A list of sub-events was observed from top websites related used in shaping policies, e.g., in media companies to understand to the three events and we selected those which were the most if there is a need to improve the content before publishing it. popular in the countries with the selected national languages. For Health organizations may be interested to know the patterns of sports, a list of countries with their national sports was fetched spreading of a cure for a certain disease. Environmental scien- and then filtered for national language1, 2. Based on popularity, tists are perhaps attentive to see whether spread of news about we selected the FIFA world cup. Similarly, for natural disasters, climate changes inside the country is similar to what is being lists of natural disasters were collected by country taking the na- reported internationally. tional language into account, for instance, for Slovenia we looked Domain-specific gaps in information spreading are ubiquitous, for this country in the natural disaster category on Wikipedia3. and may exist due to economic conditions, political factors, or Earthquakes4 and global warming5 were found to be the most linguistic, geographical, time-zone, cultural and other barriers. prevalent, thus a dataset for each was collected. Table 1 shows the These factors potentially contribute to obstructing the flow of selected events and other related events ordered by prevalence. local as well as international news. We believe that there is a lack The paper makes the following contributions to science: of research studies which examine, identify and uncover the rea- (1) a novel methodology to collect a domain-specific corpus sons for barriers in information spreading. Additionally, there is from news repository; (2) semantic similarity between news articles; Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and 1http://www.quickgs.com/countries-and-their-national-sports/ the full citation on the first page. Copyrights for third-party components of this 2https://www.topendsports.com/ work must be honored. For all other uses, contact the owner/author(s). 3https://en.wikipedia.org/wiki/Category:Natural_disasters_in_Slovenia Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia 4https://en.wikipedia.org/wiki/List_of_earthquakes_in_2020 © 2020 Copyright held by the owner/author(s). 5https://www.theguardian.com/environment/2011/apr/21/countries-responsible- climate-change, 6 197 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Abdul Sittar, Dunja Mladenić, and Tomaž Erjavec (3) an annotated dataset encoding the level of information spreading from an article. The rest of the paper is organized as follows: in Section 2 we discuss prior work about information spreading; in Section 3 we describe the data collection methodology; Section 4 describes semantic similarity and dataset annotation; and Section 5 gives the conclusions. 2 RELATED WORK Information spreading is prevalent in our society. It plays a vi- tal part in tasks that encompass the spreading of innovations [9], effects in marketing [6], and opinion spreading [4]. News spreading provides information to consumers that can be used for decision making and potentially contribute to shaping na- tional and international policies. There are several types of media Figure 1: Data collection methodology involved, such as print media, broadcast, and internet media. In- ternet is considered as a building block for connecting individuals worldwide, while news reflects current significant events for peo- ple [7]. Apart from news, online social media proved to be a remarkable alternative to support information spreading in an emergency [8, 5]. Social connection plays a vital role in news spreading. Especially the structure of network reflecting who is connected to whom, crucially increases the proportion of in- formation spreading. Network structure analysis comes with a hypothesis related to the strength of the connections, namely that information will spread further in a situation where there exist many weak connections rather than clusters of strong [2]. While, in general, there are not many dataset that would help in modelling information spreading, there are some corpora for detecting the spreading of information about diseases [3] and fake news in social media [10]. There is currently no multilingual dataset of news articles for analysis of information propagation composed from a variety of event-centric information such as Figure 2: Articles with metadata sports, natural disasters, and climate changes. This provides ad- ditional motivation for our work. Table 2: Statistics about dataset 3 DATA COLLECTION METHODOLOGY Dataset Domain Event type Articles per Language Total Articles Eng Spa Ger Slv Por In order to collect news originating from different sources, in 1 Sports FIFA World Cup 983 762 711 10 216 2682 2 Natural Disaster Earthquake 941 999 937 19 251 3147 different languages, and targeting diverse events, we used Event 3 Climate Changes Global Warming 996 298 545 8 97 1944 Registry, a platform that identifies events by collecting related articles written in different languages from tens of thousands of news sources [9]. Using Event Registry APIs 7, we fetched a list This service uses a page-rank based method to identify a coherent of articles about each event in the following languages: English, set of relevant concepts from Wikipedia [1]. We retrieved a list Spanish, German, Portuguese, and Slovenian. Figure 1 shows the of Wikipedia concepts for each article. After representing each data collection process. article with a list of Wikipedia concepts, the tf-idf score was com- Each article was parsed from the JSON response and stored in puted using the popular machine learning library Scikit-Learn9. CSV files. Each article was connected with the available list of Using the same library, cosine similarity was calculated between relevant information such as the language of the article, event tf-idf representation of news articles across all five languages. type, publisher, title, date, and time. Figure 2 shows the metadata In the process of computing similarity between the articles, for of articles. each article we calculated its cosine similarity to all other articles The number of collected articles in each domain varies consid- and stored the results in a CSV file. The results were then sorted erably, and also varies across the languages within each domain. based on the publishing time of articles and we kept only the cal- Table 2 shows statistics about each dataset. culations of similarity to articles that are published later that the article in hands. Since we are interested in information propaga- 4 SEMANTIC SIMILARITY BETWEEN NEWS tion, we do not need to compare an article to those articles which ARTICLES have been published before it. As a result, we had a multiple similarity score for each article where each score show the simi- We have represented the cross-lingual news articles by monolin- larity with other articles. Cosine similarity varies between zero gual (English) Wikipedia concepts using the Wikifier service8. and one, zero meaning no similarity and one meaning maximum 7https://github.com/EventRegistry/event-registry-python/blob/master/ similarity, i.e., a duplicate article. eventregistry/examples/QueryArticlesExamples.py 8http://wikifier.org/info.html 9https://scikit-learn.org/stable/ 198 A Dataset for Information Spreading over the News Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Table 3: Selected articles for evaluation Domains Percentage of correctly labelled pairs Global Warming 100% Earthquake 93% FIFA World Cup 100 % for Portuguese, German, Slovene and Spanish to translate them into English. Evaluation results shown that the annotation was significantly related to information spreading. Articles in the "Information- Propagated" class show that most articles were an exact or para- phrased copy of each other, with some articles published within few hours after each other. Articles in the "Unsure" class were Figure 3: Class distribution for all domains typically also relevant to the event but involved extra and dif- ferent discussions. Lastly, in the third class "Information-Not- Propagated", articles involved only keywords related to event but discussion was about other topics. Moreover, here the gap in the 4.1 Dataset annotations publishing time was quite large. The results of the semantic similarity calculation were in the form of a table where rows shown the list of articles and columns shown the corresponding similarity score in the range 0..1 with 5 CONCLUSIONS all the other articles. This similarity score was calculated using This paper proposed a methodology and explained the process cosine between TF-IDF representation of news articles (See Sec- of data collection from a news repository to provide a corpus tion ??). First, we excluded those articles which had scored 1.0, for event-centric information propagation between news articles. as they were considered as a copy of the article. We then, for This corpus covers three domains and each dataset corresponds each article, chose an article which had the highest similarity to one event type (FIFA World Cup, Earthquake, and Global score to it from the list of all articles. After performing this step, Warming). The corpus is available to others for the evaluation we had one similarity score for each article which shows either of techniques for information spreading as it allows the analysis that the information spread to a certain extent (if >0) or not (if of cross-lingual news articles published by different publishers 0). To decide about the class label whether the information is located geographically in different places. spreading or not, we divided the scores into three intervals. The In the future, we plan to add more attributes to each dataset. first is Similarity ≥ 0.7, the second is 0.7 > Similarity ≥ 0.4, For instance, for now, we only know the publisher of a news and the third is Similarity < 0.4. Articles that have scores in article but in the future, we would like to include the publisher the first interval were labeled as "Information-Propagated". The profile and the economic condition of a country from where the second interval was considered as unclear whether the informa- information is published. Also, we plan to apply and evaluate tion from the article propagated or not such articles were labeled different techniques to analysis information propagation barriers. as "Unsure". The lowest interval was considered as a signal for no propagation and labeled "Information-not-Propagated". For 6 ACKNOWLEDGEMENTS instance, low similarity can be of an article about a sports ground which mentions the population of the city and another article This work was supported by the Slovenian Research Agency and that discusses the population itself. We have manually examined the project leading to this publication has received funding from concepts of articles in each class. Figure 3 shows the distribu- the European Union’s Horizon 2020 research and innovation tion of class labels in FIFA World Cup, Earthquake, and Global programme under the Marie Skłodowska-Curie grant agreement Warming dataset respectively. No 812997. REFERENCES 4.2 Evaluation of dataset [1] Janez Brank, Gregor Leban, and Marko Grobelnik. 2017. Each article was annotated with a label based upon the similarity Annotating documents with relevant wikipedia concepts. score threshold of each article with other articles (See Section In Proceedings of Slovenian KDD Conference on Data Mining 4.1). For evaluation of the dataset we have checked the content of and Data Warehouses (SiKDD). the corresponding articles which were responsible for a specific [2] Damon Centola. 2010. The spread of behavior in an online class label. We performed the evaluation of labelling by manually social network experiment. science, 329, 5996, 1194–1197. inspecting a subset of pairs of articles. If a pair, for instance, were [3] Emily Chen, Kristina Lerman, and Emilio Ferrara. 2020. labelled as "Information-Propagated" then two articles should Covid-19: the first public coronavirus twitter dataset. arXiv have text discussing more or less the same event, both in mono- preprint arXiv:2003.07372. and cross-lingual settings. [4] David Liben-Nowell and Jon Kleinberg. 2008. Tracing in- We have randomly chosen 10 articles with their corresponding formation flow on a global scale using internet chain-letter articles considering all languages in each class and in each dataset. data. Proceedings of the national academy of sciences, 105, In this way, we have manually checked 180 articles. Table 3 shows 12, 4633–4638. these pairs of articles for evaluation in each dataset. We scanned each article manually for all languages, using Google Translator 199 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Abdul Sittar, Dunja Mladenić, and Tomaž Erjavec [5] Kees Nieuwenhuis. 2007. Information systems for crisis crisis informatics: study of 2013 oklahoma tornado. Trans- response and management. In International Workshop on portation Research Record, 2459, 1, 110–118. Mobile Information Technology for Emergency Response. [9] Duncan J Watts and Peter Sheridan Dodds. 2007. Influen- Springer, 1–8. tials, networks, and public opinion formation. Journal of [6] Everett M Rogers. 2010. Diffusion of innovations. Simon consumer research, 34, 4, 441–458. and Schuster. [10] Zilong Zhao, Jichang Zhao, Yukie Sano, Orr Levy, Hideki [7] Sandeep Suntwal, Susan Brown, and Mark Patton. 2020. Takayasu, Misako Takayasu, Daqing Li, Junjie Wu, and How does information spread? an exploratory study of Shlomo Havlin. 2020. Fake news propagates differently true and fake news. In Proceedings of the 53rd Hawaii In- from real news even at early stages of spreading. EPJ Data ternational Conference on System Sciences. Science, 9, 1, 7. [8] Satish V Ukkusuri, Xianyuan Zhan, Arif Mohaimin Sadri, and Qing Ye. 2014. Use of social media data to explore 200 Learning to fill the slots from multiple perspectives Patrik Zajec Dunja Mladenič patrik.zajec@ijs.si dunja.mladenic@ijs.si Jožef Stefan Institute and Jožef Stefan International Jožef Stefan Institute and Jožef Stefan International Postgraduate School Postgraduate School Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT Furthermore, since the set of topics is not fixed and could expand We present an approach to train the slot-filling system in a fully over time, such a slot filling system should be able to adapt quickly automatic, semi-supervised setting on a limited domain of events to fill new slots and ideally should not be limited to the English from Wikipedia using the summaries in different languages. We language. use the multiple languages and the different topics of the events We believe that annotation work can be greatly minimized to provide several alternative views on the data. Our experiments if we rely on our limited domain to identify and annotate only show how such an approach can be used to train the multilingual informative examples and use the additional assumptions to prop- slot-filling system and increase the performance of a monolingual agate these labels. We also believe that simultaneous training of system. the system on multiple topics can be advantageous, as we can introduce additional supervision on the common slots and use KEYWORDS distinct slots as a source of negative examples. In this work we use Wikipedia and Wikidata [9] as the source information extraction, slot filling, machine learning, probabilis- of data. We treat the Wikidata entities that have the point-in-time tic soft logic property specified as events and summary sections of Wikipedia articles about the entity in different languages as news articles. 1 INTRODUCTION Each entity belongs to a single topic and we adopt the subset of This paper is addressing the slot filling task that aims to extract topic-specific properties as slot keys. An automatic exact match- the structured knowledge from a given set of documents using a ing of such values from Wikidata with named entities from model trained for a specific domain and the associated slots. For Wikipedia articles is rarely successful. We use the successful example, within a news article reporting on an earthquake, the and unambiguous matches as a set of labeled seed examples. task is to detect the earthquake’s magnitude, the number of peo- We formulate the task as a semi-supervised learning problem ple injured, the location of the epicentre and other information. [8] where the set of base learners is trained iteratively, starting We refer to those as a set of slot keys or slots, to their exact values with a small seed set of labeled examples and a larger set of unla- as a slot values and to the named entities from the documents beled examples. In each iteration, the most confident predictions corresponding to those values as target entities. on the examples from unlabeled set are used to increase the train- Slot filling is closely related to the task of relation extraction [1] ing set by assigning pseudo-labels. We introduce an additional and can be seen as a kind of unary relation extraction. Both tasks component which combines the confidences of multiple base can be formulated as classification and are usually approached learners for each example. by first training a classifier with a sentence and tagged entities at To the best of our knowledge, we are the first to use the limited the input and the prediction of relation or slot key as the output. domain of news events, which allows the additional assumptions, As there is a large number of relations between entities that such as the connection between slots of different topics and the we might be interested in detecting, there is also a large num- redundancy of reporting in multiple languages, to first train and ber of slot keys we seek the slot value for. In order to avoid the later boost the performance of a slot-filling system. resource-intensive process of annotating a large number of exam- The contributions of this paper are the following: ples for each possible slot/relation and to increase the flexibility • we combine the data from Wikidata and Wikipedia to of training procedures beyond the straight-forward supervised setup a learning and evaluation scenario that mimics the learning, many alternative approaches have been proposed, such learning on news events and articles, as bootstrapping [4], distant supervision [6] and self supervision • we demonstrate how simultaneous learning on multiple [5]. topics and languages can be used not only to train the As stated both tasks can be performed for different types of multilingual slot-filling system, but to also improve the documents. We limit our focus to news events on multiple topics performance of a monolingual system, (such as natural disasters and terrorist attacks), taking the articles • we show how an inference component can be used to com- reporting about events as the documents. Since the number of bine predictions from multiple base learners to improve news topics is large, and consequently so is the number of slots, the pseudo-labeling step of the semi-supervised learning we would like to minimize the need for manual annotations. process. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or 2 METHODOLOGY distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this 2.1 Problem Definition work must be honored. For all other uses, contact the owner/author(s). Given a collection of topics T (such as earthquakes, terrorist Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia attacks, etc.), where each topic 𝑡 has its own set of slot keys S , © 2020 Copyright held by the owner/author(s). 𝑡 the goal is to automatically extract values from the relevant texts 201 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Patrik Zajec and Dunja Mladenič to fill in the slots. For example, the members of S of the XLM Roberta model [3] using the implementation from 𝑒𝑎𝑟 𝑡 ℎ𝑞𝑢𝑎𝑘𝑒𝑠 are number of injured, magnitude and location. For each topic the Transformers 2 library. Note that the representation of each 𝑡 there is a set of events E , each of which took place at some entity remains fixed throughout the learning process because we 𝑡 point in time and was reported by several documents in different have found that the representation is expressive enough for our languages. purposes and it speeds up the training between iterations. Also The values of all or at least most slot keys (or slots) from S are note that since the entity is masked, it is not directly captured in 𝑑 represented in each of the documents as named entities, which the representation. we also refer to as target entities. We say most of the slots, since it is possible that an earthquake caused no casualties. It is also 2.4 Selecting the topics possible that some of the documents do not report about the Our assumption is that training the system to detect the slots on number of casualties as it may be too early to know if there were multiple topics simultaneously can provide additional benefits. any. In addition, the documents might contain different values for For two topics ′ 𝑡 and 𝑡 there is potentially a set of common slots the same slot key, as for example, the reported number of people and a set of topic-specific slots. injured by an earthquake can increase over time. There may also For slot ′ 𝑠 which appears in both topics the base learner trained be several different mentions of the same slot in a particular on ′ 𝑡 can be used to make predictions for examples from 𝑡 . By document, as for example one magnitude might refer to an actual combining predictions from learners trained on ′ 𝑡 and 𝑡 , we could earthquake that the event is about, while the other magnitude get a better estimate of the true labels of the examples. might refer to an earthquake that struck the same region years For the slot 𝑠, which is specific to the topic 𝑡 , all examples from ago. the topic ′ 𝑡 can be used as negative examples. Selecting reliable Our task is actually a two step process. In the first step, the negative examples from the same topic is not easy, as we may goal is to train a system capable of identifying the target entities inadvertently mislabel some of the positive examples. for a set of slot keys from the context, which in our case is limited to a single sentence. Such a system is not yet able to recognise 2.5 Using multiple languages the true value for a given slot if there are multiple different candidates, such as selecting the actual magnitude from several Articles from different languages offer in some ways different reported magnitude values. The goal of the second step is to views on the same event. The slot values we are trying to detect assign a single correct value to each of the slot keys. We assume should appear in all the articles, as they are highly relevant to that inferring the correctness of a value is a document-level task, the event. since it requires a broader context. Solving the first step is a kind The values for slots such as location and time should be con- of prerequisite for the second step, so we focus on it in this paper. sistent across all articles, whereas this does not necessarily apply to other slots such as the number of injured or the number of 2.2 Overview of the proposed method casualties. Matching such values across the articles is therefore not a trivial task, and although a variant of soft matching can be The system is trained iteratively and starts with a noisy seed set, performed, we leave it for the future work and limit our focus which grows larger with pseudo-labeled positive and negative only on the values that can be matched unambiguously. examples. Each of the base learners is trained on the set of la- We can combine the predictions of several language-specific beled examples from the topic (or multiple topics) and language base learners into a single pseudo-label for entities that can be assigned to it. The prediction probabilities for each of the unla- matched across the articles. beled examples are determined by combining the probabilities of all base learners. This is done either by averaging or by feeding 2.6 Assigning pseudo labels the probabilities as approximations of the true labels into the component, which attempts to derive the true value for each ex- Each iteration starts with a set of labeled examples 𝑋 , a set of 𝑙 ample and the error rates for each learner [7]. The examples with unlabeled examples 𝑋 and a set of base learners trained on 𝑋 . 𝑢 𝑙 probabilities above or below the specific thresholds are given a Base learners are simple logistic regression classifiers that use pseudo-label and added to the training set. vector representations of entities as features and classify each The seed set is constructed by matching the slot values ob- example 𝑥 as a target entity for the slot key 𝑠 or not. 𝑠 tained from Wikidata with named entities found in Wikipedia Each base learner ¯ 𝑓 is a binary classifier trained on the la- 𝑡 ,𝑙 articles for each event. There are only a handful of unambigu- beled data for the slot key 𝑠 from the topic 𝑡 and the language ous matches for each slot key, which are labeled as a positive 𝑙 . Such base learners are topic-specific as they are trained on a examples, while the negative examples are all other named en- single topic 𝑠 𝑡 . Base learners ¯ 𝑓 are trained on the labeled data 𝑙 tities from the articles in which they appeared. Figure 1 shows for the slot key 𝑠 from the language 𝑙 and all the topics with the a high-level overview of the proposed methodology. The entire slot key 𝑠. Such base learners are shared across topics, as they workflow is repeated in each iteration until no new examples are consider the examples from all the topics as a single training set. selected for pseudo-labelling. We use the classification probability of the positive class instead of hard labels, ¯𝑠 ¯𝑠 𝑓 (𝑥 ), 𝑓 (𝑥 ) ∈ [0, 1]. 𝑡 ,𝑙 𝑙 2.3 Representing the entities For each entity 𝑥 from a news article with the language 𝑙 Each named entity together with its context forms a single ex- reporting on the event 𝑒 from the topic 𝑡 we obtain the following ample. We annotate each article and extract the named entities predictions: with Spacy 1. To capture the context, we compute the vector • ¯𝑠 ′ 𝑓 ( and all such that ′ , that ′ 𝑥 ) for each 𝑠 ∈ S 𝑡 𝑠 ∈ S 𝑡 𝑡 𝑡 ,𝑙 representation of each entity by replacing it with a mask token is the probability that 𝑥 is a target entity for the slot key and feeding the entire sentence through a pre-trained version 1https://spacy.io/ 2https://huggingface.co/transformers/ 202 Learning to fill the slots from multiple perspectives Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Figure 1: High-level overview of the proposed methodology. 𝑠 , where 𝑠 is a slot key from the topic 𝑡 , using the topic- We have collected the Wikipedia articles and Wikidata in- specific base learner trained on examples from the same formation of 913 earthquakes from 2000 to 2020 in 6 different language on the topic ′ 𝑡 that also has the slot key 𝑠, languages, namely English, Spanish, German, French, Italian and • ¯𝑠 𝑠 𝑓 ( ( and for each Dutch. We have manually annotated the entities of 85 English ′ 𝑥 ) which equals ¯ 𝑓 ′ 𝑦) for each 𝑠 ∈ S𝑡 𝑡 ,𝑙 𝑡 ,𝑙 language ′ 𝑙 such that there is an article reporting about articles using the slot keys number of deaths, (number of injured the same event 𝑒 in that language and contains an entity and magnitude, which serve as a labeled test set and are not in- 𝑦 which is matched to 𝑥 , cluded in the training process. In addition, we have collected the • ¯𝑠 𝑓 (𝑥 ) for each 𝑠 ∈ S , using the shared base learner, which data of 315 terrorist attacks from 2000 to 2020 with the articles 𝑡 𝑙 is on examples from all topics ′ from the same 6 languages. 𝑡 that have the slot key 𝑠. Predictions from multiple base learners for each 𝑥 and 𝑠 are 3.2 Evaluation Settings combined as a weighted average to obtain a single prediction 𝑠 The evaluation for each approach is performed on the labeled 𝑓 (𝑥 ). The weight of each base learner ¯ 𝑓 is determined by its error rate English dataset, where 76 entities are labeled as number of deaths, 𝑒 ( ¯ 𝑓 ) which is estimated using an approach from [7] using both unlabeled and labeled examples. This is done by introducing 45 as number of injured and 125 as magnitude. The threshold the following logical rules (referred to as ensemble rules in [7]) values for the pseudo-labeling are set to 𝑇 = 0.6 and 𝑇 = 0.05. 𝑝 𝑛 for each of the base learners ¯𝑠 The approaches differ by the subset of base learners used to form 𝑓 predicting for 𝑥: ¯ the combined prediction and by the weighting of the predictions. 𝑠 𝑠 𝑠 ¯𝑠 𝑠 𝑠 𝑓 (𝑥 ) ∧ ¬𝑒 ( ¯ 𝑓 ) → 𝑓 (𝑥 ), 𝑎𝑛𝑑 , 𝑓 (𝑥 ) ∧ 𝑒 ( ¯ 𝑓 ) → ¬𝑓 (𝑥 ), Single or multiple languages. In single language setting, only ¬ ¯𝑠 𝑠 𝑠 𝑠 𝑠 𝑠 𝑓 (𝑥 ) ∧ ¬𝑒 ( ¯ 𝑓 ) → ¬𝑓 (𝑥 ), 𝑎𝑛𝑑 , ¬ ¯ 𝑓 (𝑥 ) ∧ 𝑒 ( ¯ 𝑓 ) → 𝑓 (𝑥 ). English articles are used to extract the entities and train the base The truth values are not limited to Boolean values, but instead learners. In the multi-language setting, all available articles are represent the probability that the corresponding ground predicate used and the entities are matched across the articles from the or rule is true. For a detailed explanation of the method we refer same event. the reader to [7]. We introduce a prior belief that the predictions of base learners are correct via the following two rules: Single or multiple topics. In the single topic setting only the examples from the earthquake topic are used. In the multi-topic ¯𝑠 𝑠 𝑠 𝑠 𝑓 (𝑥 ) → 𝑓 (𝑥 ), 𝑎𝑛𝑑 , ¬ ¯ 𝑓 (𝑥 ) → ¬𝑓 (𝑥 ). setting, the examples from terrorist attacks are used as negative Since each examples for the slot key magnitude, the base learners for the 𝑥 can be target entity for at most one slot key, we introduce a mutual exclusion rule: slot keys number of deaths and number of injured are combined as described in the section 2.6. ¯ ′ 𝑠 𝑠 𝑠 𝑓 (𝑥 ) ∧ 𝑓 (𝑥 ) → 𝑒 ( ¯ 𝑓 ). Uniform or estimated weights. In the uniform setting all pre- The rules are written in the syntax of a Probabilistic soft logic dictions of the base learners contribute equally, while in the [2] program, where each rule is assigned a weight. We assign estimated setting the weights of the base learners are estimated a weight of 1 to all ensemble rules, a weight of 0.1 to all prior using the approach described in the section 2.6. belief rules and a weight of 1 to all mutual exclusion rules. The inference is performed using the PSL framework 3. As we obtain 3.3 Results and discussion the approximations for all 𝑥 ∈ 𝑋 , we extend the set of positive 𝑢 examples for each slot 𝑠 The results of all experiments are summarized in the table 1. Since 𝑠 with all 𝑥 such that 𝑓 (𝑥 ) >= 𝑇 and 𝑝 the set of negative examples with all 𝑠 the test set is limited to the topic earthquake and English, only a 𝑥 such that 𝑓 (𝑥 ) <= 𝑇 , 𝑛 for predefined thresholds subset of base learners was used to make the final predictions. We 𝑇 and 𝑇 . 𝑝 𝑛 report the average value of precision, recall and F1 across all slot 3 EXPERIMENTS keys. The threshold of 0.5 was used to round the classification probabilities. 3.1 Dataset Single iteration. Approaches in which base learners are trained To evaluate the proposed methodology, we have conducted ex- on the initial seed set for a single iteration achieve higher preci- periments on two topics: earthquakes and terrorist attacks. sion with the cost of a lower recall. We observe that they distin- 3https://psl.linqs.org/ guish almost perfectly between the slots from the seed set and 203 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Patrik Zajec and Dunja Mladenič Table 1: Results of all experiments. The column Single iteration reports the results of approaches where base learners were trained on the seed set only. Results where base learners were trained in the semi-supervised setting with different weightings of the predictions are reported in the columns Uniform weights and Estimated weights. The values of precision, recall and F1 are averaged over all slot keys. Single iteration Uniform weights Estimated weights Model P R F1 P R F1 P R F1 Single language, single topic 0.94 0.64 0.76 0.83 0.75 0.77 0.84 0.76 0.79 Multiple languages, single topic 0.94 0.64 0.76 0.82 0.74 0.76 0.83 0.75 0.77 Single language, multiple topics 0.91 0.76 0.83 0.83 0.83 0.83 0.86 0.83 0.84 Multiple languages, multiple topics 0.93 0.76 0.83 0.82 0.83 0.82 0.84 0.84 0.84 produce almost no false positives. Using one or more languages REFERENCES has almost no effect on the averaged scores when the number [1] Nguyen Bach and Sameer Badaskar. 2007. A Survey on Re- of topics is fixed. When using multiple topics, a higher recall is lation Extraction. Technical report. Language Technologies achieved without a significant decrease in precision. 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Unsupervised cross-lingual representation learning Most of the loss of precision is due to misclassification between at scale. arXiv preprint arXiv:1911.02116. slots number of deaths and number of injured, similar as the exam- [4] Tianyu Gao, Xu Han, Ruobing Xie, Zhiyuan Liu, Fen Lin, ple "370 people were killed by the earthquake and related building Leyu Lin, and Maosong Sun. 2020. Neural snowball for collapses, including 228 in Mexico City, and more than 6,000 were few-shot relation learning. In Proceedings of AAAI. injured." where 228 was incorrectly classified as number of injured [5] Xu ming Hu, Lijie Wen, Y. Xu, Chenwei Zhang, and Philip S. and not the number of deaths. The use of multiple topics reduces Yu. 2020. Selfore: self-supervised relational feature learning misclassification between these slots and further improves the for open relation extraction. 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In Advances in Neural evaluate this component. A major advantage is its flexibility, Information Processing Systems, 4361–4370. since we can easily incorporate prior knowledge of the slots or [8] Jesper E Van Engelen and Holger H Hoos. 2020. A survey additional constraints on the predictions in the form of logical on semi-supervised learning. Machine Learning, 109, 2, 373– rules. 440. [9] Denny Vrandečić and Markus Krötzsch. 2014. Wikidata: a 4 CONCLUSION AND FUTURE WORK free collaborative knowledgebase. Communications of the We presented an approach for training the slot-filling system ACM, 57, 10, 78–85. which can benefit from large amounts of data from Wikipedia. The experiments were performed on a relatively small dataset and show that the proposed direction seems promising. However, the right test of our approach would be to apply it to a much larger number of topics and events, which will be done in the immediate next step. Furthermore, the current approach needs to be evaluated in more detail. ACKNOWLEDGMENTS This work was supported by the Slovenian Research Agency and NAIADES European Unions project under grant agreement H2020-SC5-820985. 204 Knowledge graph aware text classification Nela Petrželková∗ Blaž Škrlj Nada Lavrač Jožef Stefan Institute Jožef Stefan Institute and Jožef Stefan Institute Ljubljana, Slovenia Jožef Stefan Int. Postgraduate School Ljubljana, Slovenia nela.petrzelkova@seznam.cz Ljubljana, Slovenia nada.lavrac@ijs.si blaz.skrlj@ijs.si ABSTRACT (2) The proposed method is extensively empirically evaluated, Knowledge graphs are becoming ubiquitous in many scientific indicating that the proposed semantic feature construc- and industrial domains, ranging from biology, industrial engi- tion aids the classification performance on many real-life neering to natural language processing. In this work we explore datasets. how one of the largest currently available knowledge graphs, the (3) The implemented method is freely available3 with a simple- Microsoft Concept Graph, can be used to construct interpretable to-use, scikit-learn API. features that are of potential use for the task of text classification. The paper is structured as follows. Section 2 presents the By exploiting graph-theoretic feature ranking, introduced as part background and related work. Section 3 presents the proposed of the existing tax2vec algorithm, we show that massive, real-life approach to semantic feature construction using the information knowledge graphs can be used for the construction of features, from a given knowledge graph. Section 4 describes the experi- derived from the relational structure of the knowledge graph mental setting and the results, followed by a summary and further itself. To our knowledge, this is one of the first approaches that work in Section 5. explores how interpretable features can be constructed from the Microsoft Concept graph with more than five million concepts 2 BACKGROUND AND RELATED WORK and more than 80 million IsA relations for the task of text classi- In text classification tasks, characterized by short documents fication. The proposed solution was evaluated on eight real-life or small amounts of documents, deep learning methods are fre- text classification data sets. quently outperformed by more standard approaches, including SVMs [4]. In such settings, it was shown that approaches capa- KEYWORDS ble of using semantic context may outperform the naïve learn- knowledge graphs, text classification, feature construction, se- ing approaches, the examples are among other based on Latent mantic enrichment Dirichlet Allocation [5], Latent Semantic Analysis [6] or word embeddings [7], which is referred to as first-level context. 1 INTRODUCTION Second-level context can be introduced by adding background Text classification is the process of assigning labels to text accord- knowledge into a learning process, which may help to increase ing to its content. It is one of the fundamental tasks in Natural performance and improve interpretability. Usage of knowledge Language Processing (NLP) with various applications such as graphs also helped in classification with extending neural net- spam detection, topic labeling, sentiment analysis, news catego- work based lexical word embedding objective function [8]. El- rization and many more [1]. In recent years, knowledge graphs— hadad et al. [9] present an ontology-based web document, while real-life graph-structured sources of knowledge—are becoming Kaur et al. [10] propose a clustering-based algorithm for docu- an interesting source of background knowledge, potentially use- ment classification that also benefits from knowledge stored in ful in contemporary machine learning [2]. Knowledge graphs, the underlying ontologies. Use of hypernym-based features was such as DBPedia1 or the Microsoft Concept Graph2 span tens of performed already in e.g., the Ripper rule learning algorithm [11]. millions of triplets of the form subject-predicate-object, and in- Wang and Domeniconi [12] used the derived background knowl- clude many potentially interesting relations, from which a given edge from Wikipedia for text enriching. In short document clas- machine learning algorithm can potentially benefit. sification, it was shown that the tax2vec algorithm (described In this work we propose an approach to scalable feature con- below) can help those classifiers gain better results by adding struction from one of the largest freely available knowledge extra semantic knowledge to the feature vectors. graphs, and demonstrate its utility on multiple real life data sets. The tax2vec [3] is an algorithm for semantic feature construc- The main contributions of this work are as follows: tion that can be used to enrich the feature vectors constructed by the established text processing methods such as the tf-idf. It (1) We propose an extension to the tax2vec [3] algorithm for takes as input a labeled or unlabeled corpus of documents and a semantic feature construction, adapting it to operate with word taxonomy, i.e. a directed graph to which parts of a given real-life knowledge graphs comprised of tens of millions document map to. It outputs a matrix of semantic feature vectors of triplets. where each row represents a semantics-based vector representa- 1https://wiki.dbpedia.org/ tion of one input document. It makes it by mapping the words 2https://concept.research.microsoft.com/Home/Introduction from the document to a given taxonomy, WordNet or in this work Microsoft Concept Graph, by which it creates the collection of Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or terms for each document and from it, a corpus taxonomy—a rela- distributed for profit or commercial advantage and that copies bear this notice and tional structure specific to the considered document space. The the full citation on the first page. Copyrights for third-party components of this terms presented in the corpus taxonomy represent the potential work must be honored. For all other uses, contact the owner/author(s). Information society ’20, October 5–9, 2020, Ljubljana, Slovenia features. © 2020 Copyright held by the owner/author(s). 3https://github.com/SkBlaz/tax2vec 205 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Petrželková et al. 3 KNOWLEDGE GRAPH-BASED SEMANTIC Table 1: Part of the Microsoft Concept Graph. The row is FEATURE CONSTRUCTION in form of hypernym - hyponym - frequency of relation Semantic features are constructed as follows. With the help of social network facebook 4987 spaCy library [13], we first find nouns in each document in the symptom fever 4966 corpus and for every noun we find all hypernyms in the associ- sport tennis 4964 ated knowledge graph. Next, we add the most frequent 𝑛 such fruit strawberry 4824 hypernyms to the document-based taxonomy (the number in activity fishing 4789 the third column in Table 1). We identified this step as critical, feature construction, how the text is being processed prior to as the crawl-based knowledge graphs are commonly noisy, and that and how are semantic features used after that. prunning out uncertain relations is of high relevance. After per- forming this for all documents in the corpus, document-based 3.2 Microsoft Concept Graph taxonomies are concatenated into corpus-based taxonomy. Next, we perform feature selection, discussed next. We are using Microsoft Concept Graph4 [15] [16] for obtaining the extra semantic information. This large relational graph con-3.1 Feature selection sists of more than 5.4 million concepts that are a part of more than 80 million triplets. It was created by harnessing billions of During feature selection we choose a predefined number of web pages, so it is very general and various, offering a lot knowl- features within the set of features with the goal to select the edge to add to our text we want to classify. It contains mostly IsA most useful or important features. Hence, from the set of hy- relations, which was the part we use to obtain hypernyms for pernyms which we constructed from the knowledge graph, we nouns in the input text and enrich the feature vectors by some choose only top 𝑑 features (= dimension of the space) based on of them. A part of the downloaded knowledge graph is shown one of the heuristics described below. Closeness centrality of in Table 1. The number in the third column is the count of times a node is a measure of centrality in a network, calculated as this relation was found when creating the knowledge graph, so 𝐶 (𝑥 ) = 1 , where 𝑑 (𝑦, 𝑥) is the distance (path length) be- Í 𝑑 ( 𝑦,𝑥 ) a frequency of the relation’s occurrence. We removed relations 𝑦 tween vertices 𝑥 and 𝑦. The bigger the closeness centrality value that had frequency of one, which immediately reduced the graph a given node has, the closer it is to all other nodes. The rarest approximately to half the size and removed mostly noisy rela- terms are the most document-specific and are more likely to tions. Later we used the NetworkX library [17] to transform the provide more information than the ones frequently occurring. Microsoft Knowledge Graph from bare text to a directed graph. Hence this heuristic simply takes overall counts of all the hy- This step makes the subsequent exploitation of the knowledge pernyms, sorts them in ascending order by their frequency of graph easier. occurrence and takes the top 𝑑. The mutual information be- tween two random discrete variables represented as vectors 𝑋𝑖 3.3 Proposed approach extending tax2vec (the 𝑖-th hypernym feature) and 𝑌 (the target binary class) is Firstly, we tokenize each document and assign part-of-speech defined as follows: tags to the tokens with the help of the spaCy library [13]. Then for each noun in the text, we find its hypernyms in the knowledge Õ 𝑝 (𝑋 = 𝑥, 𝑌 = 𝑦) 𝑖 𝑀 𝐼 (𝑋 , 𝑌 ) = 𝑝 (𝑋 = 𝑥, 𝑌 = 𝑦) log 𝑖 𝑖 2 graph. The number of hypernyms for each noun is a parameter 𝑝 (𝑋 = 𝑥 )𝑝 (𝑌 = 𝑦) 𝑖 𝑥 ,𝑦 ∈ {0,1 } chosen by the user, we choose those hypernyms based on the highest frequencies of relation between the current noun and where 𝑝 (𝑋 = 𝑥) and 𝑝 (𝑌 = 𝑦) correspond to marginal distribu- 𝑖 the hypernyms. As shown later in the paper, bigger number of tions of the joint probability distribution of 𝑋 and 𝑌 . Tax2vec 𝑖 hypernyms does not help a lot, but increases execution time sig- computes the mutual information (MI) between all hypernym nificantly, so it is more sensible to choose a smaller number. Then features and a given class. So for each target class a vector of we create a document-based taxonomy, which is a directed graph mutual information scores is obtained, corresponding to MI be- where edges are created as hypernym-noun for each hypernym tween individual hypernym features and a given target class. and each noun. We merge the document-based taxonomies into Then the MI scores for each target class are summed up and the one corpus-based taxonomy (maintaining unique nodes, merge- final vector is obtained. The features are sorted by MI scores in Graph method in the pseudocode) and on it we perform one of descending order and the first 𝑑 features are chosen as the final the above mentioned heuristics to choose the best 𝑑 hypernyms. semantic space. The personalized PageRank algorithm takes Those steps are outlined in Algorithm 1. as an input a network and a set of starting nodes in the network and returns a vector assigning a score to each node. The scores 4 EXPERIMENTS AND RESULTS are calculated as the stationary distribution of the positions of a random walker that starts its walk on one of the starting nodes This section presents the setting of the experiments and the data and, in each step, either randomly jumps from a node to one of sets on which the experiments were conducted. We also describe its neighbors (with probability the metrics used to estimate classification performance. 𝑝 ) or jumps back to one of the starting nodes (with probability 1-𝑝). In our experiments prob- ability 4.1 Data sets 𝑝 was set to 0.85. The tax2vec exploits the idea initially introduced in [14], where personalized PageRank scores are com- We conducted the experiments on eight different data sets, which puted w.r.t. the terms, present throughout the document space. are described below. They were chosen intentionally from differ- This way, a graph-based, completely unsupervised ranking is ent domains and the basic information about them can be seen obtained, and is used in similar manner to other feature selection in Table 2. heuristics discussed in the previous paragraphs. In this section we introduce how the knowledge graph is used for semantic 4https://concept.research.microsoft.com/ 206 Knowledge graph aware text classification Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Data: corpus, knowledgeGraph, maxHypernyms some cases. We compare those results to the classification without corpusTaxonomy = [ ]; any semantic features which is plotted as a grey horizontal line. foreach 𝑑𝑜𝑐 ∈ 𝑐𝑜𝑟𝑝𝑢𝑠 do On the other hand, on the datasets CNN News, Medical Relation documentTaxonomy = [ ]; and SMS Spam we didn’t see any improvement with the addition 𝑡 𝑜𝑘𝑒𝑛𝑠 = tokenize(𝑑𝑜𝑐 ); of semantic features. Figure 2 shows the relation between feature foreach 𝑡𝑜𝑘𝑒𝑛 ∈ 𝑡𝑜𝑘𝑒𝑛𝑠 do space size and the execution times. if 𝑡𝑜𝑘𝑒𝑛 is 𝑛𝑜𝑢𝑛 then edges = knowledgeGraph.edgesFrom(𝑡𝑜𝑘𝑒𝑛); foreach 𝑒𝑑𝑔𝑒 ∈ 𝑒𝑑𝑔𝑒𝑠 do if 𝑙𝑒𝑛(𝑑𝑜𝑐𝑢𝑚𝑒𝑛𝑡𝑇 𝑎𝑥𝑜𝑛𝑜𝑚𝑦) >= 𝑚𝑎𝑥 𝐻 𝑦𝑝𝑒𝑟 𝑛𝑦𝑚𝑠 then break; documentTaxonomy.add(𝑒𝑑𝑔𝑒 ∈ 𝑒𝑑𝑔𝑒𝑠) corpusTaxonomy.mergeGraph(documentTaxonomy) featureSelection(corpusTaxonomy) Result: Selected semantic features Algorithm 1: Semantic feature construction. Table 2: Data sets used for evaluation of knowledge graph’s extra features impact on learning. Data set Classes Words Unique w. Documents PAN 2017 Gender 2 5169966 607474 3600 PAN 2017 Age 5 992742 185713 402 SMSSpam 2 86910 15691 5571 CNN-news 7 1685642 159463 2107 MedicalRelation 18 1136326 66235 22176 Articles 20 5524333 178443 19990 SemEval2019 2 295354 39319 13240 Yelp 5 1298353 88539 10000 PAN 2017 (Gender) Given a set of tweets per user, the task is to predict the user’s gender [18]. PAN 2017 (Age) Given a set of tweets per user, the task is to predict the user’s age group [19]. CNN News Given a news article (composed of a number of paragraphs), the task is to assign to it a topic from a list of topic categories. [20]. SMS Spam Given a SMS message, the task is to predict whether it is a spam or not. [21]. Medical Relations Given an article with biomedical topic, the task is to predict the relationship between the medical terms annotated. [22]. SemEval 2019 Given a tweet, the task is to predict whether it contains offensive content [23]. Articles Given an web article, the goal is to assign to it a topic. [24]. Yelp Given an review of a restaurant, the goal is to predict the ranking from one to five stars. Settings. In all the datasets the stop words were removed. Stop words are for example "the", "is", "are" etc. There is no uni- Figure 1: Results of text classification on data sets Yelp, versal list of stop words in NLP research, however we used NLTK pan-2017-age, pan-2017-gender, CNN News, SMSSpam, Se- (Natural Language Toolkit) [25] for filtering stop words. The doc- mEval 2019, Medical Relation and Articles with execution uments were tokenized with the help of spaCy’s NLP tool. The times as the numbers in the plot. data sets were divided into 90% training data and 10% test data by using random splits. Number of hypernyms for each noun was 10. We used linear SVM classifier for classification and 𝐹1 5 CONCLUSION measure for performance. We showed that information from a large, real-life knowledge graph can improve text classification. Our approach aims at short 4.2 Results texts like tweets, shorter articles, messages and similar. We firstly Figure 1 shows that on some datasets (namely Yelp, PAN 2017 Age, process the document with spaCy, find nouns with their corre- PAN 2017 Gender and on SemEval 2019 and Articles) the extra sponding hypernyms, from which we create a taxonomy and semantic features constructed from the knowledge graph help in from that we later choose the most helpful features with one 207 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Petrželková et al. [6] T. K. Landauer. 2006. Latent semantic analysis. [7] T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean. [n. d.] Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems 26. [8] A. Celikyilmaz, D. Hakkani-Tür, P. Pasupat, and R. Sarikaya. 2015. Enriching word embeddings using knowledge graph for semantic tagging in conversational dialog systems. In. [9] M. K. Elhadad, K. M. Badran, and G. I. Salama. 2018. 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Latent dirichlet allocation. 208 EveOut: Reproducible Event Dataset for Studying and Analyzing the Complex Event-Outlet Relationship Swati Tomaž Erjavec Dunja Mladenić swati@ijs.si tomaz.erjavec@ijs.si dunja.mladenic@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan International Jožef Stefan International Jožef Stefan International Postgraduate School Postgraduate School Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT relationship and impact of different features on the selection of events by the outlets. We present a dataset consisting of 77, 545 news events collected between January 2019 and May 2020. We selected the top five 1.1 Contributions news outlets based on Alexa Global Rankings and retrieved all the events reported in English by these outlets using the Event The paper makes the following three contributions to science: Registry API. Our dataset can be used as a resource to analyze • The dataset generation scripts, which provide a structured and learn the relationship between events and their selection reproducible approach to building a publicly available by the outlets. It is primarily intended to be used by researchers dataset of news events with varied features. This will not studying bias in event selection. However, it may also be used to only speed up the development of future versions of Eve- study the geographical, temporal, categorical and several other Out, but will also help to create custom datasets with the aspects of the events. We demonstrate the value of the resource desired outlets and features. in developing novel applications in the digital humanities with • The compilation of EveOut, a novel dataset with a rich motivating use cases. Website with additional details is available range of event features and spanning multiple news cate- at http:// cleopatra.ijs.si/ EveOut/ . gories. • Identification of possible use cases intended to facilitate KEYWORDS the creation of tools to improve digital journalism and to Dataset, News Event Analysis, Event selection bias, News cover- help researchers study the complex relationship between age events and news outlets. 1 INTRODUCTION 2 DATASET News outlets are constantly faced with the task of selecting events Several news outlets may cover a single world event as a story in they will report on, dependent on the perceived interest of the a variety of different ways. A collection of one or more stories, all event to their readership. This can be driven by various factors, of which describe the same world event, is referred to as an ‘event’ such as the geographical origin of the event, involvement of in the entire paper. In the following subsections, we define our well-known persons, etc. Such selection requires monitoring of data generation process and provide statistics on the resulting current affairs to determine their news value for the outlet. dataset. Machine learning tools may help outlets to deal with the large numbers of events, help them explore strategies for selecting 2.1 Data Source publishable events, and build dedicated decision support systems We use Event Registry1[4] as the data source which monitors, for this task. The effectiveness of these systems depends on the collects, and provides news articles from news outlets around the availability of news event collections complemented by relevant world in over 30 languages. It also identifies the major incidents event details such as date, category, country of occurrence, brief reported in the articles and aggregates them into clusters known description, etc. as events. For example, “missiles launched by Iran at US forces in In this paper we introduce EveOut, the first large publicly Iraq” is an event reported across the globe in over 3,200 news available data set of 77, 545 English news events with a variety of articles. features collected between January 2019 and May 2020. It includes To construct an event, Event Registry follows a series of steps. events in eight different categories of news, i.e. business, politics, News aggregation is the first step in which RSS feeds are con- technology, environment, health, science, sports, and arts-and- stantly monitored for new articles. The next major step is the entertainment. We hope that EveOut will encourage publishers semantic event information extraction, which retrieves informa- and others involved in the news production process to develop tion from the articles in a structured way to be used in subsequent tools to enhance digital journalism. The data set would also allow steps. Clustering algorithms are then used to group articles that researchers from digital humanities to study and analyze the describe the same event. In the last step, the article clusters are marked as events and are annotated with rich metadata such as Permission to make digital or hard copies of part or all of this work for personal a unique id to track the event coverage, categories to which it or classroom use is granted without fee provided that copies are not made or may belong, geographical location, sentiment, etc. As a result, its distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this extensive temporal coverage can be used effectively to study the work must be honored. For all other uses, contact the owner /author(s). complex correlation between events and news outlets. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 1 https://eventregistry.org 209 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Swati, Tomaž Erjavec, and Dunja Mladenić 𝑄 . Next, we set the time limit 𝑄 = [𝑄 , 𝑄 ] for ex- 𝑡 𝑖𝑚𝑒 𝑡 𝑖𝑚𝑒 𝑠𝑑 𝑒𝑑 tracting events that occurred within the specified time where, Select Outlets Set Time Constraint 𝑄 = ‘2019-01-01’ and 𝑄 = ‘2020-05-31’ signify the event’s 𝑠𝑑 𝑒𝑑 Ex: Top 5 Global Newspapers Ex: 2019-01-01 to 2020-05-31 start date and end date. Since the outlet’s event selection pol- icy may change over time, we selected this time frame as re- cent data tends to be more reliable in predicting event cover- age patterns. We then set 𝑄 = {𝑄 , 𝑄 , 𝑄 } where, 𝑡 𝑒𝑥 𝑡 𝑜𝑢𝑡 𝑙 𝑎𝑛𝑔 𝑐𝑎𝑡 Generate Event List 𝑄 = {‘𝑛𝑦𝑡𝑖𝑚𝑒𝑠’, ‘𝑖𝑛𝑑𝑖𝑎𝑡𝑖𝑚𝑒𝑠’, ‘𝑤𝑎𝑠ℎ𝑖𝑛𝑔𝑡𝑜𝑛𝑝𝑜𝑠𝑡 ’, ‘𝑢𝑠𝑎𝑡𝑜𝑑- 𝑜𝑢𝑡 Ex: eng-4500343 𝑎𝑦 ’, ‘𝑐ℎ𝑖𝑛𝑎𝑑𝑎𝑖𝑙𝑦 ’}, 𝑄 = {‘𝑒𝑛𝑔’}, and 𝑄 = {‘𝑝𝑜𝑙𝑖𝑡𝑖𝑐𝑠’, ‘𝑏𝑢- 𝑙 𝑎𝑛𝑔 𝑐𝑎𝑡 𝑠𝑖𝑛𝑒𝑠𝑠 ’, ‘𝑠 𝑝𝑜𝑟 𝑡 𝑠 ’, ‘𝑎𝑟 𝑡 𝑠 𝑎𝑛𝑑 𝑒𝑛𝑡 𝑒𝑟 𝑡 𝑎𝑖𝑛𝑚𝑒𝑛𝑡 ’, ‘𝑠𝑐𝑖𝑒𝑛𝑐𝑒 ’, ‘𝑡 𝑒𝑐ℎ- 𝑛𝑜𝑙 𝑜𝑔𝑦 ’, ‘ℎ𝑒𝑎𝑙 𝑡 ℎ’, ‘𝑒𝑛𝑣𝑖𝑟 𝑜𝑛𝑚𝑒𝑛𝑡 ’} represent the outlets, languages Extract Event Info and news categories respectively. Ex: id, date, title, summary, ... From the extracted event list, we first excluded events that were not covered by any of the selected outlets. We then extracted individual outlets from the event’s outlet list and created a column Generate Outlet Label in the dataset to represent each of them. We use a binary scalar Ex: 0- Not Covered, 1- Covered value to indicate whether the outlets covered the event or not. The event coverage by the outlets is not uniform, which can be EveOut - Event Outlet visualized in Figure 2. nytimes Figure 1: EveOut dataset generation process. chinadaily indiatimes Table 1: Description of the dataset attributes. Attribute Description usatoday washingtonpost uri a unique event identifier title title of the event in English event_date date in yyyy-mm-dd format sentiment event sentiment categories Figure 2: Distribution of event coverage by the outlets. event categories loc_country country where the event occurred loc_continent continent where the event 3 AVAILABILITY occurred total_article_count total number of articles published The GitHub repository containing the scripts is available at article_count total number of articles published https:// github.com/ Swati17293/ EveOut. To facilitate discov-in English erability and preservation, the full data set is archived as an on- summary summary of the event line resource at https:// doi.org/ 10.5281/ zenodo.3953878. Eve-outlet_list list of outlets that reported the Out is available in three common formats ( JSON, XML, and CSV) event for direct download and use. The documentation meets the re- quirements of the FAIR Data principles3 with all necessary meta- data defined. Under the Creative Commons Attribution 4.0 Interna- 2.2 Data Generation Process tional license, it is freely available to make it reusable for almost any purpose. A separate web page with detailed statistics and To generate the dataset we adopted an automated approach which illustrations can be found at http:// cleopatra.ijs.si/ EveOut/ is depicted in Figure 1. We use Event Registry API to collect event for in-depth analysis. related information mentioned in Table 1. The script is designed to simplify the release of future versions and to be able to replicate 3.1 Reusability the process of generating custom datasets. The outlined process The resource is currently being used for individual projects is the result of the resource’s core requirement to best address and as a contribution to the project’s deliverables of the Marie the potential use-cases referred to in Section 4. 4 Skłodowska-Curie CLEOPATRA Innovative Training Network . For data generation, we first selected the top five news out- 2 A major part of this project aims to provide a temporal, cross- lets based on Alexa Global Rankings . We then used an ex- lingual analysis of concepts around different events, exploring plicit temporal query (𝑄 ) to retrieve all events in all news cat- 𝑡 how language impacts the mediatic narratives built by the media. egories from the Event Registry API. 𝑄 = {𝑄 , 𝑄 } 𝑡 𝑡 𝑒𝑥 𝑡 𝑡 𝑖𝑚𝑒 It also aims to analyse news reporting bias and multiple media consists of the text component 𝑄 and the time component 𝑡 𝑒𝑥 𝑡 3 http://www.nature.com/articles/sdata201618/ 2 4 https://www.alexa.com/topsites/category/Top/News/Newspapers http://cleopatra- project.eu/ 210 EveOut: Reproducible Event Dataset for Studying and Analyzing the Complex Event-Outlet Relationship Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Figure 3: Overview of the category-wise event coverage by the outlets. narratives which would enable to filter out appropriate informa- that category are high/low than usual, it will be reflected in the tion which then will be used to build information representation outlet’s coverage pattern. tools. Since EveOut serves as the basis for the study and analysis Figure 4 reveals that instead of favoring events with neutral of events and their attributes, it is ideally suited to the project sentiment, outlets tend to favor events with positive sentiment. needs. In addition, event coverage by ‘usatoday’ and ‘washingtonpost’ is quite diverse with respect to sentiments. 4 POTENTIAL USE CASES 4.1 Examine Event-Selection Bias It is important for a journalist to know which event is worthy enough to be published. Even readers would be interested to know the factors that affect this selection. An automated solution can be devised using EveOut to provide an overview of the event and to visualize differences in coverage. 4.2 Outlet Prediction EveOut is designed to predict the likelihood of an event being covered by the outlet. It would enable the publishers of the outlets to assess the significance of the event. In addition, it may also be used by independent editors who prefer to report on events Figure 4: Distribution of event coverage by the outlets with covered by mainstream outlets. respect to sentiments. 5 STATISTICS AND ANALYSIS In this section we provide further information about the data In terms of the sentiments used in each category as plotted in contained in EveOut, focusing explicitly on the distribution of Figure 5, it is worth noting that ‘technology’ and ‘sports’ events events between the outlets. are mostly positive. With regard to the distribution of event categories covered by the outlets, as shown in Figure 3, ‘politics’ is the most common category, while ‘environment’ is the least common category. It is also worth noting that each outlet focuses on the different categories of events aside from ‘politics’. For instance, ‘india- times’ focuses more on events related to ‘arts and entertainment’, whereas ‘chinadaily’ tends to cover more ‘business’ related events. As far as the coverage of the event over time is concerned, it is also inconsistent as depicted in Figure 6. Furthermore, the event-coverage of ‘usatoday’ and ‘washingtonpost’ is slightly inconsistent. It is also interesting to note the sharp decline in coverage by ‘usatoday’ in ‘Aug 2019’ and by ‘washingtonpost’ in ‘May 2020’. The drop in the graph for washingtonpost in ‘May 2020 is due to its event preference. It is evident from washingtonpost’s radial graph in Figure 3 that its coverage is biased towards politics and sports. These two categories alone represent around 50% of events in the dataset. However, this percentage dropped to 40% in ‘May 2020 and, as a result, the coverage of washingtonpost dropped significantly. Increase of event coverage in ‘Mar 2019 is also attributed to the fact that about 56% of events were from Figure 5: Distribution of category over sentiments. these two categories. In nutshell, if the outlet favors a certain category of events and, in a specific time frame, and events of 211 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Swati, Tomaž Erjavec, and Dunja Mladenić Figure 6: Distribution of the event coverage by the outlets over time. 6 RELATED WORK ACKNOWLEDGMENTS There are a number of datasets that focus on news articles [7]. As This work was supported by the Slovenian Research Agency and far as the availability of event-centric datasets is concerned, there the European Union’s Horizon 2020 research and innovation is a scarcity of publicly available datasets. There are few related program under the Marie Skłodowska-Curie grant agreement No research on the event data [3, 1], but the extracted/generated 812997. datasets for the experiments is also not publicly accessible. GDELT [5] is the most popular, very large and publicly avail- REFERENCES able event-oriented news dataset. It contains data in multiple [1] Dylan Bourgeois, Jérémie Rappaz, and Karl Aberer. 2018. languages from a wide range of online publications. It’s collection Selection bias in news coverage: learning it, fighting it. In of world events is centered on location, network and temporal Companion Proceedings of the The Web Conference 2018, 535– attributes. There is no attribute defining the outlet list for the 543. event in the dataset. As a result, there is a lack of knowledge [2] Cindy Cheng, Joan Barceló, Allison Spencer Hartnett, Robert essential to the analysis of the event-outlet relationship that is Kubinec, and Luca Messerschmidt. 2020. Covid-19 govern- the foundation of our dataset. ment response event dataset (coronanet v. 1.0). Nature Hu- In addition, the existing event datasets [6, 2] are category- man Behaviour, 1–13. dependent (politics/healthcare/disaster etc.) which renders them [3] Felix Hamborg, Norman Meuschke, and Bela Gipp. 2018. useful for specific research purposes only. Therefore, by providing Bias-aware news analysis using matrix-based news aggre- a generalized event-centric news dataset, EveOut addresses the gation. International Journal on Digital Libraries, 1–19. stated dataset bottleneck. [4] Gregor Leban, Blaz Fortuna, Janez Brank, and Marko Gro- belnik. 2014. Event registry: learning about world events 7 CONCLUSIONS AND FUTURE WORK from news. In Proceedings of the 23rd International Confer- In this paper, we introduced the EveOut dataset, which covers ence on World Wide Web, 107–110. events reported by the top five global news outlets for over 17 [5] Kalev Leetaru and Philip A Schrodt. 2013. Gdelt: global data months. We have ensured that the dataset complies with the on events, location, and tone, 1979–2012. In ISA annual FAIR principles. In conjunction with the data set, we provide the convention. Volume 2, 1–49. source code for reproducing the dataset with varied features. [6] Clionadh Raleigh, Andrew Linke, Håvard Hegre, and Joakim For instance, it is possible to generate a reduced version of Eve- Karlsen. 2010. Introducing acled: an armed conflict location Out, focused on just one category, say ‘politics’. Specific outlets, and event dataset: special data feature. Journal of peace dates, and languages can also be specified in accordance with research, 47, 651–660. the requirements. We illustrate potential use cases to show how [7] Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, Chuhan Wu, the dataset could be used to study the pattern of event coverage Tao Qi, Jianxun Lian, Danyang Liu, X. Xie, Jianfeng Gao, of an individual outlet and to predict whether or not the outlet Winnie Wu, and M. Zhou. 2020. 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In the future , we intend to extend the dataset to 3597–3606. doi: 10 . 18653 / v1 / 2020 . acl - main . 331. https : include events described in different languages. //www.aclweb.org/anthology/2020.acl- main.331. 212 Ontology alignment using Named-Entity Recognition methods in the domain of food Gorjan Popovski1,2∗ , Tome Eftimov1 , Dunja Mladenić1,2 and Barbara Koroušić Seljak1,2 1Jožef Stefan Institute, 1000 Ljubljana, Slovenia 2Jožef Stefan International Postgraduate School, 1000 Ljubljana, Slovenia {gorjan.popovski, tome.eftimov, dunja.mladenic, barbara.korousic}@ijs.si Abstract Terminology-driven NER methods, also called dictionary- based NER methods [Zhou et al., 2006], match text phrases In recent years, a great amount of research has against concept synonyms that exist in the terminological re- been done in predictive modeling in the domain sources (dictionaries). The main disadvantage of these meth- of healthcare. Such research is facilitated by the ods is that only the entity mentions that exist in the resources existence of various biomedical vocabularies and will be recognized, but the benefit of using them is related to standards which play a crucial role in understand- the frequent updates of the terminological resources with new ing healthcare information. In addition, the Unified concepts and synonyms. Medical Language System (UMLS) links together Rule-based NER methods [Hanisch et al., 2005] use regu- biomedical vocabularies to enable interoperability. lar expressions that combine information from terminological However, in the food domain such resources are resources and characteristics of the entities of interest. The scarce. To address this issue, this paper explores a main disadvantage of these methods is the manual construc- methodology for ontology alignment in the domain tion of the rules, which is a time-consuming task and depends of food by leveraging Named-Entity-Recognition on the domain. (NER) methods based on different semantic re- Corpus-based NER methods [Alnazzawi et al., 2015; Lea- sources. It is based on a recently published rule- man et al., 2015] are based on an annotated corpus provided based NER method named FoodIE, whose seman- by subject-matter experts as well as the use of ML tech- tic annotations are based on the Hansard corpus, niques to predict the entities’ labels. These methods are less as well as a NER tool called Wikifier, from which affected by terminological resources and manually created DBpedia URIs are extracted. To perform the align- rules. However, their limitation is their dependence on an ex- ment we use the FoodBase corpus, which consists istence of an annotated corpus for the domain of interest. The of recipes annotated with food entities and includes construction of the annotated corpus for a new domain is a a ground truth version which is additionally used time consuming task and requires effort by the subject-matter for evaluation. experts to produce it. To exploit unlabelled data in constructing NER methods, 1 Introduction AL can be used [Settles, 2010; Tran et al., 2017]. This rep- resents semi-supervised learning in which an algorithm is Information Extraction (IE) is the task of automatically ex- able to interactively query the user to obtain the desired la- tracting information from unstructured data and, in most bels/outputs at new data points. Which examples are sent cases, is concerned with the processing of human language to the user for labelling is chosen by the algorithm and their text by means of natural language processing (NLP) [Aggar- number is often much lower than the number of examples re- wal and Zhai, 2012]. The main idea behind IE is to provide quired for supervised learning. It usually consists of three a structure to the information extracted from the unstructured components: (1) the annotation interface, (2) the corpus- data. based NER, and (3) component for querying samples. One of the core IE tasks is named-entity recognition (NER), which addresses the problem of identification and classification of predefined concepts [Nadeau and Sekine, 2 Related work 2007]. It aims to determine and identify words or phrases in text into predefined labels (classes) that describe concepts 2.1 Hansard corpus of interest in a given domain. Various NER methods ex- ist: terminology-driven, rule-based, corpus-based, methods The Hansard corpus is a collection of text and concepts cre- based on active learning (AL), and methods based on deep ated as a part of the SAMUELS project [Alexander and An- neural networks (DNNs). derson, 2012; Rayson et al., 2004]. It contains 37 higher level semantic groups, one of which is our topic of interest — Food ∗Contact Author and Drink. 213 2.2 FoodIE Having annotated the recipes with both methods, we can FoodIE is a rule-based food Named-Entity Recognition perform the ontology alignment by using the location infor- method [Popovski et al., 2019a]. As it is rule-based, it con- mation for each annotation in each recipe. Each unique con- sists of a rule-engine in which the rules are based on compu- cept from both methods (semantic resources) is assigned its tational linguistics and semantic information that describe the unique ID, and then a table is constructed for each concept food entities. mapping containing the IDs. 2.3 Wikifier 5 Evaluation and experimental setup Wikifier is a tool that uses an efficient approach for annotating 5.1 Match types documents with relevant concepts from Wikipedia [Brank et • al., 2017]. It is based on a pagerank method to identify a set of True Positives (TP) — these are matches where the relevant concepts. As it provides the location in the document whole food concept is correctly annotated; where the annotation occurs, it is effectively a Named-Entity • False Positives (FP) — these are matches where a non- Recognition method. It provides Wikipedia concepts as anno- food concept is annotated as a food concept; tations, additionally assigning DBpedia concepts if they exist. • False Negatives (FN) — these are matches where a food entity is not properly annotated; 3 Data • Partial match — these are matches where only some to- A recent publication provides one of the first annotated cor- kens from a food concepts are properly annotated. pora, named FoodBase [Popovski et al., 2019b], containing food entities. It consists of two version, a ground truth set 5.2 Evaluation metrics referred to as “curated” (containing 1,000 annotated recipes), Using the concept of True Positives, False Positives and False as well an “un-curated” version, consisting of around 22,000 Negatives, we compute the widely used evaluation metrics: recipes. The recipe categories that are included are: Appe- Precision (P), Recall (R) and F1 Score (F1). They are defined tizers and snacks, Breakfast and Lunch, Dessert, Dinner, and as: Drinks. In this paper, we use the curated version to perform • the ontology alignment as well as evaluate the methodology. P = T P T P +F P This version was manually checked by subject-matter ex- • R = T P perts, so the false positive food entities were removed, while T P +F N the false negative entities were manually added in the corpus. • F 1 = 2 P ·R P +R An example of a recipe can be found on Figure 1. 6 Results and discussion 4 Ontology alignment After running the evaluation, we obtain the following results. Using FoodIE and the Wikifier tool, we obtain annotations The matches for both methods are presented in Table 1, while for all 1,000 recipes from the FoodBase. the evaluation metrics are presented in Table 2. FoodIE extracts and annotates each recipe with semantic tags from the Hansard corpus. Each annotation contains the Table 1: Match types. location of the extracted entity, i.e. where in the raw text the surface form representing the concept occurs, and its corre- FoodIE Wikifier sponding semantic tags from the Hansard corpus. TPs 11461 6380 The Wikifier tool is used to annotate the recipes with DB- FNs 684 4121 pedia URIs. As these are general DBpedia concepts, ad- FPs 258 5861 ditional information to filter out food concepts from non- Partial 359 3297 food concepts is required. Webscraping the pages for the URIs provides useful information that can be used to dis- tinguish food from non-food concepts, such as the broader Table 2: Evaluation metrics. concept/class to which the concept of interest belongs. The post-processing of the DBpedia URIs checks the entity type FoodIE Wikifier of the concept and checks if it is one of: “FOOD”, “FOODS”, F1 Score 0.9605 0.5611 “DISH”, “INGREDIENT”, “FOOD AND DRINK”, “BEV- Precision 0.9780 0.5212 ERAGE”, “PLANT”, “ANIMAL”, or “FUNGUS”. If it does Recall 0.9437 0.6076 not belong to one of the above entity types, the page is checked for mentions of other URIs which are semantically From the results in the tables it is evident that FoodIE pro- related to food: “FOOD”, “PLANT”, “ANIMAL”, or “FUN- vides more promising results. However, this was expected as GUS”. These URI mentions can occur anywhere in the page this NER method was specifically constructed to only cater and if one of these matches is satisfied, the entity is assumed to the domain of food. Of especial interest are the matches of to be a food entity. type partial, since they represent a match where only a subset A post-processed example of such an annotation can be of the tokens in a food entity are correctly recognized. For found on Figure 2. example, looking at Figure 1, the first extracted food entity 214 Figure 1: Example recipe from the “curated” part of FoodBase. Figure 2: Wikifier annotation example on a single recipe 215 should be “dry ranch salad dressing”, which is correctly ex- [Alnazzawi et al., 2015] Noha Alnazzawi, Paul Thompson, tracted by FoodIE. Looking at Figure 2, the same food entity Riza Batista-Navarro, and Sophia Ananiadou. Using text is only extracted as “salad”. Such match types do not factor mining techniques to extract phenotypic information from in the calculation of the evaluation metrics, as it is debatable the phenochf corpus. BMC medical informatics and deci- whether to count them as TPs or FNs. Nevertheless, they sion making, 15(2):1, 2015. are interesting to compare, since even partial matches con- [Brank et al., 2017] Janez Brank, Gregor Leban, and Marko vey at least some semantic meaning regarding the food entity. Grobelnik. Annotating documents with relevant wikipedia Moreover, FP annotations on the same figure are “bowl” and concepts. Proceedings of SiKDD, 2017. “shape” which are not food entities. Additionally, a recent comparison of existing food NER methods can be found in [Hanisch et al., 2005] Daniel Hanisch, Katrin Fundel, [Popovski et al., 2020], where the authors compare the per- Heinz-Theodor Mevissen, Ralf Zimmer, and Juliane formance of FoodIE with NER methods using other food on- Fluck. Prominer: rule-based protein and gene entity tologies available in the BioPortal. recognition. BMC bioinformatics, 6(1):S14, 2005. Regarding the mapping of the concepts, a total of 348 ex- [Leaman et al., 2015] Robert Leaman, Chih-Hsuan Wei, plicit concept mappings were discovered by the methodology. Cherry Zou, and Zhiyong Lu. Mining patents with tm- An example mapping for the concept “garlic” would be: chem, gnormplus and an ensemble of open systems. In • A000016: ‘garlic’, AG.01.h.02.e [Onion/leek/garlic]. Proce. The fifth BioCreative challenge evaluation work- shop, pages 140–146, 2015. • E000029: ‘garlic’, http://dbpedia.org/resource/Garlic [Nadeau and Sekine, 2007] David Nadeau and Satoshi 7 Conclusion and future work Sekine. A survey of named entity recognition and classification. Lingvisticae Investigationes, 30(1):3–26, In this work we propose a methodology for ontology align- 2007. ment by using Named-Entity Recognition methods in the do- main of food. It utilizes the newly proposed FoodIE NER [Popovski et al., 2019a] Gorjan Popovski, Stefan Kochev, method and the Wikifier text annotation tool. Our experimen- Barbara Koroušić Seljak, and Tome Eftimov. Foodie: A tal results show that FoodIE provides more promising results rule-based named-entity recognition method for food in- than Wikifier, achieving an F 1 score of 0.9605, compared formation extraction. In Proceedings of the 8th Inter- to 0.5611. This is expected since FoodIE is specifically de- national Conference on Pattern Recognition Applications signed for the food domain, while Wikifier uses general vo- and Methods, (ICPRAM 2019), pages 915–922, 2019. cabulary and annotates text with Wikipedia concepts. [Popovski et al., 2019b] Gorjan Popovski, Barbara Koroušić For future work, recursive webscraping can be performed Seljak, and Tome Eftimov. FoodBase corpus: a new re- to more accurately distinguish between food and non-food source of annotated food entities. Database, 2019, 11 annotated concepts from the Wikifier tool. Specifically, this 2019. baz121. would mean repeating the steps to check if the entity is a [Popovski et al., 2020] G. Popovski, B. K. Seljak, and T. Ef- food entity or not on the parent nodes in DBpedia. Addition- timov. A survey of named-entity recognition methods ally, more food semantic resources can be included to provide for food information extraction. IEEE Access, 8:31586– mapping between multiple ontologies. Doing this is depen- 31594, 2020. dent on the existence of a NER method that works with con- cepts from the desired food semantic resource. [Rayson et al., 2004] Paul Rayson, Dawn Archer, Scott Piao, and AM McEnery. The ucrel semantic analysis system. Acknowledgements 2004. This research was supported by the Slovenian Research [Settles, 2010] Burr Settles. Active learning literature sur- Agency (research core grant number P2-0098), and the Eu- vey. University of Wisconsin, Madison, 52(55-66):11, ropean Union’s Horizon 2020 research and innovation pro- 2010. gramme (FNS-Cloud, Food Nutrition Security) (grant agree- [Tran et al., 2017] Van Cuong Tran, Ngoc Thanh Nguyen, ment 863059). The information and the views set out in this Hamido Fujita, Dinh Tuyen Hoang, and Dosam Hwang. A publication are those of the authors and do not necessarily re- combination of active learning and self-learning for named flect the official opinion of the European Union. Neither the entity recognition on twitter using conditional random European Union institutions and bodies nor any person acting fields. Knowledge-Based Systems, 132:179–187, 2017. on their behalf may be held responsible for the use that may [Zhou et al., 2006] Xiaohua Zhou, Xiaodan Zhang, and Xi- be made of the information contained herein. aohua Hu. Maxmatcher: Biological concept extraction us- ing approximate dictionary lookup. In Pacific Rim Interna- References tional Conference on Artificial Intelligence, pages 1145– [Aggarwal and Zhai, 2012] Charu C Aggarwal and ChengX- 1149. Springer, 2006. iang Zhai. Mining text data. Springer Science & Business Media, 2012. [Alexander and Anderson, 2012] Marc Alexander and J An- derson. The hansard corpus, 1803-2003. 2012. 216 Extracting structured metadata from multilingual textual descriptions in the domain of silk heritage M.Besher Massri Dunja Mladenić Jožef Stefan Institute, Slovenia Jožef Stefan Institute besher.massri@ijs.si Jožef Stefan International Postgraduate School Ljubljana, Slovenia dunja.mladenic@ijs.si ABSTRACT processing and annotation, we generated 24 binary datasets and 19 multi-class datasets (four for English, two for Spanish, and In this paper, we present a methodology for extracting structured one for French). Using machine learning techniques we trained metadata from museum artifacts in the field of silk heritage. The classifiers on the labeled data examples to predict the labels (slot main challenge was to train on a relatively small and noisy data values) based on the textual descriptions. Despite relatively small corpus with highly imbalanced class distribution by utilizing a and unbalanced data corpora, using sampling techniques and variety of machine learning techniques. We have evaluated the weighted loss function helped mitigate the issue. In an experi- proposed approach on real-world data from five museums, two mental evaluation, we observed that on our data using traditional English, two Spanish, and one French. The experimental results methods might be as good as using deep learning models when show that in our setting using traditional machine learning al- the data is scarce. However, using deep learning allows for build- gorithms such as Support Vector Machines gives comparable ing multilingual models that scale across different languages. and in some cases better results than multilingual deep learning The main contribution of this paper is in proposing an ap- algorithms. The study presents an effective approach for catego- proach to adding metadata to historical artifacts based on ap- rization of text described artifacts in a niche domain with scarce plying machine learning on multilingual textual descriptions of data resources. the artifacts. Moreover, we have defined the learning problem in KEYWORDS collaboration with domain experts and performed evaluations on real-world data in English, Spanish, and French. The rest of this Information extraction, Text classification, Silk heritage, Trans- paper is structured as follows. Section 2 provides a description of formers, Support Vector Machines. the data, Section 3 describes the proposed methodology, Section 4 gives the results of the evaluation and Section 5 concludes the 1 INTRODUCTION paper summarizing the approach and the findings. When looking to improve the understanding of silk heritage we find that the data available in the museums often lack seman- tic information on the artifacts or have them to some extent 2 DESCRIPTION OF DATA included in textual descriptions. To facilitate automatic analysis We used the SilkNow knowledge graph [8] as our source of data. of silk heritage data and support digital modeling of the weaving The source consists of records of different museums in different techniques, we propose multilingual metadata extraction from languages as shown in Table 1. The largest are MET with8364 textual descriptions provided by the museums. artifacts in English, VAM with 7231 artifacts in English, and Ima- We propose the usage of machine learning techniques to model tex with 6799 artifacts in Spanish. We have used a subset of the the target variables, referred here as slots to align with the ter- data that contain artifacts with provided metadata and textual minology of information extraction. Using machine learning descriptions in related fields that were pointed out as relevant by methods we build a model for each of the target variables in the domain experts. Each record consists of the basic information order to annotate the text. This enabled us to add metadata to about the object, such as the title and the museum it belongs to, the silk heritage artifacts of the museums. The domain experts along with two other sets of attributes, textual attributes, and collaborating on Silknow project [9] have identified four kinds categorical attributes. Textual attributes hold a textual descrip- of metadata information that would be useful and are contained tion of the object in several fields, such as physical description in texts of at least some of the targeted museums. We treat these and a technical description. The categorical description holds as four slots for information extraction, where the list of possible metadata information, such as technique or materials used. How- slot values for each of the four was defined by the domain experts. ever, the data quality varies across the museums and records. Based on that we formed a multi-class dataset for each slot. Some museums are rich in both textual and categorical attributes, The corpora of text included were in three different languages like the VAM museum, and others have short/low-quality textual (English, Spanish, and French) from five different museums, with attributes like Imatex. Also, some records have a text description a total of 500 museum records used in the study. After the data in their categorical attributes instead of a single category value. The metadata fields that we have considered are weaving Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or technique, weave, motifs, and style. The list of labels or slot distributed for profit or commercial advantage and that copies bear this notice and values for each of the metadata field (i.e. slot for information the full citation on the first page. Copyrights for components of this work owned extraction) were compiled by the domain experts. These values by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior describe the silk artifacts’ nature and structure. Each of those specific permission and /or a fee. Request permissions from permissions@acm.org. slot values is represented by a term and a list of alternatives, up Information society ’20, October 5–9, 2020, Ljubljana, Slovenia to four alternatives per term. Examples of slot values are satin, © 2020 Association for Computing Machinery. twill, and tabby, representing possible values of the weave slot. 217 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Museum Language Count The features were generated from sequences of words, referred CER Spanish 1296 to as n-grams, of length 1, 2, and 3. The remaining parameters Garin Spanish 3101 were left unchanged from their default values. We used nltk [1] Imatex Spanish 6799 library for tokenization, SpaCy [4] for lemmatization, and Snow Joconde French 376 Ball Stemmer [6] for stemming. MAD French 763 Due to the methodology of data labeling, we sometimes ended MET English 8364 up with a highly imbalanced datasets having a lot more negatives MFA English 3297 than positives. Therefore, in the binary dataset, we took a random MTMAD French 663 subset from the negative examples to match the positive count. In RISD English 3338 addition, some examples were generated from the same records, by having more than one textual record with mentions of the VAM English 7231 Table 1: Museums from the Silknow knowledge graph same class’s term/alternatives, therefore, corrections have been showing the language of the artifacts and the number of applied to the dataset by putting all examples of the same record artifacts included in the knowledge graph. in either train or test but not in both. This process was done to ensure no leakage occurs by potentially having highly similar textual text in train and text. 3.3 Multi-class Classification Tasks 3 METHODOLOGY For multi-class classification, we used a deep learning approach. The architecture consists of a pre-trained transformer, an LSTM 3.1 Annotating datasets with slot values layer, a dropout layer, a dense (linear) layer, and finally a soft-max Based on the data and target variables, two types of datasets activation layer. For the transformer we used BERT [3], multi- were formed for two types of text classification tasks. The first lingual BERT, and XLM-ROBERTA [2]. The loss function used type is binary classification dataset, in which the target class was a cross-entropy loss with Adam as the optimizer. We used is one of the slot values. The other is multi-class classification PyTorch framework [7] and hugging-face transformers library dataset, in which a dataset is formed for each of the four slots in [10]. each museum, where the target classes are the slot values that fall Considering that some of the datasets have a large class imbal- under the selected slot in addition to extra "other" class indicating ance, which can be a couple of thousand examples of the majority that the example doesn’t fall under any of them. class and only a few examples of the minority classes, we exper- For forming the binary classification dataset we used a simple imented with several class-weighting schemas. First, we tried string matching approach. For each target class in each museum, assigning weights to the classes in the loss function is inversely examples were formed out of textual attributes of the museum proportional to the number of examples of each class. In addi- records that contain a mention of either one of the possible value tion, when we used weighted sampling with return for loading terms or its alternatives. Categorical attributes of the same record the examples into batches. This had the effect of over-sampling were used to determine the label of the example. The task is to the minority classes and under-sampling the majority classes to classify whether the example has the slot value against the other achieve as balanced batch representation as possible. Finally, we slot values of the same slot. Each item is classified as True if tried a derivable version of F1 Macro as a loss function where the the categorical attributes contain only the target value or one prediction matrix is taken as a probability rather than a binary of its alternatives but not any of the other slot values’ terms value. or their alternatives. If there is no mention of the slot value term or alternatives, then it’s classified as false. If it contains 4 RESULTS this slot value’ term along with other slot values’ terms then it’s 4.1 Experimental Datasets considered as indeterminate and the example is removed. To form the multi-class datasets, we merged the datasets of The dataset collection methodology was applied to 10 museums the same museum with target classes representing slot values and 4 categories holding more than 150 class values overall. How- that fall under the same slot. The true items of each slot value ever, most of the datasets have no positive items. In this research, dataset formed the set of the examples with that slot value as the we have selected datasets with at least 10 positive examples for labels. The items that are false in each slot value dataset formed binary classification tasks and at least 10 non-other in multi- the "Other" class in the multi-class dataset. class tasks. This final list consists of 24 binary datasets and 19 multi-class datasets. These datasets are used for training machine 3.2 Binary Classification Tasks learning classifiers. For binary classification, we used TFIDF word-vector represen- 4.2 Binary Classification Tasks tation for generating the feature vectors and trained a Linear For binary Classification, we applied the described methodology Support Vector Machines (SVM) as the classifier using scikit- on all the datasets with at least 10 positive examples. The results learn library [5]. All dataset were split into train and test using of binary classification are consolidated in Table 2. 80-20 stratified split. We performed a grid search with 5-fold The graph in figure 1 displaying the correlation between the cross validation on the training part using the following options: number of examples and the F1 score reveals a weak correlation • stemming, lemmatisation, or none of 0.19. We can see that when having more than 600 examples, we • max document frequency: [0.95.1.0] achieve F1 over 0.8. Upon closer inspection on the museum level, • min document frequency: [0,0.05] we found that the best results are achieved in the MFA museum on • SVM tolerance: [1e-4,1e-5] motifs and weaving technique and Joconde museums on weave. 218 Extracting structured metadata from multilingual textual descriptions in the domain of silk heritage Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Museum Slot value Slot Language #Exs Accuracy Precision Recall F1 cer bordado weaving technique Spanish 278 0.89 0.87 0.93 0.9 cer motivo vegetal motifs Spanish 146 0.57 0.56 0.6 0.58 cer tafetán weave Spanish 581 0.77 0.9 0.6 0.72 cer terciopelo weaving technique Spanish 118 0.67 0.67 0.67 0.67 garin brocatel weaving technique Spanish 932 0.88 0.85 0.92 0.89 garin damasco weaving technique Spanish 1748 0.9 0.92 0.87 0.89 garin espolÃn weaving technique Spanish 972 0.88 0.89 0.88 0.88 joconde Satin weave French 159 0.91 0.9 0.95 0.93 joconde Taffetas weave French 110 0.95 0.92 1 0.96 mfa Lace motifs English 190 0.92 0.9 0.95 0.92 mfa plain weaving technique English 130 1.00 1.00 1.00 1.00 vam brocade weaving technique English 634 0.87 0.87 0.87 0.87 vam damask weaving technique English 480 0.84 0.85 0.83 0.84 vam Ear motifs English 262 0.83 0.84 0.81 0.82 vam Edge motifs English 178 0.81 0.87 0.72 0.79 vam embroidery weaving technique English 1614 0.85 0.86 0.83 0.84 Table 2: Results for the binary classification task. Overall the best results are achieved by MFA and Joconde with because of the large fluctuation in F1 macro value across training an average F1 of .96 and .95 respectively followed by Garin, VAM, epochs caused by having minority classes with few examples. and CER with the average F1 of .89, .81, and .72 respectively. Model configuration Accuracy F1 Base model 84.6 43.1 Weighted loss 82.1 47.2 Weighted sampling 82.6 52.2 F1 loss function 77.5 59.1 weighted sampling and f1 loss 52 22.8 Weighted loss and weighted sampling 84.8 54.7 + Learning rate 1e-4 − → 5𝑒 − 6 86.1 57.9 Multi-Lingual BERT 85.3 55.2 XLM-ROBERTA 87.5 53.6 Table 3: Comparison between different model configura- tion on the Weave Slot detection in VAM Dataset Figure 1: F1 score vs #Examples showing good perfor- mance on the largest datasets, when the number of exam- ples is at least 600. Comparing the learning curves of BERT and multi-lingual BERT in figure 2 reveals that despite the comparable results, the multi-lingual BERT took double the number of epochs to 4.3 Multi Class Classification Class stabilize and finish training compared to its BERT counterpart. 4.3.1 Use Case: Detecting Weave Slot from VAM museum. We This can be due to the fact that Multi-lingual BERT is trained in selected the VAM Weave slot as a use case dataset to perform many languages and it needs more fine-tuning to adapt to any hyperparameter tuning and select the best configurations for certain language, whereas the BERT transformer was trained in weighting. The dataset contains 2760 items with a baseline of English-only documents. 52.9% distributed across 4 classes: Satin, Tabby, Twill, and Other. The dataset was split into train, test, and validation in the form 4.3.2 Generalizing towards all datasets. After we experimented of 60-20-20 split. The results in Table 3 show that using class with different parameter settings, we decided to use the follow- weighting in both loss function and sampling provides the best ing parameters on all the datasets: Weighted Loss function and −6 results w.r.t both classification accuracy and F1. Using F1 as a loss Weighted Sampling for batches; learning rate of 5 ∗ 10 ; batch function sometimes provided good results but was discarded as size of 16 for BERT and 12 for multi-lingual BERT and XLM- it was not stable across different datasets. In addition, decreasing ROBERTA, due to memory limits; 1024 Units for LSTM Layer; the learning rate improved results and stabilized the training dropout layer of 0.5. curve. Finally, using the XLM-ROBERTA transformer showed an Moreover, the datasets were tested against three types of trans- improvement in accuracy. The number of epochs was determined former: Language-Specific BERT, Multilingual BERT, and XLM- based on the accuracy performance of the validation dataset. The ROBERTA, as well as the SVM classifier. The accuracy results in training would stop when the accuracy did not improve for the Table 4 show that on most of the datasets SVM performs better last 15 epochs. The accuracy (F1 micro) was chosen over F1 macro or comparable to the deep learning models. 219 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Museum Lang Slot Baseline # Cls # Exs SVM BERT Multi BERT XLM-ROBERTA VAM English Weave 52.9 4 2760 82.8 86 85.3 87.5 VAM English Weaving Technique 35.9 14 3525 77.6 80.1 78 78 VAM English Motifs 84.8 9 5500 91 90.6 87.4 87 CER Spanish Weave 59.3 5 945 75.1 75.1 64 72 CER Spanish Weaving Technique 61.1 11 720 74.3 74.1 71.5 66 Joconde French Weave 55.6 4 180 66.7 30.6 86.1 91.7 Joconde French Weaving Technique 60 5 150 97.2 70 76.7 63.3 Table 4: Results for the multi-class classification task. ACKNOWLEDGMENTS This work was supported by the Slovenian Research Agency and SilkNow European Unions Horizon 2020 project under grant agreement No 769504. REFERENCES [1] Steven Bird, Ewan Klein, and Edward Loper. 2009. Natural Language Processing with Python. O’Reilly Media. 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We believe that the over-fitting html. could be mitigated further by using regularization on the LSTM [7] [n. d.] Pytorch: an imperative style, high-performance layer, as well as using weight-decaying in the optimizer. deep learning library. In. The experimental results show that with low data quality and [8] 2020. Silknow knowledge graph data. https://github.com/ having not enough data, traditional methods such as SVM in silknow/converter/tree/master/output. (2020). some cases outperform deep neural network models. We expect [9] 2020. SilkNow project. https://silknow.eu/. (2020). that the results could be improved by having an assembly of [10] T. Wolf, L. Debut, V. Sanh, J. Chaumond, C. Delangue, A. those models instead of using one of them only, which is a part Moi, P. Cistac, T. Rault, R. Louf, M. Funtowicz, J. Davison, of the future work. Furthermore, one can fine-tune each model S. Shleifer, P. von Platen, C. Ma, Y. Jernite, J. Plu, C. Xu, independently to achieve better performance. T. Le Scao, S. Gugger, M. Drame, Q. Lhoest, and A. M. In future work, we plan to test cross-museum learning by Rush. [n. d.] Huggingface’s transformers: state-of-the-art training on one museum and predicting other museums both in natural language processing. the same language and in different languages using multi-lingual transformers. This has practical value for labeling the data in the museums that do not contain metadata information but do have suitable textual descriptions of the artifacts. 220 Hierarchical classification of educational resources Gregor Žunič Erik Novak Jožef Stefan Institute Jožef Stefan Institute Ljubljana, Slovenia Jožef Stefan International Postgraduate School gregor.zunic@ijs.si Ljubljana, Slovenia erik.novak@ijs.si ABSTRACT 2 RELATED WORK This paper describes an approach to automate the process of la- There are two approaches to hierarchically classify the data: (1) the belling hierarchically structured data. We propose a top-down level- Big-bang, and (2) the Top-down level-based approach [4, 8, 9]. based approach with SVMs to classify the data with scientific do- The big-bang approach works by training (complex) global main labels. The model was trained on labeled open education classifiers which consider the entire class hierarchy as a whole. lectures and returns high accuracy predictions for lectures in the Each global classifier is binary and decides if the material fits the English language. We found that our model performs better with entire hierarchy (entire hierarchy is for example “Computer Sci- the traditional text extraction method TF-IDF than with pre-trained ence/Machine Learning/Support Vector Machine”). The advantage language model XLM-RoBERTa. of this approach is that it avoids class-prediction inconsistencies across multiple levels. The major drawback of this approach is the KEYWORDS high complexity due to the enforcing the model to correctly predict hierarchical classification, support vector machine, multi-class clas- the whole hierarchy branch, which can be difficult to achieve. sification, machine learning, open educational resources The top-down level-based approach works by training local classifiers at each level to distinguish between its child nodes. An ACM Reference Format: example will first, at the root level, be classified into a second- Gregor Žunič and Erik Novak. 2020. Hierarchical classification of educa- level category. It will then be further classified at the lower level tional resources. In Proceedings of Slovenian KDD Conference (SiKDD’20). category until it reaches one or more final categories where it can ACM, New York, NY, USA, Article 4, 4 pages. https://doi.org/10.475/123_4 not be classified any further. The main advantage of this model is its simplicity. The disadvantage is the difficulty to detect an error 1 INTRODUCTION in the parent category which could lead to false classification. Manually labeling data can be tedious work; one must have suf- The most common implementation of a local classifier [3] is the ficient background knowledge about the data and have clear in- support vector machine [7, 11]. In the later papers they propose to structions in the labeling process. This becomes even more difficult train separate SVMs for every level of a branch in the hierarchy. when the data needs to be annotated with hierarchically structured labels. 3 DATA SET In this paper we present a top-down level-based approach us- ing support vector machines (SVMs) for labeling open education The data set used in the experiment consists of 28,769 OER lec- resources (OERs). The labels are in a hierarchical structure and tures available at Videolectures.NET [10], an award winning video represent different scientific domains. We compare different lecture OER repository. For each lecture we collected the following meta- representations using TF-IDF and XLM-RoBERTa and find that the data: title, description, labels, language, authors, date published and TF-IDF representations yield better results. Even though the paper the length of the lecture. The description is present in 58% of the focuses on OERs the method can be generalized to any textual data lectures. The data set contains 24532 lectures in English, 3930 in set. Slovene and 307 lectures in other 16 languages. The remainder of the paper is structured as follows. Section 2 Preprocessing. For our methodology we used only the lecture’s describes the related work done on the topic of hierarchical classifi- title, description, language and categories. Each lecture is labeled cation. Next, we present the data used in the evaluation in Section 3. with one or more scientific (sub-)domains most relevant for the The methodology is described in Section 4. The evaluation setting lecture (e.g. “Computer Science”, "Computer Science/Crowd Sourc- and its results are described in Section 5 followed by a discussion ing"). Figure 1 shows the distribution of lectures per number of in Section 6. We present the future work in Section 7 and conclude labels. the paper in Section 8. Almost half of the lectures have more than one label. Lectures with no labels are placed under the “No Labels” category. These lectures are mostly introductory speakers’ presentations in confer- Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed ences. We focus on predicting a single label with high accuracy. We for profit or commercial advantage and that copies bear this notice and the full citation prescribed to only have one label per lecture. We achieve this by on the first page. Copyrights for third-party components of this work must be honored. duplicating a lecture For all other uses, contact the owner/author(s). 𝑛 times, where 𝑛 is the number of labels of SiKDD’20, October 2020, Ljubljana, Slovenia the lecture and assign a distinct label to each duplicate. Although © 2020 Copyright held by the owner/author(s). the duplicates may reduce the performance of the models we do ACM ISBN 123-4567-24-567/08/06. not reduce the already small number of lectures used during the https://doi.org/10.475/123_4 221 SiKDD’20, October 2020, Ljubljana, Slovenia Gregor Žunič and Erik Novak XLM-RoBERTa. The model is based on the RoBERTa model released in 2019. It is a large language model trained on 2.5 TB of CommonCrawl data [2]. The model achieves state-of-the-art performance on cross-lingual classification, sequence labeling and question answering. The most useful feature of the model is that it does not require the sentence language as an input. In theory, it extracts the same vectors for similar words in 100 languages. The length of the vector that the model outputs is 768. To ex- tract the features a CUDA-enabled GPU is required and the model training is very slow. 4.2 Multi-class SVM Classifier Figure 1: Distribution of lectures per number of correspond- We chose the top-down level-based approach for our classifier. The ing labels. Most of the lectures have only one label. raw text input is firstly vectorized following one of the two feature extraction approaches described in Section 4.1. The vector is then training process. Figure 2 shows the top scientific domain labels in input to the main SVM which determines the first category. Then the data set. the input is handled by the second SVM, trained specifically for sub- labels of first classified category. If a sub-label tops the threshold of 0, this step is repeated, otherwise the model outputs the lowest level parent category. For example “Computer Science” is the first determined cate- gory. Then the input is handled by the SVM trained on sub-labels of “Computer Science”, which determines that the input does not match with any of the sub-labels. The model puts the lecture in the “Computer Science” category. This is visually explained in figure 3. Input ... “Machine Feature “Computer 0 . 1 - 0 . 2 Learning” SVM Figure 2: Top scientific domain labels in the data set. The extraction Science” most frequent label is Computer_Science. SVM “Semantic - 0 . 7 “Business” - 0 . 7 SVM . . . Web” The most frequent label is “Computer Science”. In addition, a “Social - 1 . 0 SVM . . . Sciences” large number of lectures are not labeled; this is because a lot of ... lectures are presentations that do not correspond to any of the scientific domains. The data set is unbalanced on both domain and Figure 3: Visual representation of hierarchical SVM classi- sub-domain levels. fier. The example shows a lecture classified as belonging to the “Computer Science” category 4 METHODOLOGIES In this section we describe the methods used to perform the feature Each SVM is an implementation of a multi-class classifier using extraction of the text, the implementation of multi class classifier the one-vs-rest approach. Predicted class should always be domi- model and the lectures’ weights. nant otherwise the recommendation is not relevant. The input to the classifier is a raw string created by concatenating the title and the description if the description is available. It is then 4.3 Lecture Weights converted to a vector. In this paper we experimented with two Each lecture is assigned a weight of 1 , 𝑥 = 4, where 𝑛 is the 𝑥 𝑛 approaches: TF-IDF and XLM-RoBERTa. number of total labels in the original lecture and 𝑥 is a parameter. If 𝑥 < 4 the accuracy is greatly reduced, if 𝑥 > 4 the accuracy is 4.1 Feature Extraction increased by a small margin. It converges when 𝑥 → ∞. When TF-IDF. Each lecture is represented with a vector of its TF-IDF increasing the parameter 𝑥 the weight comes closer to 0 which values [6]. TF measures how frequently a term occurs in a lecture’s means that the model accounts for data less during training. This text. The IDF is a measure of how much information the word means that the 4th power is a sufficient balance between excluding provides. If it is common across all lectures its value is close to 0. some data and reducing the accuracy. The terms with the highest TF-IDF scores are usually the ones that The other approach could be to ignore multi-label lectures during characterize the topic of the lecture best. testing phase ( 1∞ ). 𝑛 The size of the lecture’s vector representation is exactly the same Because some labels are so scarce, we limit ourselves to labels as the total number of unique words. Since most of the features are with at least 20 lectures. This reduces the total number of labels in zero the lecture vectors are sparse. the data set from 502 to 244. 222 Hierarchical classification of educational resources SiKDD’20, October 2020, Ljubljana, Slovenia 5 EVALUATION the model would opt for SVMs trained on features extracted using 5.1 Parameters and Specifications TF-IDF, because of the better performance. All other languages would be handled by SVMs trained by XLM-RoBERTa, because the SVM. The SVM implementation used in the evaluation is the Lin- classifier performs much better than random. earSVC [1] with the default parameters. The TD-IDF method could also be used to classify lectures that XLM-RoBERTa. The model used for representation generation are in the non-english languages by firstly translating the text to is the hugging face’s pretrained model [5] which was trained on English before using them during training. With this approach the default parameters found in the paper [2]. The training was exe- model could work in all languages and retain the simplicity of TF- cuted on the Google Colab (online hosted Jupyter notebook) free IDF. Note that that this approach would be strongly dependant on tier machine (12GB RAM, dual core CPU, NVIDIA K80). the quality of the translations. Weighting the errors during the training process. We did 5.2 Results not use the hierarchy structure for calculating the error between Table 1 shows the performance of the different models with linear the predicted and the actual labels hence all the errors types during kernel. We have also evaluated other kernels (polynomial, RBF, training were the same. This is not ideal because the error should sigmoid), but the performance was worse than using linear kernel. be more significant when the classifier incorrectly predicts the That is why we omitted them from the performance table. main branch versus when it incorrectly predicts a lower level label. TF-IDF with linear kernel SVM. Using the TF-IDF method for For example, if we take a lecture that is labeled as “Computer feature extraction we found that the SVMs performed the best with Science/Machine Learning” then the error should be bigger if our linear kernel. One explanation for such results is that the dimension classifier predicts the “Biology” label rather than the “Computer of the features is large (more than 60k), which means that other Science/Semantic Web” label. more advance kernels might lead to over-fitting. XLM-RoBERTa with linear kernel SVM. The model’s perfor- 7 FUTURE WORK mance was worse than using TF-IDF. The accuracy of the main We intend to improve the performance of the XLM-RoBERTa and classifier was 19% compared to 70% when using TF-IDF. The other to experiment with other language models and try to achieve better SVM kernels (polynomial, RBF, sigmoid) performed worse com- performance. pared to linear kernel. Table 1 shows the performance of the model. One additional direction for future work might be training a SVM. The problem with current SVM implementation is that it multiclass classifier to predict more than one label to a given lecture. can only put the lecture in one category. One way to solve the issue We tried implementing the multi label output classifier using the of only one label would be to firstly predict one label. Then, if the MultiOutputClassifier wrapper on SVM but the precision of the user (editor) wants another prediction, the model can output the model was noticeably lower. prediction with second highest certainty. The model is ready to be used in production in Videolectures.NET TF-IDF vs XLM-RoBERTa. The advantage of choosing XLM- as a recommender engine to help the editors. The service could RoBERTa over of TF-IDF is that it works with 100 languages. The either be wrapped in a Flask microservice or directly into Videolec- vector outputs are similar [2] for all languages. This was proven tures.NET’s backend. by translating the same text input into multiple languages (using Google Translate) and the predicted category did not change. When 8 CONCLUSION using TF-IDF you have to split the original data set into subsets In this paper we explore a top-down level-based approach for clas- containing a single language and train the model from scratch. That sifying OER lectures with scientific domain labels. We used over- would be possible with enough data. For some languages (German, sampling to handle label unbalance and experimented with two French) the the data set contains less than 30 lectures, which means text representation approaches, TF-IDF and XLM-RoBERTa. We that you can not train an SVM sufficiently. found that the model using the TF-IDF representations gives better results. 6 DISCUSSION ACKNOWLEDGMENTS Unbalanced Data Set. We found the SVM trained on an over- sampled data set to be working better than the SVM trained on the This work was supported by the Slovenian Research Agency and raw data set. Due to the unbalanced data if the data set is not re- X5GON European Unions Horizon 2020 project under grant agree- sampled the bias towards the strongest category (Computer Science) ment No 761758. is strongly presented. For example neutral words such as “ ”, “the” etc. are classified as belonging in REFERENCES Computer Science category. Comparing Word Embedding Techniques. The TF-IDF ap- [1] Lars Buitinck, Gilles Louppe, Mathieu Blondel, Fabian Pedregosa, Andreas Mueller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Alexandre Gramfort, proach performs much better than XLM-RoBERTa which is surpris- Jaques Grobler, Robert Layton, Jake VanderPlas, Arnaud Joly, Brian Holt, and Gaël ing. Pre-trained models usually perform better than legacy feature Varoquaux. 2013. 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SSVM: a simple SVM algorithm. 3 (2002), 2393–2398 vol.3. 224 Are You Following the Right News-Outlet? A Machine Learning based approach to outlet prediction Swati Dunja Mladenić swati@ijs.si dunja.mladenic@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan International Postgraduate School Jožef Stefan International Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT outlet is forced to select a set of reporting events. Several factors, such as the geographical origin of the event, the involvement of In this work, we propose a benchmark task of outlet prediction an elite person or country, etc. influences such selection. Also and present a dataset of English news events tailored to the the procedure requires rigorous monitoring of current affairs to proposed task. Addressing this problem would not only allow determine the news value, and may result in event selection bias readers to choose and respond to relevant and broader facets also known as gatekeeping bias. of events but also enable the outlets to examine and report on their work. We also propose a neural network based approach However, no well-established automated method reveals to to recommend a list of probable outlets covering an event of users the outlets that will cover the event of their interest. This interest. Evaluation results reveal that even in its simplest form, drives the motivation of this study. The aim is to predict a list of our model is capable of predicting the outlet significantly better outlets reporting on a given event. Addressing this problem would than the existing rule based approaches. The proposed model not only allow readers to choose and respond to relevant and will also serve as a baseline for evaluating approaches intended broader facets of events but also enable the outlets to examine and to address the task. Implementation scripts can be found at https: // github.com/ Swati17293/ outlet-prediction report on their work. For instance, some outlets tend to publish . events covered by well-established outlets. Instead of waiting for KEYWORDS the news to be published, the proposed system will help them to get an insight into the degree of predictability of event selection News bias, Event Selection bias, News coverage, News Event by the major outlets. Analysis, Recommendation System 1 INTRODUCTION 1.1 contributions We make the following contributions in this context: The advancement in the field of Natural Language Processing [9, 10, 5, 4] over the last decade, has made solutions to complex • We propose a benchmark task of outlet prediction and machine learning problems more convenient. The problems such present a dataset of English news events tailored to the as machine translation, text summarization, and segmentation proposed task. are being solved much more efficiently than ever before. Conse- • We provide a neural network model that can serve as a quently, it offered the researchers the opportunity to use these baseline for evaluating approaches intended to address advanced techniques to solve problems in a variety of contexts the task. such as news bias analysis. This analysis task is poised as the The GitHub repository containing our code is available at identification of the inherent bias present in the news production https:// github.com/ Swati17293/ outlet-prediction. and its coverage process. It occurs when a news outlet publishes a news story selectively or incorrectly. 1.2 Problem Statement The problem is addressed as an outlet prediction task in which the If the news is biased, then it can bias the thought process bias is examined by comparing the learning ability of a classifier and decision making of the person listening, watching, and/or trained to predict the probability of event coverage by an outlet. reading it [12]. It can have several direct or indirect implications whether political or social. For example, if the news shows only 2 LITERATURE REVIEW the positive or negative side of a political party; it has been ob- During the different stages of news production, various forms of served to influence the public vote [2]. Not only politics but also news bias arise as described by Baker et al. [1]. The first stage the news about the disaster or spread of viral disease affects the begins with the selection of events also called gatekeeping, where belief system of the general public. an outlet selects or rejects an event for reporting. The selection process is driven by a number of factors, such as the geographical There are numerous events that happen continuously, and origin of the event, the involvement of an elite person or country, any form of bias can arise in numerous possible ways. It is not etc., and requires rigorous monitoring of current affairs to de- possible for any single outlet to capture every event. Thus, an termine the news value. To our knowledge, only a few methods Permission to make digital or hard copies of part or all of this work for personal have been suggested that explicitly attempt to examine this bias. or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this Saez-Trumper et al. [11] attempted to identify bias in online work must be honored. For all other uses, contact the owner /author(s). news sources and social media groups surrounding them. They Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia studied the disparity in the selection of events based on the quan- © 2020 Copyright held by the owner/author(s). tity and exclusivity of stories published by 80 mainstream news 225 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Swati and Dunja Mladenić outlets across the globe over a span of two weeks. From the re- 3.2 Dataset view, it is found that there is a weak correlation between the For our experiments, we first selected the top three news outlets quantity and exclusivity of news articles published by the outlets. 3 based on Alexa Global Rankings . We then used the Event Reg- It is also discovered that both the news and social media follow istry API to collect all news events reported in English between the same pattern of selection of events in similar geographical January 2019 and May 2020. We excluded events that were not areas. However, media in the same region often choose the same covered by any of the selected outlets. We ended up with 51, 409 events and publish similar-length posts. events for which we extracted basic information such as event id, title, summary, and source. Since the event coverage by these out- Bourgeois et al. [3] used a matrix factorization method to ex- lets is not uniform, which can be visualized in Figure 1, we used tract latent factors that determine the selection of the event by a stratified split to mimic this imbalance across the generated an outlet. They combined the method with a BPR optimization train-valid-test sets. scheme developed by Rendle et al.[8]. They used the events de- rived from the GDELT dataset and arranged the outlets in rows and their reported events in columns to form a matrix. Each cell value of the resulting matrix describes the selection/rejection of the event by the outlet. nytimes washingtonpost For the bias analysis, they chose affiliation, ownership, and geographic proximity of the different outlets as the major factors. They suggest that each outlet follows its own latent preferences structure which facilitates the outlet to rank events. They also indiatimes suggested that events should be selected such that the selected list should be diverse and should include a wide range of actively reported events. They thus adopted the method of Maximum Marginal Relevance which facilitates ranking based on the rel- Figure 1: Distribution of event coverage by the outlets. evance and diversity of the events. It is discovered that event selection favors the most discussed topics rather than the unique ones. 4 MATERIALS AND METHODS F. Hamborg et al. [6] uses a matrix similar to the one created 4.1 Problem Modeling by Bourgeois et al.[3] Each cell in the matrix represent the most For an event 𝐸 and its associated pair (𝑇 , 𝑆 ), the task is to generate representative topic of the article reported by one country about a list of outlets 𝑂 expected to cover 𝐸 . Here 𝑇 is the event title the other. By spanning the matrix through outlets and topics in and 𝑆 is a short summary of the event as provided by the Event a region, the bias can be examined. They used a collection of 1.6 Registry. Mathematically, the task can be formulated as, million articles from more than 100 countries over a two-month 1 span from the Europe Media Monitor (EMM) as their dataset. 𝑂 = 𝑓 (𝑇 , 𝑆, 𝛼 ) (1) Authors in [6] aggregates the related articles and then out- where, 𝑓 is the outlet prediction function and 𝛼 denotes the source the task of bias identification to the users, forcing them model parameters. 𝑂 can have a well-thought-out variable length 𝑙 to determine the bias on their own. While the rest of the existing response generated from the list unique outlets 𝑂 . For this work, 𝑙 work analyzes the selection bias, it certainly does not present an |𝑂 | = 3. automated approach suited to the outlet prediction task, unlike our work. 4.2 Methodology We extract feature vectors from 𝑇 and 𝑆 . We fuse them together to 3 DATA DESCRIPTION create a fused vector which is then passed through several layers to finally generate 𝑂 . Figure 2 illustrates the entire prediction 3.1 Raw Data Source process. We further outline these tasks with more details in the Event Registry2 [7] monitors, collects, and provides news arti-following subsections. cles from news outlets around the world. It also aggregates them 4.2.1 Feature Extraction and Fusion. We used Google’s Univer- into clusters that are referred to as events. Each event is then sal Sentence Encoder 4(USE) to extract 128-dimensional feature annotated with several metadata such as unique id to track the ′ ′ ′ ′ vectors 𝑇 and 𝑆 . For feature fusion, we concatenated 𝑇 and 𝑆 event coverage, categories to which it may belong, geographical and applied 𝑡 𝑎𝑛ℎ activation to generate 𝐹 . We then used batch- location, sentiment, etc. As a result, its large-scale temporal cov- normalization to increase the stability of the network and for erage can be used effectively to study the event selection process regularization. of news outlets. ′ ′ 𝐹 = 𝐵𝑁 (𝑡 𝑎𝑛ℎ (𝑇 ⊕ 𝑆 )) (2) In Eq 2, 𝐵 𝑁 and ⊕ represents batch-normalization and concate- nation respectively. 1 3 https://ec.europa.eu/knowledge4policy/ https://www.alexa.com/topsites/category/Top/News/Newspapers 2 4 https://eventregistry.org https://tfhub.dev/google/universal- sentence- encoder/ 226 A Machine Learning based approach to outlet prediction Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia USE T Event Title T′ tanh F softmax Batch Norm FC Outlet (Ô) Event S S′ Summary USE Figure 2: Outlet prediction process. 4.2.2 Outlet Prediction. Table 1: Multiple correct predictions. We solve the problem using a multi-label classification model for which we create a separate outlet-index dictionary for outlets 𝐷 = {𝑜 : 1 : 2 : 1 , 𝑜 2 . . . 𝑜 𝑛 }, where 𝑛 𝑛 indiatimes nytimes washingtonpost 𝑙 is the total number of unique outlets in 𝑂 . To predict the list indiatimes washingtonpost nytimes of outlets we pass 𝐹 to the fully-connected layer (FC) having 𝑠𝑜 𝑓 𝑡𝑚𝑎𝑥 activation with 𝑛 output neurons. Since an event can be covered by more than one outlet, we formulate the recursive • Subset Accuracy (𝑎): It measures the percentage of in- prediction procedure as, stances in which all of the outlets are correctly classified. ˆ 𝑜 = P (𝑜 |𝐹 , ˆ 𝑜 + 𝑏 ) (3) 𝑁 𝑖 𝑖 −1, 𝑏 ) = 𝑠𝑜 𝑓 𝑡𝑚𝑎𝑥 (𝐹 𝑤𝑖 𝑖 1 Õ Subset Accuracy (𝑎) = ( ˆ 𝑜 − 𝑜 ) (6) 𝐹 𝑤 +𝑏 𝑖 𝑖 𝑒 𝑖 𝑖 𝑁 = (4) 𝑖 =1 Í𝑛 𝐹 𝑤 +𝑏 𝑒 𝑗 𝑗 𝑗 =1 • Hamming Loss (ℓ): It measures the fraction of the incor- 𝑡 ℎ rectly predicted outlet to the total number of outlets. Since where, ˆ 𝑜 is the probability of selecting the 𝑖 outlet (𝑜 ) given 𝐹 , 𝑖 it is a loss function, its ideal value is 0. bias (𝑏 ), and the set of probabilities of previously predicted outlets ( ˆ 𝑜 ), and 𝑤 is the weight. We use categorical cross entropy as 𝑁 𝑖 −1 1 Õ ∩ ˆ 𝑜 𝑜 𝑖 𝑖 the loss function as follows: Hamming Loss (ℓ ) = (7) 𝑁 ˆ 𝑜 ∪ 𝑜 𝑖 𝑖 𝑛 𝑥 𝑖 =1 Õ Õ L (𝑜, ˆ 𝑜 ) = − (𝑜 ∗ log( ˆ 𝑜 )) (5) 𝑖 𝑗 𝑖 𝑗 5.3 Results and Analysis 𝑗 =1 𝑖 =1 Table 2 shows the comparison of our model with the baseline 𝑡 ℎ In Eq (5), for 𝑖 outlet in the output sequence of length 𝑥 , 𝑜𝑖 𝑗 models in terms of subset accuracy and hamming loss. and ˆ 𝑜 denotes the actual and predicted probability of selecting 𝑖 𝑗 𝑡 ℎ the 𝑗 outlet from 𝐷 . Table 2: Comparison between the baseline models and our 4.2.3 Hyper-parameters. 5 We used Categorical accuracy as the proposed model. metrics to calculate the mean accuracy rate for multilabel classi- fication problems across all the predictions. We consider a batch Subset Accuracy Hamming Loss of size 128 and number of epocs as 100 for training. To optimize Uniform 0.140 0.526 the weights during training we use Adam optimizer. Stratified 0.286 0.422 5 EXPERIMENTAL EVALUATION Ours 0.546 0.275 5.1 Baselines Quantitative analysis of the experimental results shows that, We use the following well-known and simplified methods as our our model outperforms the Uniform and Stratified models by a baseline models. margin of 0.41 and 0.26 points for subset accuracy and by 0.25 • Uniform: Generate predictions randomly using a uniform and 0.15 points for hamming loss respectively. The performance distribution. difference is clearly visible in Figure 3. • Stratified: Generates predictions by respecting the class distribution of the training set. The intersection that we find among the different outlet pairs differs considerably as evident in Figure 1. This can be best seen 5.2 Evaluation Metric by assessing the conditional probability of an event covered by an We aim to predict the list of outlets in this work. However, it is outlet given that it is covered by another outlet as listed in Table 3. not necessary to predict the sequence in which outlets appear on For example, we can note that the 𝑃 (𝑤 𝑎𝑠ℎ𝑖𝑛𝑔𝑡𝑜𝑛 |𝑛𝑦𝑡𝑖𝑚𝑒𝑠 ) = this list. This is explained with an example given in Table 1. In 0.492 which is quite high and indicates that 𝑤 𝑎𝑠ℎ𝑖𝑛𝑔𝑡 𝑜𝑛𝑝𝑜𝑠𝑡 tends other cases, a combination of correct and incorrect outlets may to cover most of the events covered by 𝑛𝑦𝑡 𝑖𝑚𝑒𝑠 . It is also inter- be predicted by the model. esting to note that 𝑖𝑛𝑑𝑖𝑎𝑡 𝑖𝑚𝑒𝑠 do not follow 𝑤 𝑎𝑠ℎ𝑖𝑛𝑔𝑡 𝑜𝑛𝑝𝑜𝑠𝑡 or 𝑛𝑦𝑡 𝑖𝑚𝑒𝑠 , and vice versa. We used the following metrics to evaluate the effectiveness of our model where, ˆ 𝑜 is the predicted outlet, 𝑜 is the true outlet, 6 CONCLUSIONS AND FUTURE WORK and 𝑁 is the total number of instances. It is important for a journalist to know which event is worthy 5 https://github.com/keras-team/keras/blob/master/keras/metrics.py enough to be published. Even readers would be interested to know 227 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Swati and Dunja Mladenić Table 3: Conditional probability of an event to be covered by an outlet, provided it is covered by another outlet. P(x|y) nytimes indiatimes washingtonpost nytimes 1.000 0.067 0.364 indiatimes 0.034 1.000 0.023 washingtonpost 0.492 0.063 1.000 [3] Dylan Bourgeois, Jérémie Rappaz, and Karl Aberer. 2018. Selection bias in news coverage: learning it, fighting it. In Companion Proceedings of the The Web Conference 2018, 535–543. [4] Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon. 2019. Unified language model pre-training for natural language understanding and generation. In Advances in Neural Information Processing Systems, 13042–13054. [5] Zihao Fu. 2019. An introduction of deep learning based word representation applied to natural language process- ing. In 2019 International Conference on Machine Learning, Figure 3: Comparison between the baseline models and Big Data and Business Intelligence (MLBDBI). IEEE, 92–104. our proposed model. [6] Felix Hamborg, Norman Meuschke, and Bela Gipp. 2018. Bias-aware news analysis using matrix-based news aggre- gation, 1–19. the outlets that are going to cover the event of their interest. Yet [7] Gregor Leban, Blaz Fortuna, Janez Brank, and Marko Gro- it is certainly not an automated approach, therefore in this work, belnik. 2014. Event registry: learning about world events we propose an approach to address the outlet prediction task from news. In Proceedings of the 23rd International Confer- given the event title and description. We also find that even in its ence on World Wide Web, 107–110. simplest form, our model is capable of predicting the outlet. In [8] Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, the future, we intend to enhance our proposed model to better and Lars Schmidt-Thieme. 2009. Bpr: bayesian personal- predict the outlets and to work in a cross-lingual setting. We ized ranking from implicit feedback. In Proceedings of the plan to include a few more metadata provided by Event Registry Twenty-Fifth Conference on Uncertainty in Artificial Intelli- (refer Section 3.1) along with Wikipedia concepts. We also plan gence (UAI ’09). AUAI Press, Montreal, Quebec, Canada, to analyze the speed of reporting, time-span, and importance 452–461. isbn: 9780974903958. given to the events by the outlets. In addition, we will also be [9] Sebastian Ruder. 2019. Neural transfer learning for natural looking into how the outlets change their coverage style over language processing. PhD thesis. NUI Galway. time. [10] Sebastian Ruder, Matthew E Peters, Swabha Swayamdipta, ACKNOWLEDGMENTS and Thomas Wolf. 2019. Transfer learning in natural lan- guage processing. In Proceedings of the 2019 Conference of This work was supported by the Slovenian Research Agency and the North American Chapter of the Association for Compu- the European Union’s Horizon 2020 research and innovation tational Linguistics: Tutorials, 15–18. program under the Marie Skłodowska-Curie grant agreement No [11] Diego Saez-Trumper, Carlos Castillo, and Mounia Lalmas. 812997. 2013. Social media news communities: gatekeeping, cov- REFERENCES erage, and statement bias. In Proceedings of the 22nd ACM international conference on Information & Knowledge Man- [1] Brent H Baker, Tim Graham, and Steve Kaminsky. 1994. agement, 1679–1684. How to identify, expose & correct liberal media bias. [12] Rune J Sørensen. 2019. The impact of state television on [2] Matthew Barnidge, Albert C Gunther, Jinha Kim, Yang- voter turnout. British Journal of Political Science, 257–278. sun Hong, Mallory Perryman, Swee Kiat Tay, and Sandra Knisely. 2020. Politically motivated selective exposure and perceived media bias, 82–103. 228 MultiCOMET – Multilingual Commonsense Description Adrian Mladenic Grobelnik Dunja Mladenic Marko Grobelnik Artificial Intelligence Laboratory Artificial Intelligence Laboratory Artificial Intelligence Laboratory Jozef Stefan Institute Jozef Stefan Institute Jozef Stefan Institute Ljubljana Slovenia Ljubljana Slovenia Ljubljana Slovenia adrian.m.grobelnik@ijs.si dunja.mladenic@ijs.si marko.grobelnik@ijs.si ABSTRACT The main contributions of this paper are (1) a new multilingual approach to annotating natural language sentences with This paper presents an approach to generating multilingual commonsense descriptors, (2) implementation of the proposed commonsense descriptions of sentences provided in natural language. We have expanded on an existing approach to automatic approach that is made publicly available as an online service knowledge base construction in English to work on different MultiCOMET http://multicomet.ijs.si/ (illustrated in Figure 4), (3) languages. The proposed approach has been utilized to develop evaluation of the proposed approach on the Slovenian language. An MultiCOMET, a publicly available online service for generating additional contribution is the publicly available source code [3] multilingual commonsense descriptions. Our experimental results allowing users to train their own models for other natural show that the proposed approach is suitable for generating languages. commonsense description for natural languages with Latin script. Comparing performance on Slovenian sentences to the English The rest of this paper is organized as follows: Section 2 provides a original, we have achieved precision as high as 0.7 for certain types data description. Section 3 describes the problem and the algorithm of descriptors. used. Section 4 exhibits our experimental results. The paper concludes with discussion and directions for the future work in CCS CONCEPTS Section 5. •CCS Information systems Information retrieval Document 2 Data Description representation Content analysis and feature selection KEYWORDS One might say the only way for AI to learn to perform deep learning, commonsense reasoning, multilingual natural commonsense reasoning, is to learn from humans. Following the approach proposed by COMET [1], we used data from the language processing ATOMIC [2] dataset. The ATOMIC dataset consists of over 24,000 sentences containing common phrases manually labelled by 1 Introduction workers on Amazon Turk. For each sentence the workers were As artificial intelligence systems are becoming better at performing asked to assign open-text values to nine descriptors which capture highly specialized tasks, sometimes outperforming humans, they nine if-then relation types to distinguish causes vs. effects, agents are unable to understand a simple children’s fairy tale due to their vs. themes, voluntary vs. involuntary events and actions vs. mental inability to make commonsense inferences from simple events. states [2] as described in ATOMIC. With recent breakthroughs in the area of deep learning and overall The following are the nine descriptors and their explanations: increases in computing power, it has enabled us to model xIntent – Because PersonX wanted… commonsense inferences with deep learning models. In our research, we expand on the approach to automatic generation of xNeed – Before, PersonX needed… commonsense descriptors proposed in COMET [1] by applying their deep learning models to languages other than English. xAttr – PersonX is seen as… The approach presented in COMET tackles automatic xReact – As a result, PersonX feels… commonsense completion with the development of generative xWant – As a result, PersonX wants… models of commonsense knowledge, and commonsense transformers that learn to generate diverse commonsense xEffect – PersonX then… descriptions in natural language [1]. oReact – As a result, others feel… Our research hypothesis is that the approach proposed by COMET oWant – As a result, others want… [1] can be expanded to Latin script languages other than English. To test this claim, we have trained our own deep learning model on oEffect – Others then… the original training data, and another model on the data translated into another natural language. 229 The dataset contains almost 300,000 unique descriptor values for we were strict in our comparisons, for instance “to stay away from the listed nine descriptors. An example of a labeled sentence is people” and “to get away from others” do not count in overlap. shown in Figure 3. Experimental results show there is considerable difference in In order to test the proposed approach, we implemented it for the performance between the nine descriptors. The best performing Slovene language. We have translated the sentences from the descriptor was xReact, where precision@5 was 0.716, followed by ATOMIC dataset to Slovene, keeping the descriptor values in oReact and oWant with precisions@5 of 0.706 and 0.468 English. The translation was done using Google Cloud’s respectively. The worst performing descriptor was xWant, with a Translation API [4]. precision@5 of 0.21 (see Table 1). 3 Problem Description and Algorithm Descriptor Precision The problem we are solving is predicting the most likely values for xIntent 0.324 each tag in the ATOMIC [1] dataset, given an input sentence in a xNeed 0.352 Latin script language. Following the proposal in COMET, we are addressing the following problem: xAttr 0.438 xReact 0.716 Given a training knowledge base of natural tuples in the {𝑠, 𝑟, 𝑑} format, where 𝑠 is the sentence, 𝑟 is the relation type and 𝑑 xWant 0.210 represents the relation values. The task is to generate 𝑑 given 𝑠 and xEffect 0.456 𝑟 as inputs. oReact 0.706 Figure 1 depicts our approach to solving this problem. The system oWant 0.468 takes labelled sentences as input, translates them to the targeted oEffect 0.310 Latin language and trains a deep learning model capable of Average 0.442 labelling previously unseen sentences with values for nine Table 1: Experimental results on the nine descriptors, showing descriptors capturing the nine predefined relation types as precision of the top 5 predictions. described in Section 2. The best performing descriptor was xReact (representing the relation: As a result, PersonX feels). This was likely due to the fact that most predicted values were only one word long for both models, making it considerably easier for their predictions to overlap. The worst performing descriptor was xWant (representing the relation: As a result, PersonX wants), this could be attributed to the fact that the most predicted values were at least 3-4 words in length, greatly decreasing the likelihood of overlap. Another reason for such low precision could be our strict overlap comparisons. Figure 1: Architecture of the proposed approach Original Translated/Predicted 4 Experimental Results Sentence PersonX looks PersonY PersonX izgleda PersonY Prior to training the model, we split the ATOMIC dataset into train, ___ in the face ___ v obraz test and development sets identical to those used in COMET [1]. In xReact nervous satisfied our evaluation we used 100 sentences from the test set. Values Our deep learning models are trained on the ATOMIC [2] dataset. happy happy We have trained one model on the original dataset in English, and another model on an automatically translated dataset to Slovene. satisfied attractive Both models were trained under the same parameter settings: batch powerful proud size=6, iterations=50000, maximum number of input features = 50. confident angry To evaluate the performance of the proposed approach, we compared the predictions of the model trained on Slovene Table 2: One of the worst performing test sentences for xReact sentences with the predictions of the English model. As the performance metrics, we took the top 5 predicted values for each Table 2 shows the predicted values of one of the worst performing sentences for the xReact descriptor. Note the sentence “PersonX descriptor and checked their overlap. By taking the English looks PersonY ___ in the face” can refer to “Bob looks Mary predictions as the ground truth, we are measuring the precision of slowly in the face” or “Adrian looks Anna kindly in the face” our model by the number of identical descriptor values. Note that or something 230 else. The columns in Table 2 and Table 3 labelled “Original” show the original English sentence and its predicted descriptor values. The columns labelled “Translated/Predicted” show the sentence translated into Slovene and its predicted descriptor values. Table 3 shows the predicted values of one of the worst performing sentences for the xWant descriptor. We can see that there are no common predictions between the two models. Note the sentence “PersonX avoids every ___” can refer to “Marko avoids every car on the road” or “Dunja avoids every boring event” or something else. Original Translated/Predicted Sentence PersonX avoids every ___ PersonX se izogiba vsakemu ___ xWant to stay away from people to get away from others Values to avoid trouble to make sure they are ok to stay away to get away from the situation to not get caught to be alone to not be noticed to make a decision Table 3: One of the worst performing test sentences for xWant While Tables 2 and 3 show the model’s outputs for a single descriptor, Figure 3 shows the full output of the model, given an example sentence “Mojca je pojedla odličen sendvič” (Mary ate an excellent sandwich). Figure 2 shows a close-up of the output of Figure 3. The images in Figures 2 and 3 were taken directly from the interface of our online service MultiCOMET [5]. Figure 3: Full tree of predicted descriptor values generated for an example Slovene sentence For the sentence “Mojca je pojedla odličen sendvič” (Mary ate an excellent sandwich) depicted in Figures 2 and 3, here is a potential English interpretation of the Slovenian output of the model: Mary was hungry (xAttr) and wanted to eat food (xIntent). To do that, she needed to go to the restaurant (xNeed). At the restaurant, other people were also eating food (oEffect). As a consequence of eating the sandwich, Mary’s clothes got dirty (xEffect). Mary feels impressed (xReact) and wants to eat something else (xWant). The restaurant is grateful (oReact) for Mary’s visit and wants to thank Mary (oWant). The MultiCOMET online service is a publicly available implementation of our proposed approach, shown in Figure 4. At the time of writing, MultiCOMET only supports English and Slovene. Figure 2: Close-up of predicted descriptor values generated for an example Slovene sentence 231 Figure 4: Illustrative example of MultiCOMET after submitting a query “Mary ate a wonderful sandwich.” 5 After testing the proposed multilingual approach on the Slovene Discussion language, we intend to expand our coverage to other Latin script In our research we expanded on an existing monolingual languages including Croatian, Italian and French. approach and proposed a new approach to generating multilingual commonsense descriptions from natural language. ACKNOWLEDGMENTS In order to implement our approach, we built on an existing The research described in this paper was supported by the library, implementing the approach proposed by COMET [1]. Slovenian research agency under the project J2-1736 Causalify Our experimental results show that we are getting meaningful and co-financed by the Republic of Slovenia and the European values for the descriptors. Experimental comparison of the Union under the European Regional Development Fund. The predicted descriptor values of the Slovene and English models operation is carried out under the Operational Programme for the show an average precision of 0.44, given our strict comparison Implementation of the EU Cohesion Policy 2014–2020. methodology. We noted the precision values ranged from 0.716 to 0.210 across different descriptors. REFERENCES Based on our literature review (September 2020), none of the [1] Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli articles citing the original COMET [1] paper expanded their Celikyilmaz, Yejin Choi. (2019). COMET: Commonsense Transformers for Automatic Knowledge Graph Construction. Allen Institute for Artificial approach to include other languages. The most similar work we Intelligence, Seattle, WA, USA. Paul G. Allen School of Computer Science found in the literature combining commonsense and & Engineering, Seattle, WA, USA. Microsoft Research, Redmond, WA, USA. [2] Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas multilinguality was [6] where the authors were extending the Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, Yejin Choi. (2019). SemEval Task 4 solution using machine translation. ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning. Paul G. Allen School of Computer Science & Engineering, University of The possible direction for future work includes improving the Washington, Seattle, USA. Allen Institute for Artificial Intelligence, Seattle, USA. quality of the translated sentences from ATOMIC by manual [3] MultiCOMET GitHub https://github.com/AMGrobelnik/MultiCOMET translation to improve the precision of the models. Another Accessed 31.08.2020 possible direction would be to evaluate the performance of our [4] Google Cloud’s Translation API Basic https://cloud.google.com/translate Accessed 31.08.2020 models on a larger number of sentences to increase the reliability [5] MultiCOMET http://multicomet.ijs.si/ Accessed 31.08.2020 of the results. [6] Josef Jon, Martin Fajcik, Martin Docekal, Pavel Smrz. (2020). BUT-FIT at SemEval-2020 Task 4: Multilingual commonsense. arXiv. https://arxiv.org/pdf/2008.07259.pdf 232 A Slovenian Retweet Network 2018-2020 Bojan Evkoski Igor Mozetič & Jožef Stefan International Nikola Ljubešić & Postgraduate School, Petra Kralj Novak Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Bojan.Evkoski@ijs.si ABSTRACT the tweets in terms of hashtags and URLs. We draw con- As the popularity of social media has been growing steadily clusions in Section 6. since the beginning of their era, the use of data from these platforms to analyze social phenomena is becoming more 2. DATA and more reliable. In this paper, we use tweets posted over a We acquired 5,147,970 tweets in the period from January period of two years (2018-2020) to analyze the socio-political 2018 to January 2020 with the TweetCat tool [6], built environment in Slovenia. We use network analysis by ap- specifically for collecting Twitter data written in “smaller” plying community detection and influence identification on languages. The tool identifies users tweeting in the focus lan- the retweet network, as well as content analysis of tweets guage by searching for most common words in that language by using hashtags and URLs. Our study shows that Slove- through the Twitter Search API, and collects these users’ nian Twitter users are mainly grouped in three major socio- tweets through the whole data collection period. On aver- political communities: Left, Center and Right. Although age, the dataset containis around 8,000 tweets per day, with the Left community is the most numerous, the most influ- the three highest volume peaks on March 13, 2018 (11,556 ential users belong to the Right and Center communities. tweets, the resignation of Slovenia’s PM, Miro Cerar), June 1, Finally, we show that different communities prefer different 2018 (13,506 tweets, the last day of the 2018 Slovenian par- online media to inform themselves, and that they also pri- liamentary elections campaign), and May 9, 2019 (12,381 oritize topics differently. tweets, Eurovision semi-final in which Slovenia had a suc- cessful run). The variation of the daily volume of tweets Keywords is affected by many phenomena, but the more evident are: Complex networks, Twitter, community detection, influencers a weekly seasonality with high volumes on working days and low volumes on weekends, extraordinary periods for 1. INTRODUCTION the country (e.g. the 2018 Slovenian parliamentary elections Since the rise of the social networks, their data has been ex- campaign, boosting average daily tweets by around 2,000), tensively used in social analysis. As the popularity of these and holidays (e.g. 2018 and 2019 Easters as local minima platforms continues to grow daily, using them as a proxy to with 5,174 and 4,887 tweets, respectively). analyze specific phenomena is becoming more and more re- liable. Their popularity, accessibility and availability made 3. COMMUNITY DETECTION them the go-to way to share one’s opinion, support another We used the collected tweets to construct a retweet network and even get in conflict with an opposing one. Recently, with for the purpose of community detection. A retweet network the targeted advertising advancements, social media became is a directed weighted graph, where nodes represent Twit- the most important cultural and political battlefront. ter users and edges represent the retweet relations. An edge from node (user) A to node B exists if B retweeted A at In this paper, the country of interest is Slovenia and the least once, indicating the information spread from A to B, proxy is Twitter data. By following the methodology devel- or A influenced B. Note that retweeting a retweet is actually oped in [3, 2, 4, 8], we address the following questions: retweeting the original tweet (source), thus ignoring all in- termediate retweets. The weight of an edge is the number of • Are there groups of densely connected Twitter users times user B retweeted user A. We removed all self-retweets, in the Slovenian retweet network 2018-2020? since they did not provide us additional information for com- • Who are the leading influencers in these groups? munity and influence detection. Consequently, we formed a • What is the content of the tweets in these groups and network with 10,876 users (94% of all users) and 1,576,792 how much does it overlap? retweets (92% of all retweets). This paper is organised as follows. In Section 2, the data This network can be simplified if the direction of the edges acquisition process and the collected Twitter data are pre- is ignored, meaning that two users are linked if one retweets sented. Section 3 discusses the communities in the retweet the other while the source and destination are irrelevant. It network and their properties. Section 4 covers the notion of turns out that such undirected retweet graphs between Twit- influencers and identifies the main influencers in the Slove- ter users are useful to detect communities of like-minded nian retweet network. Section 5 investigates the content of users who typically share common views on specific topics. 233 Figure 1: The Slovenian retweet network (2018-2020) colored according to the detected communities, with shares of the total number of users. The label size of a node corresponds to the number of unique users that retweeted it. Only nodes with at least 700 unique retweeters are included. In complex networks, a community is defined as a subset of the communities. Most of the properties are normalized by nodes that are more closely connected to each other than the user to ease the comparison between communities. to other nodes. For the purpose of this paper, we apply a standard algorithm for community detection, the Louvain • Nodes – unique users count method [1]. The method partitions the nodes into commu- • Central user – user with most retweets nities by maximizing modularity (which measures the differ- • Central user retweets – times the central user is retweeted ence between the actual fraction of edges within the commu- nity and such fraction expected in a randomized graph with • Central user retweeters – unique users retweeting the the same degree sequence) [7]. Modularity values range from central user −0.5 to 1.0, where a value of 0.0 indicates that the edges are • HHI (n = 50) – Herfindahl–Hirschman index [9] mea- randomly distributed, and larger values indicate a higher sures the distribution of influence of the top n influen- community density. tial users. Higher value reflects the community influ- ence concentrated only in few influential users, while We ran the Louvain method (resolution = 1.05) on our undi- lower value indicates more dispersed and balanced in- rected retweet network resulting in 183 communities with a fluence distribution. modularity value of 0.382, which indicates a strong connect- • Edges in/node – edges remaining in the community per edness within communities. Only the three largest commu- user (source and destination in the same community) nities each have more than 5% of all users, while combined • Edges out/node – edges going out of the community they contain 85% of all users. The three main detected com- per user (destination in a different community) munities are presented in Fig. 1. We observe the following: • Weighted edges in/node – weighted edges remaining in • The three largest communities are labeled as Left, Cen- the community per user ter and Right with 55%, 20% and 10% as their re- • Weighted edges out/node – weighted edges going out spective shares of all users. The labeling of the com- of the community per user munities does not necessarily represent their political • Out/In ratio – “Edges out” divided by “Edges in” orientation. • Weighted out/in ratio – “Weighted edges out” divided • The Left community, even though the largest, con- by “Weighted edges in” tains the smallest number of users with more than 700 unique retweeters. 4. INFLUENCERS • The Left community is well separated from the Center We use two simple, but powerful metrics to detect influ- and the Right communities, which are more tightly encers in the retweet network: the weighted out-degree and interlinked. the Hirsch index (h-index) [5]. Both metrics are calculated from the number of retweets, thus known as retweet influ- We performed an exploratory data analysis and calculated ence metrics, indicating the ability of a user to post content the community properties presented in Table 1, to compare of interest to others. 234 Figure 2: Weighted out-degree (total retweets) and h-index comparison. Both charts include the top 25 most influential Slovenian Twitter users according to their respective metric. Bar colors represent the community of a user. Triangles point to users exclusive to one of the charts. Table 1: Community properties For domain URLs, we filtered the 2,297,008 tweets which Left Center Right contain a URL. Then, we extracted the domain part of the Nodes 7,030 1,223 2,519 URLs and removed the domains with no specific meaning Central user vecer BojanPozar JJansaSDS Central user retweets 10,398 31,432 50,688 for Slovenia’s content analysis (e.g. social networks: twit- Central user retweeters 973 1,325 1,242 ter.com, facebook.com, instagram.com, etc., and URL short- HHI (n = 50) 0.031 0.066 0.042 eners: ift.tt, bit.ly, ow.ly, etc.). This results in 512,308 Edges in/node 19.32 14.53 69.30 tweets (approximately 22% of all the tweets with links). The Edges out/node 4.47 37.11 13.19 most frequently occurring domains are owned by Slovenian Weighted edges in/node 52.91 83.68 308.33 media with nova24tv.si, rtvslo.si and delo.si as the top three Weighted edges out/node 6.95 119.42 36.14 Out/In ratio 0.23 2.55 0.19 URL domains with 23,879, 20,210 and 17,360 occurrences Weighted Out/In ratio 0.13 1.43 0.12 respectively. If instead of the total number of occurrences we count only the unique number of users which posted a do- Weighted out-degree is simply the total number of retweets main URL, the top three domains are rtvslo.si, siol.net and of a particular user, while the h-index is an author-level bib- delo.si with 2,802, 2,193 and 2,186 unique users respectively. liometric indicator that measures the scientific output of a scholar by quantifying both the number of publications (i.e., For the hashtag analysis, we filtered only tweets which con- productivity) and the number of citations per publication tain a hashtag, ending up with 701,266 tweets. The top three (i.e., citation impact). Adapted to a Twitter network, it hashtags are the following: #volitve2018 (the 2018 Slove- would be described as: a user with an index of h has posted nian parliamentary elections), #plts (the Slovenian First h tweets and each of them was retweeted at least h times. Football League) and #sdszate (Slovenian Democratic Party hashtag, meaning: SDS for you) with 9,845, 9,318 and 7,308 Let RT be the function indicating the number of retweets occurrences respectively. If we count only the unique num- for each original tweet. The values of RT are ordered in ber of users using a particular hashtag, the results for the decreasing order, from the largest to the lowest, while i in- top three Slovenian hashtags are as follows: #volitve2018 dicates the ranking position in the ordered list. The h-index with 2,473, #slovenija with 1,611 and #fakenews with 1,343 is then defined as follows: users. h-index(RT) = max min(RT(i), i) To see these results in the context of communities, we look at i the tweets authored by members of the three largest commu- The top 25 most influential users by weighted out-degree and nities, resulting in 84% of the tweets with relevant domain h-index are shown in Fig. 2. The two metrics provide fairly URLs and 83% of the tweets with relevant hashtags. We similar results (they differ only in 9 users). Both results summed the domain URL counts, while grouping them by confirm the already visible phenomena from the previous the community in which their user belongs. We applied the observations: The Right community has the most influential same procedure to the hashtags. Finally, we filtered the top users, while the Left community, even though the biggest, eight domain URLs and hashtags for each community and does not have nearly as popular users as the ones from the put them on a single Sankey diagram in Fig. 3. Even though other two communities. overlaps exist, the most popular hashtags and media very much differ from community to community, meaning that 5. CONTENT ANALYSIS all three main communities prioritize topics differently and We refer to content analysis in terms of getting knowledge they inform themselves via different media. from the text of the tweets. In this paper, we perform two kinds of content analysis: domain URLs and hashtags. 235 Figure 3: A Sankey diagram depicts the use of the eight most common hashtags (left-hand side) and URLs (right-hand side) by the three largest detected communities. 6. CONCLUSIONS Parliament: Roll-call votes and Twitter activities. PLoS In this paper we explored the Slovenian twitter network from ONE, 11(11):e0166586, 2016. January 2018 until January 2020. We applied community [3] D. Cherepnalkoski and I. Mozetič. Retweet networks of detection, identifying three main communities: Left, Center the European Parliament: Evaluation of the community and Right. We identified the most influential and the central structure. Applied Network Science, 1(1):2, 2016. users of each community by calculating the weighted out- [4] M. Grčar, D. Cherepnalkoski, I. Mozetič, and P. Kralj degree and the h-index of the nodes. We used the Herfind- Novak. Stance and influence of Twitter users regarding ahl–Hirschman index to estimate the distribution of influ- the Brexit referendum. Computational Social Networks, ence within the top communities in the network. Finally, by 4(1):6, 2017. analysis of hashtags and URL domains in tweets, we discov- [5] J. E. Hirsch. An index to quantify an individual’s ered the most popular topics for Slovenians as well as the scientific research output. Proceedings of the National most referred Slovenian media on Twitter. We showed that Academy of Sciences, pages 16569–16572, 2005. users from different communities prioritize different topics [6] N. Ljubešić, D. Fišer, and T. Erjavec. TweetCaT: a and use different media to inform themselves. tool for building Twitter corpora of smaller languages. In Proceedings of the Ninth International Conference on 7. ACKNOWLEDGMENTS Language Resources and Evaluation (LREC’14), pages The authors acknowledge financial support from the Slove- 2279–2283, Reykjavik, Iceland, May 2014. European nian Research Agency (research core funding no. P2-103 Language Resources Association (ELRA). and P6-0411), and the European Union’s Rights, Equality [7] M. E. J. Newman. Modularity and community and Citizenship Programme (2014-2020) project IMSyPP structure in networks. Proceedings of the National (Innovative Monitoring Systems and Prevention Policies of Academy of Sciences, 103(23):8577–8582, 2006. Online Hate Speech, grant no. 875263). [8] P. K. Novak, L. D. Amicis, and I. Mozetič. Impact investing market on twitter: influential users and 8. REFERENCES communities. Applied Network Science, 3(1):40, 2018. [1] V. D. Blondel, J.-L. Guillaume, R. Lambiotte, and [9] G. J. Werden. Using the Herfindahl–Hirschman index. E. Lefebvre. Fast unfolding of communities in large In L. Phlips, editor, Applied Industrial Economics, networks. Journal of Statistical Mechanics: Theory and number 2, pages 368–374. Cambridge University Press, Experiment, 2008(10):P10008, 2008. 1998. [2] D. Cherepnalkoski, A. Karpf, I. Mozetič, and M. Grčar. Cohesion and coalition formation in the European 236 Toward improved semantic annotation of food and nutrition data Lidija Jovanovska Panče Panov Jožef Stefan International Postgraduate School & Jožef Stefan Institute & Jožef Stefan Institute Jožef Stefan International Postgraduate School Ljubljana, Slovenia Ljubljana, Slovenia lidija.jovanovska@ijs.si pance.panov@ijs.si ABSTRACT repository without which there is a great difficulty in achieving This paper aims to provide a critical overview of the state-of-the- cross-cultural and expert consensus. 1 art vocabularies used for semantic annotation of databases and In this paper, we will briefly go through the fundamental datasets in the domain of food and nutrition. These vocabularies components of the Semantic Web technologies, as well as the are commonly used as a backbone for creating metadata that is standards for the development of high-level KOS (Section 2). Next, usually used in search. Furthermore, the paper aims to provide a we provide a critical overview of the most significant semantic summary of ICT technologies used for storing food and nutrition resources in the domain of food and nutrition (Section 3). Finally, datasets and searching digital repositories of such datasets. Fi- we present a proposal for the design and implementation of a nally, the results of the paper will provide a roadmap for moving broad ontology that would allow us to harmonize and integrate towards FAIR (findable, accessible, interoperable, and reusable) reference vocabularies and ontologies from different sub-areas food and nutrition datasets, which can then be used in various of food and nutrition (Section 4). AI tasks. 2 BACKGROUND KEYWORDS The goal of the Semantic Web is to make Internet data machine- ontologies, semantic technologies, data mining, food and nutri- readable by enhancing web pages with semantic annotations. tion Linked data is built upon standard web technologies, also in- cluding semantic web technologies in its technology stack [11]. Resource Description Framework (RDF) allows the represen- 1 INTRODUCTION tation of relationships between entities using a simple subject- Today more than ever before in history, we live in an age of predicate-object format known as a triple. The triples form an information-driven science. Vast amounts of information are be- RDF database — called a triplestore — which can be populated ing produced daily as a result of new types of high-throughput with RDF facts about some domain of interest. RDF Schema technology in all walks of life. Consequently, the quantity of (RDFS) was developed immediately after the appearance of RDF available scientific information is becoming overwhelming and as a set of mechanisms for describing groups of related resources without its proper organization, we would not be able to maxi- and the relationships between them. Simple Protocol and RDF mize the knowledge we harvest from it. Namely, research groups Query Language (SPARQL) is the query language for querying carry out their research in different ways, with specific and pos- RDF triples stored in RDF triplestores. sibly incompatible terminologies, formats, and computer tech- The Web Ontology Language (OWL) is based on Descrip- nologies. To tackle these issues, researchers have developed high- tion Logics, a family of logics that are expressively weaker than level knowledge organization systems (KOS), such as ontologies, First Order Logic, but enjoy certain computational properties ad- which constitute the core of the semantic web stack. Throughout vantageous for purposes such as ontology-based reasoning and the years, an abundance of ontologies has been developed and data validation. Most of the ontologies used today are represented released, slowly expanding from the biomedical sciences to the in the OWL format. fields of information science, machine learning, as well as the All the semantic technologies operate on top of various KOS. A domain of food and nutrition science. KOS is intended to encompass all types of schemes for organizing There is an old, yet simple saying which goes: “You are what information and promoting knowledge management [7]. One you eat”. As the world becomes more globalized and food pro- example of a KOS is a thesaurus as a structured, normalized, and duction grows massively, it is becoming increasingly difficult to dynamic vocabulary designed to cover the terminology of a field track the farm-to-fork food path. In the last few decades, digital of specific knowledge. It is most commonly used for indexing technology has been profoundly affecting many health and eco- and retrieving information in a natural language in a system nomic aspects of food production, distribution, and consumption. of controlled terms. When looking at the expressiveness of a Issues regarding food safety, security, authenticity as well as con- KOS, a thesaurus is on the lower side of the scale. On the other flicts arising from biocultural trademark protection are issues side, ontologies enjoy greater expressiveness than thesauri due to that were further enhanced by the lack of a centralized food data the inclusion of description logics. Arp, Smith, and Spear define the term ontology as “A representation artifact, comprising a Permission to make digital or hard copies of part or all of this work for personal taxonomy as proper part, whose representations are intended to or classroom use is granted without fee provided that copies are not made or designate some combination of universals, defined classes, and distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this certain relations between them” [1]. work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 1https://www.nature.com/scitable/knowledge/library/food-safety-and-food- security-68168348/, accessed 22/04/2020 237 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Jovanovska and Panov The Open Biomedical Ontologies (OBO) Foundry applies the of more sophisticated ontologies, such as FoodOn. Even though key principles that ontologies should be open, orthogonal, instan- the OBO Foundry principles apply only to ontologies, we can tiated in a well-specified syntax, and designed to share a common use the more general ones as evaluation criteria for the LanguaL space of identifiers. Open means that the ontologies should be thesaurus. For instance, as previously mentioned, the thesaurus is available for use without any constraint or license and also recep- open, made available in an accepted concrete syntax, versioning tive to modifications proposed by the community. Orthogonal is ensured, textual definitions are available for all the terms and means that they ensure the additivity of annotations and compli- a sufficient amount of documentation is provided. ance with modular development. The proper and well-specified syntax is expected to support algorithmic processing and the FoodOn [4] is an open-source, comprehensive ontology com- common system of identifiers enables backward compatibility posed of term hierarchy facets that cover basic raw food source with legacy annotations as the ontologies evolve [17]. ingredients, process terms for packaging, cooking, and preser- The FAIR guiding principles for scientific data management vation, and different product type schemes under which food and stewardship were conceived to serve as guidelines for those products can be categorized. FoodOn is applicable in several use- who wish to enhance the reusability and invaluableness of their cases, such as personalized foods and health, foodborne pathogen data holdings [19]. The power of these principles lies in the fact surveillance and investigations, food traceability and food webs, that they are simple and minimalistic in design and as such can be and sustainability. FoodOn echoes most of LanguaL’s plant and adapted to various application scenarios. Findability ensures that animal part descriptors —– both anatomical (arm, organ, meat, a globally unique and persistent identifier is assigned to the data seed) and fluid (blood, milk) —– but reuses existing Uberon [12] and the metadata which describes the data. Accessibility ensures and Plant Ontology [10] term identifiers for them. Multiple com- that the data and the metadata can be retrieved by their identifier ponent foods are more challenging because LanguaL provides using a standardized communications protocol. Interoperability no facility for giving identifiers to such products. ensures that data, as well as metadata, use a formal, accessible, Building on top of this, FoodOn allows food product terms like and shared language for knowledge representation. Reusability lasagna noodle to be defined directly in the ontology, and allows ensures that data and metadata are accurately described, released them to reference component products through various relations with a clear and accessible license, have detailed provenance, and which do not exist in LanguaL, such as: "has ingredient", "has meet domain-relevant community standards. part", "composed primarily of". As a suggestion, these relations can all be represented with a single relation "has ingredient" and 3 CRITICAL OVERVIEW OF FOOD AND the quantity can be expressed explicitly when annotating the NUTRITION SEMANTIC RESOURCES objects. All of the ontology terms have unique identifiers and In this section, we provide a critical overview of the most relevant the ontology is accessible and can be searched via The European KOS in the field of food and nutrition. We start by describing Bioinformatics Institute (EMBL-EBI) and its Ontology Lookup LanguaL [8], a thesaurus that serves as a foundation for most of Service (OLS).3 The ontology itself is open-source and is a mem- the ontologies in this domain. We are more focused on analyzing ber of the OBO Foundry. It also includes the upper-level Basic ontologies which belong to different sub-spheres of the food and Formal Ontology (BFO) [1]. The adherence to BFO proves useful nutrition domain. Namely, FoodOn [4], as a more general food in the case of aligning ontologies covering different domains description ontology, ONS [18], relevant in the field of nutritional because they share the same top-level. studies and ISO-Food [6], relevant in the field of annotating iso- topic data acquired from food samples. ONS [18] is the first systematic effort to provide a solid and ex- tensible ontology framework for nutritional studies. ONS was built to fill the gap between the description of nutrition-based LanguaL [8] is a thesaurus used for describing, capturing, and retrieving data about food. Since 1996, it has been used to index prevention of disease and the understanding of the complex im- numerous European Union (EU) and US agency databases, among pact nutrition has on health. Its structure consists of 3334 terms which, the US Department of Agriculture (USDA) Nutrient Data- imported from already existing ontologies and 100 newly de- base for Standard Reference and 30 European Food Information fined terms. The usability of ONS was tested in two scenarios: Resource (EuroFIR) databases. Food ingredients are represented an observational study, which aims at developing novel and af- with indexing terms, preferably in the form of a noun or a phrase. fordable nutritious foods to optimize the diet and reduce the risk The thesaurus also includes precombined terms which are food of diet-related diseases among groups at risk of poverty, and product names to which facet terms have been assigned. There an intervention study represented by the impact of increasing are 4 main facets in LanguaL: A (Product Type), B (Food Source), doses of flavonoid-rich and flavonoid-poor fruit and vegetables C (Part of Plant or Animal), and E (Physical State, Shape, or Form). on cardiovascular risk factors in an “at risk” group study. Other food product description facets include chemical additive, The development of ONS followed FAIR principles and as a preservation or cooking process, packaging, and standard na- result, it has been published in the FAIR-sharing database.4 Be- tional and international upper-level product type schemes. fore defining new terms, the developers of ONS have ensured The LanguaL thesaurus complies with the FAIR guidelines. that they are not yet defined, with the use of the ONTOBEE web The completeness of LanguaL’s indexing is to a large extent service. Terms that were already defined were imported using the assured by the Langual Food Product Indexing (FPI) software, ontology reuse service — ONTOFOX [20]. In compliance with which verifies that all facets have been indexed for each food the OBO Foundry principles, the ONS has been developed to be in the list [8]. It is available online2 and can be queried using a interoperable with other ontologies, as it has been formalized food descriptor or synonym. Its interoperability and reusability are eminent as it represents a cornerstone in the development 3https://www.ebi.ac.uk/ols/ontologies/FoodOn, accessed 22/04/2020 2https://www.langual.org, accessed 22/04/2020 4https://fairsharing.org/bsg-s001068/, accessed 22/04/2020 238 Toward improved semantic annotation of food and nutrition data Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia using the latest OWL 2 Web Ontology Language and RDF speci- fications and edited using Protégé [13] and the Hermit reasoner for consistency checking. It is also accessible, under the Creative Commons license (CC BY 4.0), published on GitHub and at NCBO BioPortal. Moreover, this ensured the adoption of a well-defined and widely adopted structure for the top and mid-level classes and principally the adherence to BFO as upper-level ontology. ISO-Food is an ontology that was conceived to aid with the or- ganization, harmonization, and knowledge extraction of datasets containing information about isotopes, that represent variants of a particular chemical element which differ in neutron number. To develop this ontology a mixed approach was used, a combination of both expert knowledge-driven (bottom-up) and data-driven (top-down) methods. Its main classes include Isotope, Sample, Location, Measurement, Article. The main class Isotope is con- nected to the rest of the classes with respective relations. The Food and Nutrient classes are linked to the RICHFIELDS ontology [5]. The ontology was further applied in a study for describing isotopic data, to annotate a data sample that consists of isotopic measurements of milk and potato samples. The ISO-Food ontology can be accessed online via the Bio- Portal repository of biomedical ontologies.5 It reuses terms from several ontologies, such as the concept Unit from the Units of Measurements Ontology (UO), the classes Food and Component from the RICHFIELDS ontology [5], the class Document from Figure 1: Diagram representing the alignment of the pro- the Bibliographic Ontology (BIBO) [3]. posed ontology with the identified relevant upper-level and domain ontologies. 4 PROPOSAL Ontologies for data mining. To provide a suitable formalized representation of the outcomes of the research in the food and domain of food and nutrition (see Figure 1). In this way, we can nutrition domain, as well as to suggest new ways to extract knowl- also use the benefits of cross-domain reasoning. Since FoodOn, edge from the ever-abundant data produced in this field, we turn ONS, and OntoDM all use BFO as a main top-level ontology, they to ontologies that are used to formally represent the data analysis speak the same general language and are consequently, easier to process. More specifically, we focus on the align. OntoDM ontology, which provides a unified framework for representing data mining entities. It consists of three modular ontologies: Towards the FNS Harmony ontology. In the context of the OntoDM-core [15] which represents core data mining entities, such as datasets, H2020 project FNS Cloud6 (food, nutrition, security) the goal is to data mining tasks, algorithms, models and patterns, develop an infrastructure and services to exploit food, nutrition OntoDT [16] — a generic ontology of datatypes, and and security data (data, knowledge, tools – resources) for a range OntoDM-KDD [14] which describes the process of knowledge discovery. of purposes. To support the different functionalities required by The ontology defines top-level concepts in data mining and the cloud platform, we started with the development of the FNS- machine learning, such as data mining task, algorithm, and their Harmony (FNS-H). The application ontology would allow us to generalizations, which denote the outputs of applying an imple- harmonize and integrate the different reference vocabularies and mentation of an algorithm on a particular dataset. Starting with ontologies from different sub-areas of food and nutrition, as well these general concepts, OntoDM also defines the components of as ontologies representing the domain of data analysis. the algorithms, such as distance and kernel functions, and other features they may contain. From the input and output data per- Initial ontology development. The development of FNS-H, spective, in this ontology, there is a hierarchical representation which is intended to bridge the gap between the field of data of data, from general concepts such as dataset to more specific analysis and food and nutrition will be guided by common best concepts regarding its structure, such as the number of features, practice principles for ontology development. The aim is to max- their role in a given task, concluding with the datatype of each imize the reuse of available ontology resources and simultane- attribute. These properties of OntoDM provide a complete formal ously follow the Minimum Information to Reference an External representation of the data mining process from beginning to end. Ontology Term (MIREOT) principles [2]. In the first phase, we will integrate the FoodOn ontology and the ONS ontology with the OntoDM suite of ontologies. With this integration, we will Combining orthogonal domain ontologies. Our goal is to align the selected ontologies in the domain of food and nutrition be able to (1) define domain-specific data types for the domain with the OntoDM ontology of data mining to improve the se- of food and nutrition by extending OntoDT generic data types; mantic annotation of the food and nutrition domain datasets, as (2) define food and nutrition analysis pipelines for the domain well as to formally represent data analysis tasks performed in the of food and nutrition by extending OntoDM-core, and (3) define 5http://bioportal.bioontology.org/ontologies/ISO-FOOD, accessed 22/04/2020 6https://www.fns-cloud.eu/ 239 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Jovanovska and Panov food and nutrition knowledge discovery scenarios by extending [3] Bojana Dimić Surla, Milan Segedinac, and Dragan Ivanović. OntoDM-KDD ontology. 2012. A bibo ontology extension for evaluation of scien- The development of the ontology already started in a top- tific research results. 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By doing Knowledge Discovery, 28, 5-6, 1222–1265. so, we can provide richer semantic annotation and discover new [16] Panče Panov, Larisa N Soldatova, and Sašo Džeroski. 2016. scenarios of harvesting knowledge from the food and nutrition Generic ontology of datatypes. Information Sciences, 329, data. 900–920. [17] Barry Smith, Michael Ashburner, and Cornelius Rosse ACKNOWLEDGMENTS et al. 2007. The obo foundry: coordinated evolution of This work was supported by the Slovenian Research Agency through the ontologies to support biomedical data integration. Nature grant J2-9230, as well as the European Union’s Horizon 2020 research and biotechnology, 25, 11, 1251–1255. innovation programme through grant 863059 (FNS-Cloud, Food Nutrition [18] Francesco Vitali, Rosario Lombardo, and Damariz Rivero et Security). al. 2018. Ons: an ontology for a standardized description of interventions and observational studies in nutrition. REFERENCES Genes & nutrition, 13, 1, 12. 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Faculty of Information Studies in Jožef Stefan Institute and Naselje nuklearne elektrarne 2 Novo mesto, Ljubljanska cesta 31a, Jožef Stefan International Krško, Slovenia Novo mesto, Slovenia Postgraduate School peter.zupancic91@gmail.com Jožef Stefan Institute, Jamova cesta Jamova cesta 39 39, Ljubljana, Slovenia Ljubljana, Slovenia biljana.mileva@fis.unm.si pance.panov@ijs.si ABSTRACT In this paper, we address the task of absenteeism prediction Absenteeism, or employee absence from work, is a perpetual from time sheets data. More specifically, based on data that we get problem for all businesses, given the necessity to replace an from MojeUre time attendance register system, we want to build a absent worker to avoid a loss of revenue. In this paper, we focus predictive model to predict if or for how many days an employee on the task of predicting worker’s absence based on historical would be absent. In this case, we are considering one-week-ahead timesheet data. The data are obtained from MojeUre, a system for prediction from workers profiles and one year historical time tracking and recording working hours, which includes timesheet sheets data. To predict if an employee will be absent in a given profiles of employees from different companies in Slovenia. More week, we employee the task of binary classification, which can specifically, based on historical data for one year, we want to be addressed by using a large number of binary classification predict, under (which) certain conditions, if an employee will be methods. On the other hand, to predict the number of days an absent from work and for how long (e.g., a week, a month). In employee would be absent in a given week, we employee re- this respect, we compare the performance of different predictive gression, which can be addressed by using regression methods. modeling methods by defining the prediction task as a binary Furthermore, we observe and discuss how adding of aggregate classification task and as a regression task. Furthermore, in the attributes influences the prediction power if used together with case of one week ahead prediction, we test if we can improve the the timesheet profiles. predictions by using additional aggregate descriptive attributes, together with the timesheet profiles. 2 DATA KEYWORDS In this section, we present the MojeUre system and then de- Absenteeism at work, absence prediction, predictive modeling, scribe the structure of the raw data, as well as the process of timesheet data, human resource management data cleaning. Then we present the structure of the dataset, used for learning the predictive and the aggregate attributes, we con- structed in order to test if they would improve the predictive 1 INTRODUCTION power of the predictive models. Companies strive to have better predictive accuracy in their day to day operations, with the main goal of improving the productiv- ity of the human resources (HR) department and hence obtaining 2.1 MojeUre system higher profits and lower HR expenditures. They obtain informa- The MojeUre system (https://mojeure.si) was developed to sup- tion and insight from the large collections of human resource port the process of planning workers schedules, as well as for management (HRM) data that each employer owns, to support recording work attendance and absenteeism. In addition to the day to day operations and decision making, as well as, to comply easy recording of the working hours of employees by a company, to the national and international legislation. the system also provides access to each employee’s own working The new era of HR executives is moving from settling on hours, vacation control, sick leave, travel orders, etc. The system receptive choices exclusively taking into account reports and can be accessed using the web or by using a mobile application. dashboards towards connecting business information and hu- The entry of working hours is done either through a web man asset information to foresee future results which will bring application or a mobile application. In the case the company also changes. Having such data enables them to detect patterns and wants to invests into a working time registrar, this can be done trends, anticipate events and spot anomalies, forecast using what- through the registrar where the employee has a personalized card if simulations and learn of changes in employee behaviour so that for clock-in or clock-out (for example usage of break, such as a employee can take actions that lead to desired business outcomes. lunch break, a private break, etc.). The system allows different The purpose of HRM is measuring employee performance and en- types of registered hours to be entered in the system in a single gagement, studying workforce collaboration patterns, analyzing day. employee churn and turnover and modelling employee lifetime All data used in the paper was obtained from the electronic value [1]. system for recording working hours. There are currently more than 150 different companies that use the system for registering Permission to make digital or hard copies of part or all of this work for personal workers attendance. The basic function of the system is to record or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the arrivals and departures of an employee at work and to record the full citation on the first page. Copyrights for third-party components of this the various types of employee absence, such as sick leave and work must be honored. For all other uses, contact the owner/author(s). vacation leave. In addition, the system covers other absences Information society ’20, October 5–9, 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). such as paternity leave, maternity leave, part-time leave, study leave, student leave, etc. 241 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Zupančič et al. In this paper, we use data from the MojeUre system for the Table 3: Attributes representing the workers profiles year 2019 and we have timesheet attendance data for all 52 weeks. The data instances are composed of three types of attributes: (1) Attribute name Type Description attributes describing workers profiles (See Table 1), (2) attributes describing timesheets absence profiles of each worker (See Table VacationLeave numeric Total days of vacation leave for 2), and (3) attributes that are aggregates from timesheets profiles TotalDays all weeks, which are defined in constructed using domain knowledge (more details about the the timesheets data used for the attributes is provided in Section 2.2). The timesheets attributes descriptive attribute space. composing the absence profile of each worker are calculated SickLeave numeric Total days of sick leave for all based on the logged presence and absence logging data aggre- TotalDays weeks, which are defined in the gated on the week level.. The entire dataset for the whole year timesheets data used for the de- consists of 232 different attributes and 2363 employees which are scriptive attribute space. defined as each row. ShortTerm numeric A count of how many times an VacationLeave3 employee was at vacation leave for at least 3 days per week. Table 1: Workers profile attributes LongTerm numeric A count of how many times an VacationLeave5 employee was on vacation leave Attribute name Type Description for at last 5 days per week. EmployeeID numeric Unique employee identifier. ShortTerm numeric A count of how many times an WorkHour numeric Data indicating how many SickLeave3 employee was on sick leave for hours per day an employee is at least 3 days. employed by contract. LongTerm numeric A count of how many times an CompanyType nominal Company type by specific cate- SickLeave5 employee was on sick leave for gories. at least 5 days. EmploymentYears numeric Describes how many years the WinterVacation numeric The number of vacation leave person has been employed by LeaveAbsence days that were used in winter. the current company. SpringVacation numeric The number of vacation leave JobType nominal Describes type of job (e.g. per- LeaveAbsence days that were used in spring. manent, part-time). SummerVacation numeric The number of vacation leave Region nominal The region in which the em- LeaveAbsence days that were used in summer. ployee’s company is located. AutumnVacation numeric The number of vacation leave LeaveAbsence days that were used in autumn. WinterSickLeave numeric The number of sick leave days Table 2: Timesheet absence profile attributes Absence that were used in winter. SpringSick numeric The number of sick leave days LeaveAbsence that were used in spring. Attribute name Type Description SummerSick numeric The number of sick leave days WeekWNYTotal numeric The number of all absences in LeaveAbsence that were used in summer. a given week, including the AutumnSick numeric The number of sick leave days sum of sick leave and (vacation) LeaveAbsence that were used in autumn. leave. WinterVacation numeric The number of vacation leave WeekWNY numeric The number of absences with LeaveHoliday days that were used in winter VacationLeave type vacation leave in a given during school holidays. week. SpringVacation numeric The number of vacation leave WeekWNY nominal The number of absences with LeaveHoliday days that were used in spring SickLeave type sick leave in a given week. during school spring holidays. WeekWNY nominal Value tells if employee was ab- SummerVacation numeric The number of vacation leave Absence sent at least 1 day in whole LeaveHoliday days that were used in summer week. during school summer holidays. AutumnVacation numeric The number of vacation leave LeaveHoliday days that were used in autumn 2.2 Data prepossessing and feature during school holidays. engineering Feature Engineering is an art (Shekhar A, 2018) and involves the process of using domain knowledge to create features with The period we are considering in our analysis is one year, the goal to increase the predictive power of machine learning that is composed of 52 weeks. For construction of the aggregate algorithms. In this section, we describe the newly constructed attributes, we have defined our seasons by weeks, defined as attributes using domain knowledge. Furthermore, we present the follows: (1) the winter season is defined from week 51 in the process of data cleaning. Before cleaning, the original dataset previous year to week 12 in the New year; (2) the spring season contains 2087 instances of individual employees. The engineered is defined from week 13 to week 25; (3) the summer season is aggregate attributes using domain knowledge from timesheets defined from week 26 week to week 39; and (4) the autumn season profiles are presented in Table 3. is defined from week 40 week to week 49. 242 Absenteeism prediction from timesheet data: A case study Information society ’20, October 5–9, 2020, Ljubljana, Slovenia In addition, we also defined the school holidays by weeks, which are defined as follows: (1) the winter holidays are defined Target Descriptive attributes from week 7 to 8; (2) the spring holidays are defined from week attribute 18 to 19; (3) the summer holidays are defined from week 26 to Timesheet Worker absence Week K week 35; and (4) the autumn holidays are defined from week 44 profile binary profile Absence to week 45. 1-(K-1) week After we cleaned up the initial dataset, we obtained a smaller number of dataset instances. This resulted in a dataset with 961 (a) Without aggregate attributes distinct rows or more precisely different employees. The main Target control statement for the data cleaning was a test if an employee Descriptive attributes attribute has less than one VacationLeaveTotalDays in the defined period. Timesheet Timesheet This would mean that: (1) an employee that fulfills this condition Worker absence absence Week K doesn’t work any more in company; or (2) the company doesn’t profile binary profile aggregates Absence use recording system anymore; or (3) the employee is student 1-(K-1) week 1-(K-1) week and for students the vacation leave days are not recorded as they (b) With aggregate attributes are usually paid per working hour only. The most of employees in the dataset are working in company Figure 1: The structure of the data instances used for learn- type called “Izobraževanje, prevajanje, kultura, šport” (Education, ing predictive models translation services, culture, sports). In addition, most of the em- ployees are coming from the region “Osrednjeslovenska” (Central Slovenia region). The largest number of absence vacation leave or holiday leave was in week 52, which is the last week in year 2019 which is expected. the aggregate attributes were calculated. The absence of the 13th week was used a target attribute. For each quarter, we constructed 3 DATA ANALYSIS SCENARIOS AND two different variants of datasets, one containing the aggregate EXPERIMENTS attributes and the other without the aggregate attributes. This Research question. In general, in this paper we want to perform procedure was done for both tasks: binary classification and re- one-week ahead prediction of employee absence, using worker gression. profile data, historical timesheet data aggregated on a week level, as well as aggregated attributes described in the previous sec- Experimental setup. For our paper, we used Weka as main soft- tion. We explore the task of predicting employee absence both ware [2] to execute predictive modelling experiments. WEKA is as a binary classification task and as a regression task. In the an open source software provides tools for data preprocessing, experiments, we want to test if and how the aggregates attributes implementation of several Machine Learning algorithms, and influence the predictive power of the built models both for the visualization tools so that one can develop machine learning case of binary classification and regression. techniques and apply them to real-world data mining problems. In the experiments, for all methods we used the default method Tasks. In the binary classification task, we want only to predict settings from Weka mining software. The evaluation method if an employee will be absent in a given week. For this case, we used was 10 fold cross-validation. use the boolean attribute WeekWNYAbsence as a target attribute (WNY is the identifier of the target week). In the regression Methods. Here, we used different predictive methods imple- task, we want to predict the number of absence days. For this mented in the WEKA software with different settings. For the case, we use one of the following numeric attributes as targets regression task, we compare the performance of the following WeekWNYTotal (for predicting the total number of absence days), methods Linear regression (LR), M5P (both regression and model WeekWNYVacationLeave (for predicting the number of vacation trees)[3], RandomForest (RF) [4] with M5P trees as base learners, leave days), or WeekWNYSickLeave (for predicting the number Bagg (Bag) [5] having M5P trees as base learners, IBK (nearest of sick leave days). neighbour classifier with different number of neighbours) [6] and SMOreg (support vector regression) [7]. Construction of the experimental datasets For the purpose For binary prediction, we compare the performance of the of analysis, we construct two types of datasets: (1) the first type following methods: jRIP (decision rules) J48 (decision trees) Ran- contain worker profile and timesheet absence profiles as descrip- domForest (RF), Bagging (Bagg) having J48 trees as base learners, tive attributes (see Figure 1a); and (2) the second type includes RandomSubSpace (RS) [8] having J48 trees as base learners, SMO also timesheets absence aggregates (see Figure 1b). (support vector machines) [9], and IBK (nearest neighbour classi- In order to perform analysis, we need to properly construct the fier with different number of neighbours). datasets used for learning predicting models. For example, if we want to predict workers absence for week 15, we use historical Evaluation measures. To answer our research question for the timesheets data from week 1-14 together with the aggregates case of regression, we use several measures for regression anal- calculated on this period as descriptive attributes. ysis, such as: Mean Absolute Error (MAE), Root mean squared We decided to split the year consisting of 52 weeks in four error (RMSE), and Correlation coefficient (CC). quarters (Q1: W1-W13, Q2: W14-W26, Q3:W27-W39, Q4:W40- For the case of classification, we use several measures for clas- W52), each containing 13 weeks. The absence data for the first sification analysis, such as: the percentage of correctly classified 12 weeks were used as historical timesheet profiles, out of which instances (classification accuracy), precision, and recall. 243 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Zupančič et al. Table 4: Predictive performance results. The bold value denotes the highest value when we compare datasets with (A) or without (NA) added aggregate attributes. The gray cells denote the best performing method for each dataset. (a) Performance results for the regression task - RMSE measure (less is better) Dataset LR MP5 M5P-R RF Bagg IBK(K=1) IBK(K=3) IBK(K=7) SMOreg Q1-A 0.789 0.692 0.775 0.688 0.64 0.804 0.687 0.734 0.681 Q1-NA 0.723 0.674 0.767 0.729 0.647 0.798 0.693 0.724 0.659 Q2-A 1.692 1.369 1.422 1.412 1.438 1.894 1.476 1.382 1.617 Q2-NA 1.44 1.382 1.396 1.457 1.379 1.752 1.506 1.425 1.497 Q3-A 0.942 0.919 0.976 0.999 0.935 1.409 1.074 1.015 0.963 Q3-NA 0.911 0.929 0.956 0.968 0.927 1.223 1.046 1.017 0.969 Q4-A 0.977 0.947 0.961 0.923 0.922 1.222 1.029 1.005 0.984 Q4-NA 0.992 0.985 0.976 1.024 0.975 1.186 1.066 0.999 1.007 (b) Performance results for the classification task - Accuracy in% (more is better) Dataset JRip j48 RF Bagg RS SMO IBK(K=1) IBK(K=3) IBK(K=7) Q1-A 87.429 90.810 90.357 90.833 89.881 92.762 87.452 91.810 90.810 Q1-NA 87.429 90.810 90.381 89.857 90.357 90.833 89.429 91.810 90.833 Q2-A 63.645 68.879 65.751 65.419 66.736 69.200 58.153 64.347 68.842 Q2-NA 66.466 68.177 67.118 66.441 66.429 66.773 65.049 62.291 67.463 Q3-A 84.429 84.404 83.288 83.061 84.409 86.677 77.182 82.616 85.333 Q3-NA 83.737 83.520 82.379 83.737 84.864 86.449 81.263 85.101 84.879 Q4-A 71.130 67.277 72.150 70.460 70.305 70.452 69.627 70.644 70.302 Q4-NA 70.455 68.266 66.774 67.441 69.791 69.466 66.093 67.610 68.960 4 RESULTS AND DISCUSSION be absent in a given week). To see the difference in performance, Regression task1. In Table 4a, we present the results for RMSE we performed experiments on datasets constructed on different measure. It indicates how close the observed data points are to quarters of the year. The best prediction method in the case of re- the model’s predicted values, and lower values indicate better fit. gression is Bagging and in general we could say that predictions From the results, we can observe that in general Bagging of M5P are slightly better if we don’t use aggregate attributes. The best trees obtains the best performance. Predicting absence in week method in the case of classification is SMO. Again almost same 13 from Q1 is generally better without using aggregate attributes. results with using or not using external aggregate attributes. We have similar behaviour for predicting absence in week 26 (Q2) In future work, we plan to perform selective analysis of absen- and week 39 (Q3). Predicting absence for the last week in the teeism using the same data based on different criteria, such as year from Q4 is generally better done using additional aggregate seasonality, closeness to holidays (before, after), critical weeks for attributes. If we consider MAE, the best performing method is certain professions etc. In addition, we plan to perform regional SMOreg, and for Q1, Q2 better results are obtained without the analysis and workers domain analysis which is based on com- use of aggregate attributes, opposite to the Q3 and Q4. Finally, if pany type. Moreover, more insight into absence patterns will be we consider CC the best performing method is Bagging, and for available after collecting several years of attendance data for each Q1 and Q4 better results are obtained without using aggregate employee. Finally, we plan to compare the different granularity attributes, opposite to Q2 and Q3. of prediction (day - based vs. week - based vs. half a month based vs. month based analysis). Classification task2. In Table 4b, we present the results for accuracy. From the results, we can observe that in general SMO ACKNOWLEDGMENTS obtains the best performance. For Q1, we obtain better results We thank the company 1A Internet d.o.o., which provided us access to if we do not include aggregate attributes. For Q2, Q3 and Q4 the data which were used in our research. Panče Panov is supported by the best results are obtained by using the additional aggregate the Slovenian Research Agency grant J2-9230. attributes. If we consider precision the best performing methods are SMO and JRip, while for recall the best performing method REFERENCES is IBK using 7 nearest neighbours. [1] Malisetty, S., Archana, R. V., & Kumari, K. V. (2017). Predictive analytics in HR management., Indian Journal of Public Health Research & Development, 8(3), 115-120. 5 CONCLUSION AND FUTURE WORK [2] Witten, I. H., & Frank, E. (2002). Data mining: practical machine learning tools The main goal of the paper was to test if adding additional and techniques with Java implementations., Acm Sigmod Record, 31(1), 76-77. [3] Ross J. Quinlan. Learning with Continuous Classes. In: 5th Australian Joint timesheet aggregate attributes can influence the predictive power Conference on Artificial Intelligence., Singapore, 343-348, 1992. in the case of one-week ahead absenteeism prediction from [4] Leo Breiman (2001). Random Forests., Machine Learning. 45(1):5-32. timesheet data. The research was performed on data from year [5] Leo Breiman (1996). Bagging predictors., Machine Learning. 24(2):123-140. [6] D. Aha, D. Kibler (1991). Instance-based learning algorithms., Machine Learning. 2019, collected by the MojeUre work attendance register system. 6:37-66. We used various predictive modelling methods formulating the [7] S.K. Shevade, S.S. Keerthi, C. Bhattacharyya, K.R.K. Murthy. Improvements to the prediction task as regression (predicting the number of absent SMO Algorithm for SVM Regression., In: IEEE Transactions on Neural Networks, 1999. days in a week) and classification (predicting if an employee will [8] Tin Kam Ho (1998) The Random Subspace Method for Constructing Decision Forests., IEEE Transactions on Pattern Analysis and Machine Intelligence. 1Complete results for regression are presented at the following URL 20(8):832-844. URL http://citeseer.ist.psu.edu/ho98random.html. https://tinyurl.com/yyp85vfr [9] J. Platt. Fast Training of Support Vector Machines using Sequential Minimal 2Complete results for classification are presented at the following URL Optimization., In B. Schoelkopf and C. Burges and A. Smola, editors, Advances https://tinyurl.com/y6o6h6d8 in Kernel Methods - Support Vector Learning, 1998. 244 Monitoring COVID-19 through text mining and visualization M.Besher Massri Joao Pita Costa Andrej Bauer Jožef Stefan Institute, Slovenia Quintelligence, Slovenia University of Ljubljana, Slovenia besher.massri@ijs.si joao.pitacosta@quintelligence.com andrej.bauer@andrej.com Marko Grobelnik Janez Brank Luka Stopar Jožef Stefan Institute, Slovenia Jožef Stefan Institute, Slovenia Jožef Stefan Institute, Slovenia marko.grobelnik@ijs.si janez.brank@ijs.si luka.stopar@ijs.si ABSTRACT The global health situation due to the SARS-COV-2 pandemic motivated an unprecedented contribution of science and tech- nology from companies and communities all over the world to fight COVID-19. In this paper, we present the impactful role of text mining and data analytics, exposed publicly through IRCAI’s Coronavirus Watch portal. We will discuss the available technol- ogy and methodology, as well as the ongoing research based on the collected data. KEYWORDS Text mining, Data analytics, Data visualisation, Public health, Figure 1: Coronavirus Watch portal Coronavirus, COVID-19, Epidemic intelligence 1 INTRODUCTION the lack of resolution of the data in aspects like the geographic When the World Health Organization (WHO) announced the location of reported cases, the commodities (i.e., other diseases global COVID-19 pandemic on March 11th 2020 [25], following that also influence the death of the patient), the frequency of the the rising incidence of the SARS-COV-2 in Europe, the world data, etc. On the other hand, it was not common to monitor the started reading and talking about the new Coronavirus. The ar- epidemic through the worldwide news (with some exceptions as rival of the epidemic to Europe scaled out the news published the Ravenpack Coronavirus News Monitor [21]). about the topic, while public health institutions and governmen- The Coronavirus Watch portal suggests the association of tal agencies had to look for existing reliable solutions that could reported incidence with worldwide published news per country, help them plan their actions and the consequences of these. which allows for real-time analysis of the epidemic situation Technological companies and scientific communities invested and its impact on public health (in which specific topics like efforts in making available tools (e.g. the GIS [1] later adopted mental health and diabetes are important related matters) but by the World Health Organisation (WHO)), challenges (e.g. the also in other domains (such as economy, social inequalities, etc.). Kaggle COVID-19 competition [13]), and scientific reports and This news monitoring is based on state-of-the-art text mining data (e.g. the repositories medRxiv [15] and Zenodo [27]). technology aligned with the validation of domain experts that In this paper we discuss the Coronavirus Watch portal [12], ensures the relevance of the customized stream of collected news. made available by the UNESCO AI Research Institute (IRCAI), Moreover, the Coronavirus Watch portal offers the user other comprehending several data exploration dashboards related to perspectives of the epidemic monitoring, such as the insights the SARS-COV-2 worldwide pandemic (see the main portal in from the published biomedical research that will help the user Figure 1). This platform aims to expose the different perspectives to better understand the disease and its impact on other health on the data generated and trigger actions that can contribute to conditions. While related work was promoted in [13] in relation a better understanding of the behavior of the disease. with the COVID-19, and is offered in general by MEDLINE mining tools (e.g., MeSH Now [16]), there seems to be no dedicated tool 2 RELATED WORK to the monitoring and mining of COVID-19 - related research as that presented here. The many platforms that have been made publicly available over the internet to monitor aspects of the COVID-19 pandemics are mostly focusing on data visualization based on the incidence of 3 DESCRIPTION OF DATA the disease and the death rate worldwide (e.g., the CoronaTracker 3.1 Historical COVID-19 Data [3]). The limitations of the available tools are potentially due to To perform an analysis of the growth of the coronavirus, we need Permission to make digital or hard copies of all or part of this work for personal to use the historical data of cases and deaths. This data is retrieved or classroom use is granted without fee provided that copies are not made or from a GitHub repository by John Hopkins University[4]. The distributed for profit or commercial advantage and that copies bear this notice and data source is based mainly on the official data from the World the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy Health Organization (WHO)[24] along with some other sources, otherwise, or republish, to post on servers or to redistribute to lists, requires prior like the Center for Disease and Control[2], and Worldometer[26], specific permission and/or a fee. Request permissions from permissions@acm.org. among others. This data provides the basis for all functionality Information society ’20, October 5–9, 2020, Ljubljana, Slovenia © 2020 Association for Computing Machinery. that depended on the statistical information about COVID-19 numbers. 245 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia 3.2 Live Data from Worldometer Apart from historical data, live data about the COVID-19 number of cases, deaths, recovered, and tests are retrieved from the worl- dometer website. Although the cases might not be as official as the one provided by John Hopkins University (which is based on WHO data), this source is updated many times per day providing the latest up-to-date data about COVID-19 statistics at all times. 3.3 Live News about Coronavirus The live news is retrieved from Event Registry [10], which is a media-intelligence platform that collects news media from around the world in many languages. The service analyzes news from more than 30,000 news, blogs, and PR sources in 35 lan- Figure 2: A snapshot of the 5D Visualization on March guages. 23rd. Countries that were at the peak in terms of growth are shown high up like Turkey. Whereas countries that 3.4 Google COVID-19 Community mostly contained the virus are shown down like China. Mobility Data Google’s Community Mobility [11] data compares mobility pat- by clicking on the country name on the left table. As seen in terns from before the COVID-19 crisis and the situation on a figure 1. weekly basis. Mobility patterns are measured as changes in the frequency of visits to six location types: Retail and recreation, 4.3 Statistical Visualizations Grocery and pharmacy, Parks, Transit stations, Workplaces, and Residential. The data is provided on a country level as well as on The following set of visualization all aims at displaying the statis- a province level. tics about COVID-19 cases and deaths in a visual format. While they all provide countries comparison, each one focus on differ- ent perspective; Some are more complex and focus on the big 3.5 MEDLINE: Medical Research Open picture (5D evolution), and some are simple and focus on one Dataset aspect (Progression and Trajectory). Besides, all of them have The MEDLINE dataset [14] contains more than 30 million cita- configuration options to tweak the visualization, like the ability tions and abstracts of the biomedical literature, hand-annotated to change the scale of the axes to focus on the top countries or by health experts using 16 major categories and a maximum of the long tale. Or a slider to manually move through the days for 13 levels of deepness. The labeled articles are hand-annotated by further inspection. Furthermore, the default view compares all humans based on their main and complementary topics, and on the countries or the top N countries, depending on the visualiza- the chemical substances that they relate to. It is widely used by tion. However, it’s possible to track a single country or a set of the biomedical research community through the well-accepted countries and compare them together for a more focused view. search engine PubMed [19]. This is done by selecting the main country by clicking on it on the left table and proceeding to select more countries by pressing 4 CORONAVIRUS WATCH DASHBOARD the ctrl key while clicking on the country. The main layout of the dashboard displayed in figure 1 consists 4.3.1 5D Evolution. 5D Evolution is a visualization that displays of two sides. It is split into the left table of countries, where a the evolution of the virus situation through time. It is called like simple table of statistics is provided about countries along with that since it encompasses five dimensions: x-axis, y-axis, bubble the total numbers of cases, deaths, and recovered. On the right size, bubble color, and time, as seen in figure 2. By default, it il- side, there is a navigation panel with tabs, each representing a lustrates the evolution of the virus in countries based on N. cases functionality. Each functionality answers some questions and (x-axis), The growth factor of N. Cases (y-axis), N. Deaths (bubble provides insights about a certain type of data. size), and country region (bubble color) through time. In addition, a red ring around the country bubble is drawn whenever the first 4.1 Coronavirus Data Table death appears. The growth rate represents how likely that the The data table functionality is a simple table that shows the basic numbers are increasing with respect to the day before. A growth statistics about the new coronavirus. It’s taken from Worldometer rate of 2 means that the numbers are likely to double in the next as it’s the most frequently updated source for coronavirus. The day. The growth rate is calculated using the exponential regres- data table comes in two forms, one that is a simplified version sion model. At each day the growth rate is based on the N. cases which is the table on the left, and one contains the full information from the previous seven days. The goal of this visualization to in a separate tab. show how countries relate to each other and which are exploding in numbers and which ones managed to "flatten the curve", since 4.2 Coronavirus Live News flattening the curve means less growth rate. It’s intended to be one visualization that gives the user a big picture of the situation. The second functionality is a live news feed about coronavirus from around the world. The feed comes from Event Registry, 4.3.2 Progression. The progression visualization displays the which is generated by querying for articles that are annotated simple Date vs N. cases/deaths line graph. It helps to provide with concepts and keywords related to coronavirus. The user can a simplistic view of the situation and compare countries based check for a country’s specific news (news source in that country) on the raw numbers only. The user can display the cumulative 246 Monitoring COVID-19 through text mining and visualization Information society ’20, October 5–9, 2020, Ljubljana, Slovenia numbers where each day represents the numbers up to now, or daily where at each date the numbers represent the cases/deaths on that day only. 4.3.3 Trajectory. While the progress visualization displays the normal date vs N. cases/deaths, this visualization seeks to com- pare how the trajectory of the countries differ starting from the point where they detect cases. This visualization helps to com- pare countries’ situations if they all start having cases on the same date. The starting point has been set to the day the country reaches 100 cases, so we would compare countries when they started gaining momentum. 4.4 Time Gap The time gap functionality tries to estimate how the countries are aligned and how many days each country is behind the other, whether that is in the number of cases or deaths. This assumes that the trajectory of the country will continue as it with taking much more strict/loose measurements, which is a rough assump- tion. It helps to estimate how bad or good the situation in terms of the number of days. To see the comparison, a country has to Figure 3: A snapshot of the Social Distancing Simulator. be selected from the table on the left. However, not all countries The canvas show a representation of the population. with are comparable as they have very different trajectories or growth red dots representing sick people, yellow dots represent- rates. ing immunized people, and grey dots represent deceased The growth of each country is represented as an exponential people. function, the base is calculated using linear regression on the log of the historical values (that is, exponential regression). Based on that, the duplication N. days, or the N. days the number of The simulator is controlled by three parameters. First, Social cases/deaths will double is determined. two countries are compa- distancing that controls to what extent the population enforces rable if they have a reasonable difference is the base or doubling social distancing. At 0% there is no social distancing and per- factor. If they are comparable, we see where the country with the sons move with maximum speed so that there is a great deal smaller value fits in the historical values of the country with the of contact between them. At 100% everyone remains still and larger numbers, with linear interpolation if the number is not there is no contact at all. Second, mortality is the probability exact, hence the decimal values. that a sick person dies. If you set mortality to 0% nobody dies, while the mortality of 100% means that anybody who catches the infection will die. Finally, infection duration determines how 4.5 Mobility long a person is infected. A longer time gives an infected person The mobility visualization is based on google community mo- more opportunities to spread the infection. Since the simulation bility data that describe how communities in each country are runs at high speed, time is measured in seconds. moving based on 6 parameters: Retail and recreation, Grocery and pharmacy, Parks, Transit stations, Workplaces, and Residen- 4.7 Biomedical Research Explorer tial. The data is then reduced to 2-dimensional data while keeping To better understand the disease, the published biomedical sci- the Euclidean proximity nearly the same. The visualization can ence is the source that provides accurate and validated infor- indicate that the closer the countries are on the visualization, the mation. Taking into consideration a large amount of published similar the mobility patterns they have. The visualization uses science and the obstacles to access scientific information, we the T-SNE algorithm for dimensionality reduction [23], which made available a MEDLINE explorer where the user can query reduces high dimensional data to low dimensional one while the system and interact with a pointer to specify the search re- keeping the distance proximity between them proportionally sults (e.g., obtaining results on biomarkers when searching for the same as possible. The algorithm works in the form of iter- articles hand-annotated with the MeSH class "Coronavirus"). ations, at each iteration, the bubbles representing the country To allow for the exploration of any health-related texts (such as are drawn. We used those iterations to provide animation to the scientific reports or news) we developed an automated classifier visualization. [5] that assigns to the input text the MeSH classes it relates to. The annotated text is then stored in Elasticsearch [18], from where 4.6 Social Distancing Simulator it can be accessed through Lucene language queries, visualized The Social Distancing simulator is displayed in figure 3. Each over easy-to-build dashboards, and connected through an API circle represents a person who can be either healthy (white), to the earlier described explorer (see [8], [20] and [17] for more immune (yellow), infected (red), or deceased (gray). A healthy detail). person is infected when they collide with an infected person. The integration of the MeSH classifier with the worldwide After a period of infection, a person either dies or becomes per- news explorer Event Registry allows us to use MeSH classes in manently immune. Thus the simulation follows the Susceptible- the queries over worldwide news promoting an integrated health Infectious-Recovered-Deceased (SIRD) compartmental epidemio- news monitoring [9] and trying to avoid bias in this context logical model. [7]. An obvious limitation is a fact that the annotation is only 247 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia available for news written in the English language, being the [7] J. Pita Costa et al. 2019. Health news bias and its impact unique language in MEDLINE. in public health. In Proceedings of the Slovenian KDD con- ference. 5 CONCLUSION AND FUTURE WORK [8] J. Pita Costa et al. 2020. Meaningful big data integration for In this paper, we presented the coronavirus watch dashboard as a global covid-19 strategy. Computer Intelligence Magazine. a use-case of observing pandemic. However, this methodology [9] J. Pita Costa et al. 2017. Text mining open datasets to sup- can be applied to other kinds of diseases given the availability of port public health. In WITS 2017 Conference Proceedings. similar data. For further development, we plan to implement a [10] EventRegistry. 2020. Event Registry. https://eventregistry. local dashboard for other countries as well which would provide org. (2020). local data in the local language. In addition, given the existence of [11] Google. 2020. Google COVID-19 Community Mobility Re- more than seven months of historical data, we would like to build port. https://www.google.com/covid19/mobility/. (2020). some predictive models to predict the number of cases/deaths in [12] IRCAI. 2020. IRCAI coronavirus watch portal. http : / / the next few days. coronaviruswatch.ircai.org/. (2020). Moreover, we are using the StreamStory technology [22] in [13] Kaggle. 2020. Kaggle covid-19 open research dataset chal- order to: (i) compare the evolution of the disease between coun- lenge. https : / / www. kaggle. com / allen - institute - for - tries by comparing their time-series of incidence; (ii) investi- ai/CORD-19-research-challenge. (2020). gate the correlation between the incidence of the disease with [14] MEDLINE. 2020. MEDLINE description of the database. weather conditions and other impact factors; and (iii) analyze https://www.nlm.nih.gov/bsd/medline.html. (2020). the dynamics of the evolution of the disease based on incidence, [15] medRxiv. 2020. medRxiv covid-19 sars-cov-2 preprints morbidity, and recovery. This technology allows for the anal- from medrxiv and biorxiv. https://connect.medrxiv.org/ ysis of dynamical Markov processes, analyzing simultaneous relate/content/181. (2020). time-series through transitions between states, offering several [16] MeSHNow. 2020. MeSHNow. https://www.ncbi.nlm.nih. customization options and data visualization modules. gov/CBBresearch/Lu/Demo/MeSHNow/. (2020). Furthermore, following the work done in the context of the [17] MIDAS. 2020. MIDAS COVID-19 portal. http : / / www. Influenza epidemic in [6], we are using Topological Data Analysis midasproject.eu/covid-19/. (2020). methods to understand the behavior of COVID-19 throughout [18] Elastic NV. 2020. Elasticsearch portal. https://www.elastic. Europe. In it, we examine the structure of data through its topo- co/. (2020). logical structure, which allows for comparison of the evolution [19] PubMed. 2020. PubMed biomedical search engine. https: of the epidemics within countries through the encoded topology //pubmed.ncbi.nlm.nih.gov/. (2020). of their incidence time series. [20] Quintelligence. 2020. Quintelligence COVID-19 portal. http://midas.quintelligence.com/. (2020). ACKNOWLEDGMENTS [21] Ravenpack. 2020. Ravenpack coronavirus news monitor. The first author has been supported by the Knowledge 4 All https://coronavirus.ravenpack.com/. (2020). foundation and the H2020 Humane AI project under the European [22] Luka Stopar. 2020. StreamStory. http://streamstory.ijs.si/. research and innovation programme under GA No. 761758), while (2020). the second author was funded by the European Union research [23] Laurens van der Maaten and Geoffrey Hinton. 2008. 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In Proceedings of the Slovenian KDD conference. 248 Usage of Incremental Learning in Land-Cover Classification Jože Peternelj Beno Šircelj Klemen Kenda Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jamova 39, 1000 Ljubljana, Jamova 39, 1000 Ljubljana, Jožef Stefan International Slovenia Slovenia Postgraduate School joze.peternelj@ijs.si beno.sircelj@ijs.si Jamova 39, 1000 Ljubljana, Slovenia klemen.kenda@ijs.si ABSTRACT 2. DATA In this paper we present a comparison of a variety of incre- 2.1 EO data mental learning algorithms along with traditional (batch) The Earth observation data were provided by the Sentinel 2 learning algorithms in an earth observation scenario. The mission of the EU Copernicus programme, whose main ob- approach was evaluated with the earth observation data jectives are land monitoring, detection of land use and land set for land-cover classification from Europe Space Agency’s changes, support for land cover creation, disaster relief sup- Sentinel-2 mission, the digital elevation model and the ground port and monitoring of climate change [2]. The data com- truth data of land use and land cover from Slovenia. We prise 13 multi-spectral channels in the visible/near- infrared show that incremental algorithms can produce competitive (VNIR) and short wave infrared (SWIR) spectral range with results while using less time than batch methods. a temporal resolution of 5 days and spatial resolutions of 10m, 20m and 60m [8]. The Sentinel’s Level-2A products Keywords (surface reflections in cartographic geometry) were accessed remote sensing, earth observation, incremental learning, ma- via the services of SentinelHub1 and processed using eo- chine learning, classification learn2 library. Additionally, a digital elevation model for Slovenia (EU-DEM) with 30m resolution3 was used. 1. INTRODUCTION 2.2 LULC data Land cover classification is one of the common and well re- searched tasks of machine learning (ML) in the Earth Ob- LULC (Land Use Land Cover) data for Slovenia is collected servation (EO) community [1]. The challenge is to classify by the Ministry of Agriculture, Forestry and Food and is land into different types based on remote sensing data such publicly available [10]. The data is provided in shapefile for- as satellite images, radar data, information on weather [12] mat, with each polygon representing a patch of land marked and altitude. The most commonly used data are satellite with one of the LULC classes. Originally there were 25 images, which may vary in acquisition period, resolution or classes, but we introduced a more general dataset by group- wavelength. A plethora of algorithms have explored the po- ing similar classes together. The frequencies of 8 newly tential of using a single-date image [3] and even time series grouped classes are shown in Figure 1. of images for the task [11, 13]. Extensive work with state- of-the-art accuracy was performed using methods of deep 2.3 Feature Engineering learning [14]. The latter report a high computational effort The EO data were collected for the whole year. 4 raw band in the learning and forecasting phase, which reduces their measurements (red, green, blue - RGB and near-infrared potential for continuous tasks requiring a timely response. - NIR) and 6 relevant vegetation- related derived indices There have also been efforts to reduce learning and predic- (normalized differential vegetation index - NDVI, normal- tion times using intelligent feature selection [6, 7]. To the ized differential water index - NDWI, enhanced vegetation best of our knowledge, no cases have been reported where index - EVI, soil-adjusted vegetation index - SAVI, structure stream models have been used in an EO scenario. The pri- intensive pigment index - SIPI and atmospherically resis- mary purpose of incremental learning would be to reduce the tant vegetation index - ARVI) were considered. The derived computational cost of classification, regression, or clustering indices are based on extensive domain knowledge and are techniques, which, when dealing with large data provided used for assessing vegetation properties. One example is the by Sentinel 2 and other sources, can be a significant cost to NDVI index, which is an indicator of for vegetation health organizations trying to extract knowledge from that data. and biomass. Its value changes during the growth period One of the advantages of incremental learning is that it is of the plants and differs significantly from other unplanted not necessary to load all the data into memory at once when creating a model. We only need to store the model and the 1https://www.sentinel-hub.com/ part of the data we are processing. This could be especially 2https://github.com/sentinel-hub/eo-learn useful in various EO scenarios, as the data from Copernicus 3https://www.eea.europa.eu/data-and-maps/data/ services is estimated to exceed 150PB. eu-dem#tab-original-data 249 Figure 1: Frequencies of grouped classes for LULC data from 2017 show that the new simplified clas- sification preserves the most common classes sepa- rated and merges the less common classes. Classes with the lowest frequencies were selected for over- sampling. areas. The NDVI is calculated as: N IR − red N DV I = NIR + red Figure 2: Example of some of the timeless fea- tures. ARVI_max_mean_len shows the length of max- Timeless features were extracted based on Valero et al. [11]. imum mean value in a sliding temporal neighbour- These features can describe the three most important crop hood of ARVI index. BLUE_max_mean_surf shows the stages: the beginning of greenness, the ripening period and surface of the flat interval area containing the peak the beginning of senescence [11, 13]. Annual time series using the blue raw band. EVI_mean_val shows mean have different shapes due to the phenological cycle of a crop value of EVI index and SAVI_neg_sur shows the max- and characterize the development of a crop. With timeless imum surface of the first negative derivative interval features, they can be represented in a condensed form. of SAVI index. For each pixel, 18 features per each of 10 time series were generated. From elevation data, the raw value and maxi- q mum tilt for a given pixel were calculated as 2 additional checks if the ratio is less than 1 − , where = log 1/δ 2n features. In total 182 features were constructed. From these and 1 − δ is desired confidence. If the ratio is small enough, features only a Pareto-optimal subset of 9 features was se- meaning that attribute A is really better than attribute B, lected [6]. then the algorithm divides the node by that attribute. 3. METHODOLOGY Bagging of HT (incremental ) Classification accuracy ( CA ) and F1 score were calcu- Given a standard training set D of size n, bagging generates lated for 11 different ML methods, 6 batch learning meth- m new training sets Di, each of size n0, by uniform sampling ods and 5 incremental learning methods. All incremental from D. Because the sampling is done with replacement, learning methods are available in the ml-rapids (MLR)4 li- some observations can be repeated in each Di. If n0 = n, brary which has been developed in order to support the use then for large n the set Di is expected to have the fraction of incremental learning techniques within eo-learn [4] library. (1 − 1/e)(≈ 63.2%) of the unique examples of D, the rest being duplicates. Then, m HT models are fitted using the Hoeffding Tree (incremental ) above m samples and combined by voting. To include a new Hoeffding tree (HT) is an incremental decision tree that can sample, a random subset of models are selected according learn from massive streams. It assumes that the distribution to Poisson distribution [9], and these models are updated of generating examples does not change over time. The Ho- with the sample in the same way as the HT model described effding tree begins as an initially empty leaf. Each time the above. new example arrives, the algorithm sorts it down the tree (it updates the internal nodes statistics ) until it reaches the Na¨ıve Bayes (incremental) leaf. When it reaches the leaf, it updates the leaf statistics of Na¨ıve Bayes (NB) is a classification technique based on Bayes’s all unused attributes. It then takes the best (A) and second- Theorem. It lets us calculate the probability of data belong- best (B) attributes based on standard deviation and calcu- ing to a given class, given prior knowledge. Bayes’ Theorem lates the ratio of their reductions. To find the best attribute is: to split a node the Hoeffding bound is used. First algorithm P (data|class) timesP (class) 4 P (class|data) = https://github.com/JozefStefanInstitute/ml-rapids P (data) 250 where P (class|data) is the probability of class given the pro- vided data. To add a new training instance, NB only needs to update relevant entries in its probability table. Logistic Regression (incremental ) Logistic regression is a statistical model that in its basic form uses a logistic function to model a binary dependent variable. A model with two predictors x1 and x2 and a binary variable Y , denoted by p = P (Y = 1), which gives us the odds of the values belonging to the class p. The relationship between these terms can be modeled with the following equation: 1 p = 1 + e−(β0+β1x1+β2x2) The parameters β0, β1, β2 can be determined by stochastic gradient descend using logistic loss function. Figure 4: F1 score vs. inference time of different Perceptron (incremental) models for predicting LULC classes. *Denotes in- Perceptron is very similar to Logistic regression. It models a cremental algorithms. binary variable with the same activation function. The only difference is in the cost function that is used for gradient descend. Batch learning methods We can observe that ml-rapid’s Na¨ıve Bayes, Hoeffding Tree, Batch learning methods learn from the whole training set Bagging of HT, Decision Trees, LGBM and Random Forest and do not have to rely on heuristics (e.g. Hoeffding bound) belong to the Pareto optimal set of algorithms according to or incremental approaches (like SGD) for building the model. the training time and F1 score. Regarding inference times The following batch methods have been tested: decision Logistic Regression, Decision Trees and Random Forest are trees, gradient boosting (LGBM), random forest, percep- the only Pareto optimal algorithms. The choice of algo- tron, multi-layer perceptron, and logistic regression [5]. rithm depends on the available processing power and time. For a system that has a lot of time and resources available, 4. RESULTS it would be best to use Random Forest as it has the high- est F1 score. In practice, this is not always feasible. For Results of the experiments are summarised in Figures 3, example, if the algorithm were used for an on-board system 4 and Table 1. Figures depict dependency of algorithm- on the satellite, we could not afford to save all the data and specific F1 score vs. its training and inference times. An would prefer to load only the model. With an incremental ideal algorithm would be located in the top left corner, algorithm, the data could be collected, processed and dis- achieving full F1 score with a training and inference time of carded while the acquired knowledge would be stored in the 0. Any algorithm that has no other algorithm in its top-left model. Another preference for HT would be in a wrapper quadrant (no algorithm is both more accurate and faster) feature selection algorithm [6]. This type of algorithms do belongs to a Pareto front, which means that this algorithm a lot of evaluations of the selected method. The main re- is optimal for a certain set of use-cases. sult is a subset of features that can later be used with other algorithms. The acquired set of features might be biased towards the method used, but the results would be obtained much faster. From the confusion matrix of the HT algorithm shown in Figure 5, we can see that shrubland is often wrongly classi- fied as forest, bareland or grassland and vice versa. This is mainly due to the unclear distinction between these classes (e.g. shrubland can be anything between bareland and for- est) and poor ground truth data due to infrequent updates, low accuracy, and lack of detail (e.g. patch of land labeled as shrubland can also grassland and trees). The unclear dis- tinction between certain classes may also explain confusion between wetlands and shrubland or wetlands and grassland, as wetlands may be covered with grass or shrubs. The lack of detail also contributes to misclassification between grass- land and artificial surface, as not every small grassy area, such as park or lawn, is included in ground truth data. Fi- Figure 3: F1 score vs. training time of different nally, grass cultures, unused land overgrown by grass and models for predicting LULC classes. *Denotes in- rotation of crops are likely some of the reasons for confusion cremental algorithms. between cultivated land and grassland. 251 7. REFERENCES [1] D4.7 stream-learning validation report, May 2020. Perceptive Sentinel. [2] Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., Hoersch, B., Isola, C., Laberinti, P., Martimort, P., et al. Sentinel-2: Esa’s optical high-resolution mission for gmes operational services. Remote sensing of Environment 120 (2012), 25–36. [3] Gómez, C., White, J. C., and Wulder, M. A. Optical remotely sensed time series data for land cover classification: A review. ISPRS Journal of Photogrammetry and Remote Sensing 116 (2016). [4] H2020 PereptiveSentinel Project. Eo-learn library. https://github.com/sentinel-hub/eo-learn. Accessed: 2019-09-06. [5] Hastie, T., Tibshirani, R., and Friedman, J. The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media, 2009. [6] Koprivec, F., Kenda, K., and Šircelj, B. Fastener feature selection for inference from earth observation Figure 5: Confusion matrix of HT based model for data. Entropy (Sep 2020). predicting LULC classes. [7] Koprivec, F., Peternelj, J., and Kenda, K. Feature Selection in Land-Cover Classification using Training Inference EO-learn. In Proc. 22th International Multiconference CA F1 time time (Ljubljana, Slovenia, 2019), vol. C, Institut ”Jožef LGBM 4.87 0.38 0.86 0.86 Stefan”, Ljubljana, pp. 37–40. Decision Tree 4.18 0.02 0.82 0.82 [8] Koprivec, F., Čerin, M., and Kenda, K. Crop Random Forest 7.53 0.14 0.87 0.87 Classification using Perceptive Sentinel. In Proc. 21th MLP 264.67 0.07 0.81 0.81 International Multiconference (Ljubljana, Slovenia, Logistic Regression 63.50 0.01 0.67 0.65 2018), vol. C, Institut ”Jožef Stefan”, Ljubljana, Perceptron 24.05 0.01 0.45 0.38 pp. 37–40. Hoeffding Tree* 0.44 0.06 0.79 0.79 [9] Oza, N. C. Online bagging and boosting. In 2005 Bagging of HT* 3.07 0.46 0.83 0.83 IEEE international conference on systems, man and Na¨ıve Bayes* 0.18 0.15 0.64 0.62 cybernetics (2005), vol. 3, Ieee, pp. 2340–2345. Logistic Regression* 0.31 0.08 0.15 0.07 [10] Slovenian ministry of agriculture. Mkgp - Perceptron* 0.33 0.07 0.14 0.04 portal. http://rkg.gov.si/. Accessed: 2020-08-11. [11] Valero, S., Morin, D., Inglada, J., Sepulcre, G., Table 1: Comparison of models for predicting LULC Arias, M., Hagolle, O., Dedieu, G., Bontemps, classes. *Denotes incremental algorithms. S., Defourny, P., and Koetz, B. Production of a dynamic cropland mask by processing remote sensing image series at high temporal and spatial resolutions. 5. CONCLUSIONS Remote Sensing 8(1) (2016), 55. In our approach we have concentrated on effective process- [12] Čerin, M., Koprivec, F., and Kenda, K. Early ing. Our goal was to provide methods and workflows which land cover classification with Sentinel 2 satellite can reduce the need for extensive hardware and processing images and temperature data. In Proc. 22th power. Our goal was focused on use cases where a near state- International Multiconference (Ljubljana, Slovenia, of-the-art accuracy can be achieved with only a fraction of 2019), vol. C, Institut ”Jožef Stefan”, Ljubljana, the processing power required by the state-of-the-art. We pp. 45–48. have researched stream mining algorithms. We have shown [13] that these algorithms, even if they are not the most accurate Waldner, F., Canto, G. S., and Defourny, P. Automated annual cropland mapping using or the fastest, take their place at the Pareto front in a multi- knowledge-based temporal features. ISPRS Journal of target environment, which means that some users might find Photogrammetry and Remote Sensing 110 (2015). them suitable for their needs and that they provide the best [14] results for particular computational demand. Zhu, X. X., Tuia, D., Mou, L., Xia, G.-S., Zhang, L., Xu, F., and Fraundorfer, F. Deep learning in 6. ACKNOWLEDGMENTS remote sensing: A comprehensive review and list of resources. IEEE Geoscience and Remote Sensing This work was supported by the Slovenian Research Agency Magazine 5, 4 (2017), 8–36. and the ICT program of the EC under project PerceptiveSen- tinel (H2020-EO-776115) and project EnviroLENS (H2020- DT-SPACE-821918). 252 Predicting bitcoin trend change using tweets Jakob Jelencic Artificial Intelligence Laboratory Jozef Stefan Institute and Jozef International Postgraduate School Ljubljana, Slovenia jakob.jelencic@ijs.si ABSTRACT by people’s trust in it. Which means that possible up or Predicting future is hard and challenging task. Predict- down trends could be predicted by understanding sentiment ing financial derivative that one can benefit from is even of people tweets related to Bitcoin and other cryptocurrencies. more challenging. The idea of this work is to use informa- Tweets data-set is combined with classical Open-High-Low- tion contained in tweets data-set combined with standard Close [OHLC] data-set for 5 minute time periods. OHLC Open-High-Low-Close [OHLC] data-set for trend prediction data-set contain information about opening and closing price of crypto-currency Bitcoin [XBT] in time period from 2019- of given time period, its maximum and minimum price during 10-01 to 2020-05-01. A lot of emphasis is put on text prepro- observed time period and sum of volume and number of cessing, which is then followed by deep learning models and transactions made [4]. This present additional information concluded with analysis of underlying embedding. Results how the market is behaving at any given point. were not as promising as one might hope for, but they present a good starting point for future work. In financial mathematics derivatives are usually modeled with some kind of stochastic process. Most commonly some 1. INTRODUCTION form of Brownian motion is used. In theory increment in Twitter is an American microblogging and social network- Brownian motion is distributed as N (µ, Σ) independent from ing service on which users post and interact with messages previous increment. This implies that prediction of a real known as ”tweets”. Registered users can post, like, and time price change of a derivative is not possible, so the target retweet tweets, but unregistered users can only read them. goal should be changed accordingly. Instead of predicting the Users access Twitter through its website interface, through impossible, the goal of this work is to predict a change in a Short Message Service (SMS) or its mobile-device application trend. Trend is calculated with exponential moving average, software. Tweets were originally restricted to 140 characters, application of it can be observed in Figure 1. but was doubled to 280 for non-CJK languages in Novem- ber 2017. People might post a message for a wide range of Definition: Exponential moving average: reasons, such as to state someone’s mood in a moment, to n−1 advertise one’s business, to comment on current events, or X EMA(TS , n) = α · ( (1 − α)iTSn−i ), to report an accident or disaster [5]. i=0 Bitcoin is a cryptocurrency. It is a decentralized digital 2 currency without a central bank or single administrator that α = . n + 1 can be sent from user to user on the peer-to-peer bitcoin network without the need for intermediaries. Bitcoin is known for its unpredictable price movements, sometimes even to 10% on the daily basis. Bitcoin also serve as an underlying asset for various financial derivatives, which means that one can profit from knowing the future price changes. Tweets data offer a constant stream of new information about people beliefs about Bitcoin. Since Bitcoin is very volatile asset, without any real-world value, its value is mainly driven Figure 1: Example of exponential moving average 253 Figure 2: Example of working dataset. 2. DATA DESCRIPTION • Escape characters were removed. Collected tweets range from 01-10-2019 to 01-05-2020. We • Tweet was split by ” ”. have filtered tweets by crypto-related hashtags. Originally tweets contained multilingual data, but only English one • All non alphanumeric characters were removed, includ- were extracted. Data-set still resulted in more than 5 000 ing ”#”. 000 tweets over a little more than a half year period. Dealing with such big data-set has proven to be too difficult of a • All characters were converted to lower case. task. But since a lot of tweets are just pure noise, this data- • Usual stop-words were removed. set can be reduced. Idea is to extract the tweets with the largest target audience. Since the data-set contain number of tweet’s author friends and followers, we have extracted At this point data-set contain over 200000 different tokens, the tweets with maximum sum of both in a 5 minute period. which is way to sparse for so limited data-set. At this point Unfortunately, crypto world is relatively anonymous, so there empirical cumulative distribution function was calculated and is no Warren Buffet alike personalty, to whom we could gave all tokens that have less than 50 appearances were removed. extra weight. The dictionary size is now 2150. Then we concatenated the reduced tweets with 5-minute Another thing to consider is how to process numbers that OHLC data-set. Snapshot can be observed in Figure 2. appear in between text. Obviously a separate token for Column names should be pretty self-explanatory, expect for each number is not acceptable, since it would negate all the ”tw1”,”tw2”,”tw3”, which stands for metadata information work it was done so far. The following function was applied about tweets and ”ama”, which stand for current movement to process numbers. 5 more tokens were created and then of trend. Continuous features are then normalized, ”ama” is numbers from a certain interval were assigned corresponding shifted one step into the future so it forms the target variable. token. Regression task has the most success with predictions. • Small number: X < 1000. 3. TWEETS PROCESSING • Medium number: X ∈ [1000, 10000). Aim of this chapter is to focus on processing tweets. Tweets differ from regular text data, since many of them consist • Semi big number: X ∈ [10000, 100000). hyperlink, hashtags, abbreviations, grammar mistakes and so • Big number: X ∈ [100000, 1000000). on. This excludes any pre-build preprocessing tools, like the one available in deep learning library Tensorflow [1] which • Huge number: X ≥ 1000000. is used for building deep learning models. In the Figure 2 we can see an example of some tweets. The cleaning process was executed in the same order as it is stated below. For Additional masking token were assigned for missing data. each tweet the following process was executed: This wrap up dictionary, final length of dictionary is 2156. 254 Last thing in processing tweets is to handle their length. Not • Stacked LSTM layer with 128 neurons. all tweets have the same length. One idea is to take the • maximum length of all tweets, then mask the others so they Stacked LSTM layer with 128 neurons. all have the same length. Unfortunately this would take a lot • Second input layer with 64 neurons (OHLC). of unnecessary space, which is a problem. Also long tweets does not mean informative tweet. In Figure 3 is plotted the • Concatenation. empirical cumulative distribution function of tweets’ length. • Stacked dense layer with 64 neurons. • Output dense layer with 1 neuron. Loss process of benchmark model can be observed in Figure 4, while loss process of tweets model can be observed in Figure 5. Orange color represent training set, while blue validation set. It is clear that the tweets model behaved a lot worse on training set than benchmark model, but on test set it has slightly lower MSE (benchmark: 13.78, tweets: 13.74). This implies that there is a lot of reserve in fitting of the tweets model, since the difference between the train and validation loss is so big. That is good since otherwise it seems that tweets do not contribute much for prediction. It is also worth noting that tweets model took way longer to learn, around 380 epochs compared to benchmark’s model Figure 3: Histogram of tweets’ length. 40. No additional manipulation of tokens were done. It is known that tokens ”bitcoin” and ”btc” means the same, and they could be join into one token, but they are left intact and the deep learning model will decide either they are the same or not. 4. DEEP LEARNING MODELS Obvious choice for text models are recurrent neural networks, more specifically Long-Short-term-Memory [LSTM] recurrent networks [2]. They are usually combined with embedding layers, which transform singular token to vector of arbitrary size [6]. Since the task at hand is predicting the future, there is no good benchmark metric or model which could serve as a threshold for our model performance. So in order to see if the tweets can contribute anything, we have decided to build a shallow neural network of just OHLC data which would serve as a benchmark model. 80% of the data-set was taken as a training set, remaining was left out for validation. Figure 4: Loss process of benchmark model. Split was the same in both models. Both time we used Adam optimizer [3] and mean-squared error [MSE] as a loss function. Training was stopped as soon as validation loss did not improve for 10 epochs. Batch size was 256. Structure of a benchmark model: • Input dense layer with 32 neurons. • Stacked dense layer with 32 neurons. • Stacked dense layer with 32 neurons. Figure 5: Loss process of tweets model. • Output dense layer with 1 neuron. 5. ANALYSIS OF UNDERLYING EMBED- Structure of a tweets model: DING MATRIX We have extracted underlying embedding matrix from tweets • Input embedding layer of size 64 (tweets). model. Since the model tried to minimize mean-squared error 255 Figure 6: TSNE projection of embedding matrix. [MSE] of predicted trend and actual trend, the embedding 6. CONCLUSION matrix accordingly to MSE derivative. For analysis we will While the obtained model cannot be served as production use cosine similarity as a metric. If 2 words are close in model for automatic trading, it presents a nice future work the embedding matrix, this does not mean that they are opportunity. We will continue to collect tweets, and hopefully semantically similar in concept of everyday language, but with time build a more accurate data-set and with some it means that they are similar in concept of Bitcoin trend hyper-tuning of tweets models achieve improved prediction. prediction. For example if model converged perfectly, and tokens ”bitcoin” and ”eth” have cosine similarity near 1, that 7. ACKNOWLEDGMENTS would mean that they both have similar impact on Bitcoin This work was financially supported by the Slovenian Re- trend. Which is not so hard to believe since it is known that search Agency. all crypto-currencies are heavily correlated with one another. On Table 1 it can be seen cosine similarity of some of the 8. REFERENCES most common tokens in the dictionary. [1] TensorFlow. https://www.tensorflow.org/. [2] I. Goodfellow, Y. Bengio, and A. Courville. Deep Table 1: Cosine similarity pairs of most common Learning. MIT Press, 2016. tokens. http://www.deeplearningbook.org. Tokens Pair Similarity [3] D. Kingma and J. Ba. Adam: A Method for Stochastic bitcoin, crypto 0.472 Optimization. 2014. blockchain, entrepreneur 0.561 https://arxiv.org/abs/1412.6980. crypto, cryptocurrency 0.519 [4] J. J. Murphy. Technical Analysis of the Financial cryptocurrency, blockchain 0.560 Markets: A Comprehensive Guide to Trading Methods volume, social media 0.508 and Applications. New York Institute of Finance Series. ethereum, blockchain 0.557 New York Institute of Finance, 1999. [5] R. Nugroho, C. Paris, S. Nepal, J. Yang, and W. Zhao. We cannot be completely satisfied with results, but for such A survey of recent methods on deriving topics from limited data-set they are not that bad. As it is with any twitter: algorithm to evaluation. Knowledge and embedding evaluation, it comes to certain amount of subjec- Information Systems, pages 1–35, 2020. tivity what is good and what is not. [6] S. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Series in Artificial Intelligence. In order to gain the better perspective of obtained embedding Prentice Hall, Upper Saddle River, NJ, third edition, we did a T-distributed stochastic neighbor embedding projec- 2010. tion to 2 dimension and plotted 100 nearest pairs. Projection can be observed in Figure 6. 256 Large-Scale Cargo Distribution Luka Stopar, PhD Luka Bradesko, PhD Tobias Jacobs, PhD Researcher Researcher Senior Researcher Jozef Stefan Institute Jozef Stefan Institute NEC Laboratories Europe GmbH Jamova cesta 39 Jamova cesta 39 Kurfürsten-Anlage 36 1000 Ljubljana, Slovenija 1000 Ljubljana, Slovenija 69115 Heidelberg luka.stopar@ijs.si luka.bradesko@ijs.si tobias.jacobs@neclab.eu Azur Kurbašić Miha Cimperman, PhD Researcher Researcher Jozef Stefan Institute Jozef Stefan Institute Jamova cesta 39 Jamova cesta 39 1000 Ljubljana, Slovenija 1000 Ljubljana, Slovenija azurkurbasic@gmail.com miha.cimperman@ijs.si ABSTRACT generalization of TSP where multiple vehicles are available. This This study focuses on the design and development of methods for class of routing problems is notoriously hard; it not only falls into generating cargo distribution plans for large-scale logistics the class of NP-complete problems, but also in practice it cannot be networks. It uses data from three large logistics operators while solved optimally even for moderate instance sizes. focusing on cross border logistics operations using one large graph. Nevertheless, due to its practical importance, many heuristics and The approach uses a three-step methodology to first represent the approximation algorithms for the vehicle routing problem have logistic infrastructure as a graph, then partition the graph into been proposed. Bertsimas et al. propose to an integer programming smaller size regions, and finally generate cargo distribution plans based formulation of the Taxi routing problem and present a for each individual region. The initial graph representation has been heuristic based on a max-flow formulation, applied in a framework extracted from regional graphs by spectral clustering and is then which allows to serve 25,000 customers per hour. A heuristic based further used for computing the distribution plan. on neighborhood search has been presented by Kytöjoki et al. in [4] and evaluated on instances with up to 20,000 customers. A large The approach introduces methods for each of the modelling steps. number of natural-inspired optimization methods have been The proposed approach on using regionalization of large logistics applied to VRP, including genetic algorithms [7], particle swarm infrastructure for generating partial plans, enables scaling to optimization [8], and honey bees mating optimization [9]. thousands of drop-off locations. Results also show that the The particular approach of partitioning the input graph for VRP has proposed approach scales better than the state-of-the-art, while been proposed by Ruhan et al. [5]. Here k-means clustering is preserving the quality of the solution. combined with a re-balancing algorithm to obtain areas with Our methodology is suited to address the main challenge in balanced number of customers. Bent et al. study the benefits and transforming rigid large logistics infrastructure into dynamic, just- limitations of vehicle and customer based decomposition schemes in-time, and point-to-point delivery-oriented logistics operations. [6], demonstrating better performance with the latter. Keywords In this paper, we present a methodology for large-scale parcel Logistics, graph construction, vehicle routing problem, spectral distribution, by utilizing optimization methods with large graph clustering, optimization heuristics, discrete optimization. clustering. The paper is structured as follows. In Section 2, we present the technical details of the proposed methodology. We explain the algorithms and data structures used in each of the steps 1. INTRODUCTION and discuss the interfaces required to link the steps into a working The complexity of operations in the logistics sector is growing, so system. In Section 3, we demonstrate the performance of our is the level of digitalization of the industry. With data driven methodology on two real-world use cases and compare it to the logistics, dynamic optimization of basic logistics processes is at the state-of-the-art on synthetic datasets. Finally, in Section 4 we forefront of the next generation of logistics services. include key findings, summarizing the strengths and limitations of the proposed approach. Finding optimal routes for vehicles is a problem which has been studied for many decades from a theoretical and practical point of view: see [2] for a survey. The most prominent case is the Traveling Salesperson Problem (TSP), where the shortest route for visiting n locations using a single vehicle has to be determined. What is typically associated with the Vehicle Routing Problem (VRP) is a 257 2. METHODOLOGY the rate of going from 𝑖 to 𝑗 is represented in terms of the number of possible trips that the driver can make between the two locations 2.1 Overview in one hour. In this section, we present the details of the proposed methodology The algorithm works by approximating the minimal 𝑘-cut of the for large-scale cargo distribution planning. The methodology, graph, removing its edges and thus reducing the graph to 𝑘 illustrated in Figure 1, uses a three-step, divide and conquer disconnected components. We adapt a spectral partitioning approach to cargo distribution, where we reduce the size of the algorithm introduced in [10] to graphs. optimization problem by (i) abstracting the physical infrastructure into a sparse graph representation, (ii) partitioning the graph into The algorithm first symmetrizes the transition rate matrix as 𝑄𝑠 = smaller chunks (i.e. regions) and (iii) planning the distribution in 1 (𝑄 + 𝑄𝑇), to ensure real-valued eigenvalues, and computes its each region independently. This allows us to run the optimization 2 Laplacian: on large graphs while producing better local results. −1 𝐿 = 𝐼 − 𝑑𝑖𝑎𝑔(𝑄𝑠1⃗ ) 𝑄𝑠 Next, it computes the 𝑘 eigenvectors of 𝐿, corresponding to the smallest 𝑘 eigenvalues. It then discards the eigenvector corresponding to 𝜆1 = 0 and assembles eigenvectors 𝑣2, 𝑣3, … , 𝑣𝑘 corresponding to eigenvalues 𝜆2 ≤ 𝜆3 ≤ ⋯ ≤ 𝜆𝑘 as columns of matrix 𝑉. The rows of 𝑉 are then normalized and used as input to the k-means clustering algorithm which constructs the final partitions. 2.4 Vehicle Routing The vehicle routing step uses Tabu search [12] to construct the distribution plan. Starting with an initial solution, Tabu search constructs a linear search path by iteratively improving the solution in a greedy fashion until a stopping criterion is met. To avoid converging to local minima, Tabu search blacklists recent moves and/or solutions for one or more iterations using design-time rules. Figure 1: Three step methodology for logistics optimization. In each iteration, the search process generates new possible solutions by removing a node from its current route and placing it Initially, we create a representation of the physical infrastructure as after one of the other nodes in the graph, possibly on a different an abstract graph, representing each pickup and drop-off location route. To mitigate scaling problems associated with generating as a node with edges as shortest connections on road in between. 𝑂(𝑛2) possible moves in each step, the algorithm only considers a Next, we partition the abstract graph with a spectral partitioning handful of moves. Specifically, the probability of considering approach. The method is an adaptation of [10] to graphs, where we placing node 𝑖 after node 𝑗 is proportional to the inverse of the use the first k eigenvalues and eigenvectors of the graphs’ Euclidean distance 𝑑(𝑖, 𝑗) between the nodes. Laplacian to construct the partitions. In each partition, we construct Like other local search algorithms, Tabu search starts from an a distribution plan using an iterative search algorithm. From an initial feasible solution which is constructed using a construction- initial solution, the algorithm constructs a linear search path by based heuristic algorithm. The heuristic procedure iteratively changing the position of a node in the distribution plan. To avoid selects a node and places it after one of the other nodes in a way local minima, it uses design-time blacklist rules which prevent the that minimizes the travel distance. The procedure iterates until all algorithm from oscillating in a local neighborhood. Each step is values are initialized. described in more details in the following sections. 2.2 Graph Construction For graph construction, the Dijkstra SPF algorithm [11] was 3. DEMONSTRATION AND RESULTS applied to identify neighbor relationships between the nodes in the In this section, we demonstrate the effectiveness of the proposed OpenStreetMaps (OSM) dataset and construct the graph methodology on two real-world use cases and compare the representation. By mapping post offices to the closest node on methodology to the state-of-the-art in vehicle routing. The first OSM, we tag the post office nodes for SPF search. pilot included two national logistics operators, namely Hrvatska Posta (Croatia) and Posta Slovenije (Slovenia). As the main focus The search frontier is a baseline for the SPF procedure and of future logistics in Europe is to operate as one large homogenous represents the list of nodes whose graph neighbors are to be logistics infrastructure, the two infrastructures were considered as searched. The final graph is built by iterating with the SPF one logistics graph. The second pilot included Hellenic Post procedure through the list of all post offices in physical (Greece) graph representation and data. infrastructure (graph nodes), and consolidating results into final the sparse matrix – each iteration computes one row of the matrix. In initial testing, simulated data were used for modelling parcel flow with graph abstraction, graph processing, and optimization 2.3 Graph Partitioning responses. The final instances were constructed from real The partitioning step first represents the graph as a transition rate infrastructure data to test the functionalities. The results are matrix (𝑄)𝑖𝑗 = 𝑞𝑖𝑗, where 𝑞𝑖𝑗 represents the rate of going from presented in the following subsections. node 𝑖 to node 𝑗 and is computed as the inverse minimal travel time (obtained from step 1) between the two nodes. With this approach, 258 3.1 Evaluation on Large Synthetic Graphs For the experiments we used a Tabu list with a length of 5% of the We now demonstrate the scalability of the proposed methodology entities (locations) that the algorithm must check, and terminated by comparing its performance to the performance of the baseline the algorithm when there was no improvement in the solution for Tabu search algorithm on synthetic graphs of various sizes, more than 10 seconds. comparing both algorithms’ running time and the total travel time On large graphs, we see that the proposed methodology in the generated cargo distribution plan. Our results show that the significantly reduces the computation time while preserving the proposed methodology enables fast generation of distribution plans quality of the result. The proposed methodology reduces the on graphs of up to 10,000 nodes, while also improving the quality computation time on graphs larger than 5k nodes, providing a of the generated result. substantial saving of 91% on graphs with 10k nodes. We also We simulate the logistics infrastructure by generating random observe that the quality of the output slightly improved when planar graphs representing the road network and drop-off locations. applying our divide-and-conquer methodology over Tabu search. First, we generate a cluster of 𝑛 drop-off locations by sampling a The improvement ranges between 23% and 40% and is largely Gaussian distribution around 𝑘 randomly chosen locations. Next, attributed to the significantly reduced search space in the partitions we connect the locations with Delaunay triangulation [13], as compared to the entire graph. resulting in a planar graph. We compute the distance between two 3.2 Testing the instances on pilot use cases locations using the Euclidean metric and assign a 50 𝑘𝑚/ℎ speed The methods presented and tested on synthetic graphs were also limit to intra-city edges and a 90 𝑘𝑚/ℎ speed limit to inter-city tested on data from two pilot scenarios, namely Slovenian-Croatian edges. Part of a synthetic graph with 10,000 nodes is shown in post (Pošta Slovenije & Hrvatska Pošta) and Hellenic Post Figure 2 below. (Greece). In the pilot use cases, the analytical pipeline is used to process ad-hoc events in the logistics infrastructure. The ad-hoc events included were structured into three categories: new parcel request (ad-hoc order), event on distribution objects (vehicle break down) and events related to changes in border crossings – border closed (cross border event). The instances built on simulated data were loaded with OpenStreetMaps data for abstraction of real infrastructure description into graph representation, as illustrated in Figure 4. Figure 2: Representation of simulated graph with 10,000 nodes. Table 1 summarizes the computation times of the proposed method along with the quality of the generated distribution plan and compares the results to Tabu search without prior clustering. We measure the quality of the generated distribution plan as the distance travelled by all vehicles according to the plan. In each row, we show the average of 10 trials on 10 different graphs. Table 1: Comparison of efficiency of Tabu search and proposed methodology. Figure 4: A region of Posta Slovenia graph representation, using OpenStreetMap. Graph Proposed Methodology Tabu search Size A similar approach was used for the case of Hellenic Post, where the OSM data for the region of Greece were loaded into the graph Running Travel Running Travel abstraction instance. For traffic modelling of the vehicles, the Time Distance Time Distance SUMO simulator [14] was used with the regional map. For graph [km] [km] manipulations, the SIoT infrastructure was used to generate the 1000 6.07min 64.7k 0.76min 85.5k social graph when an ad-hoc event was triggered. The social graph represented all entities (vehicles, etc.) in the infrastructure that are 2000 10.07min 122.9k 2.98min 160.8k in the scope to be included in event processing. In this way, 5000 30.14min 259.2k 60.04mi 428.2k distribution objects were mapped to physical infrastructure for n loading the objects into the graph representation for further 7000 39.29min 377.9k 166.79m 577.1k optimization and distribution plan estimation in 10000 55.64min 552.2k 10.78h 845.1k 259 6. REFERENCES [1] European Commission. (2015). Fact-finding studies in support of the development of an EU strategy for freight transport logistics. Lot 1: Analysis of the EU logistics sector. [2] Kumar, Suresh Nanda, and Ramasamy Panneerselvam. "A survey on the vehicle routing problem and its variants." (2012). [3] Bertsimas, Dimitris, Patrick Jaillet, and Sébastien Martin. "Online vehicle routing: The edge of optimization in large- scale applications." Operations Research 67.1 (2019): 143- 162. Figure 4: Processing ad-hoc order on a pilot scenario, using [4] Kytöjoki, Jari, et al. "An efficient variable neighborhood SUMO simulator. search heuristic for very large scale vehicle routing problems." Computers & operations research 34.9 (2007): An example of the social graph generation and ad-hoc event 2743-2757. processing is presented in Figure 4, where a new ad-hoc request is processed by SIoT and analytical pipeline. [5] He, Ruhan, et al. "Balanced k-means algorithm for partitioning areas in large-scale vehicle routing problem." The results show that abstracting the logistics infrastructure and 2009 Third International Symposium on Intelligent clustering the graph into regional structures enabled real-time Information Technology Application. Vol. 3. IEEE, 2009. processing of complex events in the logistics infrastructure. The response time for processing an ad-hoc event in regions of between [6] Bent, Russell, and Pascal Van Hentenryck. "Spatial, 50 and 100 nodes was between 20 and 30 seconds. This is relatively temporal, and hybrid decompositions for large-scale vehicle fast compared to alternatively processing 1000 nodes or more routing with time windows." International Conference on Principles and Practice of Constraint Programming. Springer, Berlin, Heidelberg, 2010. 4. CONCLUSION [7] Razali, Noraini Mohd. "An efficient genetic algorithm for In this paper, we presented an approach for generating cargo large scale vehicle routing problem subject to precedence distribution plans on large logistic infrastructures. Our results show constraints." Procedia-Social and Behavioral Sciences 195 that the proposed approach can scale to graphs of up to 10,000 (2015): 1922-1931. nodes in practical time while preserving and even slightly [8] Marinakis, Yannis, Magdalene Marinaki, and Georgios improving the quality of the result. Dounias. "A hybrid particle swarm optimization algorithm Since the main use case of logistics is point-to-point regional for the vehicle routing problem." Engineering Applications delivery and just-in-time delivery, these new services are oriented of Artificial Intelligence 23.4 (2010): 463-472. exactly to regional logistics optimization. More importantly, the [9] Marinakis, Yannis, Magdalene Marinaki, and Georgios approach enables to process ad-hoc events, such as new parcel Dounias. "Honey bees mating optimization algorithm for the delivery requests, events related to distribution vehicles, or to vehicle routing problem." Nature inspired cooperative infrastructure. The ad-hoc event processing includes manipulating strategies for optimization (NICSO 2007). Springer, Berlin, the graph representation and running the optimization methods in Heidelberg, 2008. 139-148. real-time. Since our method clusters and regionalizes large graphs, such approach can enable real-time processing of events on large [10] Ng, Jordan, Weiss. “On Spectral Clustering: Analysis and an graphs, by limiting the changes to the affected regional parts of the algorithm”. Advances in Neural Information Processing infrastructure. Systems. MIT Press, 2001. 849-856. However, while our approach can be combined with several state- [11] Dijkstra, E. W. A note on two problems in connexion with of-the-art methods, its main drawback remains the inability to graphs. Numerische Mathematik, 1(1), 269–271, 1959 generate inter-region routes, making it suitable only for local and [12] Handbook of Combinatorial Optimization, Fred Glover, last-mile distribution plans. Future work will focus on investigating Manuel Laguna, Vol. 3, 1998 the generation of inter-region plans and connecting multiple [13] Computational Geometry: Algorithms and Applications, regions into one distribution plan. Some of the options include Mark de Berg, Otfried Cheong, Marc van Kreveld, Mark introducing border checkpoints where cargo can be handed over to Overmars, Third Edition, 2008 vehicles of neighboring regions, using dedicated inter-region “highway” channels, and using dedicated vehicles for cross-region [14] http://sumo.sourceforge.net deliveries. 5. ACKNOWLEDGEMENTS This paper is supported by European Union’s Horizon 2020 research and innovation programme under grant agreement No 769141, project COG-LO (COGnitive Logistics Operations through secure, dynamic and ad-hoc collaborative networks). 260 Amazon forest fire detection with an active learning approach Matej Čerin Klemen Kenda Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan International Jožef Stefan International Postgraduate School Postgraduate School Jamova 39, 1000 Ljubljana, Jamova 39, 1000 Ljubljana, Slovenia Slovenia matej.cerin@ijs.si klemen.kenda@ijs.si ABSTRACT ing satellite images [6, 11], they inspect changes on satellite Wildfires are a growing problem in the world. With climate images to detect fires. Our solution to that problem is to use change, the fires have a larger range an are harder to put machine learning. Because we do not have prepared labeled down. Therefore it is important to find a way to detect and data-set active learning like approach is our next candidate. monitor fires in real-time. In this paper, we explain how we can use satellite images and combine it with knowledge of Active learning is the approach used when the labeled data active learning to get accurate classifier for forest fires. To are unavailable, and labeling data is too expensive or time- build the classifier we used active learning like approach. We consuming. The algorithm starts with a small labeled data train the classifier with one labeled image. Then used a clas- set and then use its predictions to train itself again. That sifier to classify the set of images. We manually inspected way the algorithm can learn itself. Algorithms usually need the images and relabeled wrongly classified examples and additional input for some data points. In these cases, a hu- build a new classifier. In the paper, we show that in a few man should label those data, and the algorithm can then iteration steps we can get a classifier that can with good correct its predictions. The active learning approach is used accuracy identify wildfires. in many use cases (speech recognition, information extrac- tion, classification, ...). Over the years, it proved to work Keywords relatively well [8]. remote sensing, earth observation, active learning, rain for- est, wildfires, machine learning, feature selection, classifica- In this paper we use active learning like approach to clas- tion sify wildfires. By the principle of active learning approach, we label a small subset of data and then train the classi- 1. INTRODUCTION fier. Then we manually check the classification results and correct the wrongly classified examples. We then use a new In last years wildfires are a growing problem for the world. bigger data-set to train the new classifier. We continue with Each year the number of forest fires around the world grow. iterations until we are satisfied with the results. That way In recent years we had growing number of fires in Ama- we can iteratively get a good classifier without labeling huge zon, Australia, Africa and Siberia. Because of high global amounts of data. warming and high temperatures, the wildfires have a bigger range and are also harder to put out. Forest fires are par- tially responsible for the air pollution [12], loss of habitat 2. DATA for animals. Amazon rain forest is also called the lungs of 2.1 Data Acquisition the world, because of oxygen production by the trees. The In the article, we use data from ESA Sentinel-2 mission [3]. loos of forest also connects to a higher chance of floods and The sentinel-2 mission produces satellite images in 13 differ- landslides [6]. Therefore the classification and monitoring ent spectral bands with wave lengths of ligt observed from of wildfires is an important task. It is important to know approximately 440 nm to 2200 nm. The spatial resolution is the time series of the spread of the fire. With that knowl- between 10 and 60 m. It consists of two satellites that circle edge we can create models for future fire events, and to plan the earth with 180◦ phase. One point on the earth’s surface measures in case of wildfire. is visited at least once every five days. In future we could use also use some other satellite data sources like available at The satellite images are a good source for observation of www.planet.com [1]. Those data have revisit time of 1 day land type [5]. Therefore they could be used for monitoring and might be even better candidate for accurate monitoring forest fires. They can be detected on satellite images, but of wildfires. the area of Amazon is big and it would take a lot of time to manually label burned areas by forest fires. Therefore we To download data we use eo-learn library [9] that have inte- should develop an algorithm that can detect fires. grated sentinel-hub[10] library used to access satellite data. Data were downloaded for the year 2019, with a spatial res- There are already existing algorithms for fire detection us- olution of 30 m. The 30 m resolution was chosen because 261 burned areas usually extends through much bigger area than 30 m and a therefore higher resolution would not help us identify forest fires. But the processing of each image would take significantly more time than it did now. 2.2 Data Preprocessing ESA already makes most of the preprocessing steps, like atmospheric reflectance or projection [4]. Therefore data is already clean and ready for use. For our experimentation purposes, we filtered out clouds for that purpose we used models available in eo-learn library. In our experiments, we used all spectral bands, but the earth observation community developed many different in- dices that can be calculated from raw spectral bands and use them as a feature in our machine learning experiments. In- dices that we used are NDVI, SAVI, EVI, NDWI, and NBR, defined in papers [7, 2]. As our feature vector we used all 13 raw bands and mentioned indices. 3. METHODOLOGY In our experiments, we iteratively improved the classifier. In each iterative step, we looked at the images and deter- mine if the classification was good or not. To do that most successfully we plotted the images in true color, where the burned area is usually dark, and if the fire is active the smoke Figure 1: The Figure shows the true color and false- is also visible. The other figure that we checked was image color images of the same area before, during and with RGB colors plotted Sentinel-2 bands 12, 11, and 3 (false after the fire. These kinds of images can be used to color). Here most of the image is usually in shades of green. manually determine burned areas. The burned area is dark gray color and the area currently burning is yellow or orange (Figure 2). With those two im- ages, we have no problem checking if the area is burned or only images, where the classifier classified fire. That is be- not. cause we noticed that the classifier already, in the beginning, finds fire, but it picked up some other areas and objects as We experimented with two different approaches. In the first fire as well. Therefore we need to find those images and label approach, we evaluated the results of classification for each them as not fire. pixel and in the second experiment, we evaluated the aver- age result for a bigger area determined with the clustering 4. We used a false-positive set to add to data-set the pix- algorithm. els that the classifier classified wrongly and true positive examples to keep the data-set balanced. We chose in each The classifier used in our experiment was logistic regression. iteration the two values for the probability of prediction in We used it because it is quite an accurate classifier for earth logistic regression. The first value was used to determine in observation and it can assess how strong the prediction is. false-positive images to find pixels that were classified with a probability above that value to add those pixels in the data set. And the second value was used to find pixels that 3.1 Experiment 1 contained forest fire. We changed those values because the First, we manually searched the area of the Amazon forest to algorithm is unreliable in the first iterations and low value in find the first satellite image with a forest fire. Then we used the images with fire would pick up a lot of noise in the data that satellite image and labeled 270 pixels as fire area and set. But with each iteration the algorithm became more 270 pixels as not fire area. We trained the logistic regression reliable, therefore we could pick lower probability without classifier and used it as our initial classifier in our iteration. much noise. The values are shown in the Table 1. The iteration steps in our experiment were: 1. Use a classifier and classify pixels of a random images of 3.2 Experiment 2 the Amazon rain forest. The formation of the initial classifier and the first three steps in that experiment were the same as in the first experiment. 2. We took images that the classifier would classify with a forest fire. The images were classified as containing a burned Additional steps in the experiment are: area if at least 3 % of pixels on the image were classified as 4. For the evaluation of the classifier, we first made cluster- fire. ing with the K-Means algorithm to group similar pixels on each image. The idea of that step is to use a homogeneous 3. We checked those images and manually assigned them group of pixels that probably represent the same ground into two sets (true-positive and false-positive). We checked cower. Those steps are useful because we noticed that K- 262 Iteration FP TP F1 score Iteration 1 0.0 0.80 Classifier from Experiment Iteration 2 0.4 0.70 1 predicting on data-set 0.81 Iteration 3 0.4 0.70 from Experiment 2 Iteration 4 0.5 0.60 Classifier from Experiment Iteration 5 0.5 0.60 2 predicting on data-set 0.78 Iteration 6 0.5 0.50 from Experiment 1 Table 1: The table shows the values of the minimum average probability of a pixel being burned area for Table 3: The F1 scores of classifiers. false-positive images (FP) and true-positive images (TP). higher than they would be on real images. In both exper- iments we used random images from the area of amazon, therefore some images might be in both training and testing Means usually grouped fire areas in one or two clusters. We set. clustered the pixels in 6 clusters. That number was chosen because on most images that number split the area that way Figure 3 depicts a time-lapse of a wildfire progress. We can that clusters with fire were separated from not burned area. see that there are some small noise pixels that are classified At the same time it did not split same ground types on too wrongly, but they are relatively rare. many clusters. Figure 2: The figure shows how clustering groups different pixels. The burned area is all in one cluster. 5. Calculate the average probability of pixel representing forest fire for each cluster. 6. To choose what pixels to add in the data-set we once again determined two values. They defined above what average pixel probability should cluster have to add pixels from that cluster in the data set. The used values for each iteration are presented in Table 2. Iteration FP TP Iteration 1 - 0.75 Iteration 2 0.5 0.75 Figure 3: The sub-figures show the development of Iteration 3 0.5 0.60 forest fire. On the left, we have true color satellite Iteration 4 0.5 0.60 images and on the right, we have the classification Iteration 5 0.5 0.60 result with our algorithm. yellow color depicts the Iteration 6 0.5 0.5 burned area. Table 2: The table shows the values of minimum Another interesting thing to observe in our experiments is average probability in the cluster for false-positive what the classifier learned and how it improved in each it- images (FP) and true-positive images (TP). eration. We noticed that in the first iterations of our exper- iments, the classifier did already find fire, but it also picked up many other areas as fire. One of the first improvements of 4. RESULTS the classifier was that it did not classify water areas (rivers We tested the classifiers from each experiment on data set and lakes) as fire. The other later improvements classifier form the other experiment. To evaluate results we calculated were also some rocky areas. It also improved significantly in F1 scores. The results are shown in Table 3. the agricultural areas, but in some cases, we could not train classifiers that there is no fire. The F1 scores are relatively high, but those data sets were constructed in a similar way, therefore the scores might be The classifier learned wrongly and we could not remove com- 263 pletely some agricultural areas and some roads in the cities. [2] Bannari Abdou et al. “A review of vegetation indices”. Most of the agricultural areas were classified correctly, but In: Remote Sensing Reviews 13 (Jan. 1996), pp. 95– there were present some fields that no matter what we did 120. doi: 10.1080/02757259509532298. were not classified correctly. This might be due to the fact [3] ESA. https://www.esa.int/Our_Activities/Observing_ that the field might be on the place that was previously the _ Earth / Copernicus / Sentinel - 2 / Satellite _ burned and the algorithm still pick that up even though it constellation. Accessed 13 August 2018. was not visible from the imagery to us. [4] ESA. https : / / sentinel . esa . int / web / sentinel / 5. CONCLUSIONS user-guides/sentinel-2-msi/processing-levels/ level-2. Accessed 13 August 2018. The approach with active learning seems promising and we can get relatively good classifiers in a short time. That way [5] Filip Koprivec, Matej Čerin, and Klemen Kenda. “Crop we could train a classifier for any classification task of satel- classification using PerceptiveSentinel”. In: (Oct. 2018). lite images. With that approach we do not need to check all [6] Rosa Lasaponara, Biagio Tucci, and Luciana Gher- images as we would if we would like to label all the data by mandi. “On the Use of Satellite Sentinel 2 Data for hand. In the end, we get a relatively good classifier. Automatic Mapping of Burnt Areas and Burn Sever- ity”. In: Sustainability 10 (Oct. 2018), p. 3889. doi: In this paper, we showed that it is possible in a relatively 10.3390/su10113889. small number of iterations to get a good and reliable clas- [7] David Roy, Luigi Boschetti, and S.N. Trigg. “Remote sifier of forest fires. Because satellite images are more ac- Sensing of Fire Severity: Assessing the Performance cessible in last years than previously it could give us almost of the Normalized Burn Ratio”. In: Geoscience and real-time insight in the Amazon rain forest. Remote Sensing Letters, IEEE 3 (Feb. 2006), pp. 112– 116. doi: 10.1109/LGRS.2005.858485. In the feature one could use other satellite sources with bet- ter time-resolution to monitor wildfires. That way we could [8] Burr Settles. “Active Learning Literature Survey”. In: get more accurate view on the spread of fires. (July 2010). [9] Sinergise. https://github.com/sentinel- hub/eo- 6. ACKNOWLEDGMENTS learn. Accessed 23 August 2019. This work was supported by the Slovenian Research Agency [10] Sinergise. https://github.com/sentinel-hub/sentinelhub-and the ICT program of the EC under projects enviroLENS py. Accessed 14 August 2018. (H2020-DT-SPACE-821918) and PerceptiveSentinel (H2020- [11] Mihai Tanase et al. “Burned Area Detection and Map- EO-776115). The authors would like to thank Sinergise for ping: Intercomparison of Sentinel-1 and Sentinel-2 Based their contribution to EO-learn library along with all help Algorithms over Tropical Africa”. In: Remote Sensing with data analysis. 12 (Jan. 2020), p. 334. doi: 10.3390/rs12020334. References [12] G. R. van der Werf et al. “Global fire emissions es- timates during 1997–2016”. In: Earth System Science [1] https : / / www . planet . com/. Accessed 1 September Data 9.2 (2017), pp. 697–720. 2020 . doi: 10 . 5194 / essd - 9- 697- 2017. url: https://essd.copernicus.org/ articles/9/697/2017/. 264 Zbornik 23. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2020 Zvezek D Proceedings of the 23rd International Multiconference INFORMATION SOCIETY – IS 2020 Volume D Etika in stroka Professional Ethics Uredili / Edited by Franci Pivec, Marjan Krisper, Matjaž Gams http://is.ijs.si 7. oktober 2020 / 7 October 2020 Ljubljana, Slovenia 265 266 PREDGOVOR Konferenca »Etika in stroka« je namenjena etiki v času informacijske družbe. Po Rushworth Kidderju je etika "znanost o idealnem človeškem značaju" oziroma "znanost o moralni dolžnosti". Richard William Paul in Linda Elder definirata etiko kot "nabor konceptov in principov, ki nas vodijo glede primernega in neprimernega obnašanja". V času informacijske družbe je vtis, da se stare norme podirajo, da je osnova uspešnega političnega delovanja čim bolj uspešno zavajanje množic preko socialnih omrežij in pristranskih medijev. Tudi množice ljudi na socialnih omrežjih ne kažejo čedalje bolj civiliziranega obraza. Kot da resnica, moralnost, etika ne bi več obstajali, oziroma so nepomembni. Posebej se to kaže v odnosu do znanosti oziroma dejstev oz. resnice. Ali je cepljenje škodljivo ali koristno? Ali lahko nasprotniki cepljenja nekaznovano povzročajo škodo svojim otrokom in otrokom drugih? Ali je omejevanje resnice s strani tehnoloških gigantov kot Google ali Facebook omejevanje svobode, ali pa gre za omejevanje hujskanja množic in sovražnega govora? Zanimive teme za prispevke so naslednje: Etični kodeksi v računalništvu/informatiki, občutljivost univerzalne (filozofske) etike za digitalni svet, etična odgovornost IT strokovnjakov, IT v službi zavajanja, etika v e-trgovanju, etika digitalnega sodišča, etičnost Googla in Facebooka, avtentičnost e-dokumentov v arhivih, etika in umetna inteligenca, etika v robotiki. Poseben poudarek je na aktualni temi: Etične smernice za zaupanja vredno Umetno inteligenco, na podlagi dokumenta Evropske komisije Ethics Guidlines for Trustworty AI, ki zajema ključna etična vprašanja informacijske družbe. Drugo leto konference smo zbrali sedem zanimivih prispevkov. Ne ravno veliko število je najbrž posledica korone, bomo videli, kaj bo naslednje leto. Franci Pivec, Marjan Krisper 267 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Janez Malačič, predsednik Matjaž Gams, organizator Drago Čepar Christian Gostečnik Majda Černič Istenič Boštjan Kerbler Karin Kasesnik Dušan Kidrič Marko Krevs Tomaž Merše, Mari Osredkar Janja Pečar Janja Povhe Jože Ramovš Jože Sambt Milivoja Šircelj Petronela Vertot Božidar Voljč 268 Should Algorithms Replace Teachers and Lecturers? Naj algoritmi nadomestijo učitelje in predavatelje? Dr. Tomaž Grušovnik Univerza na Primorskem Pedagoška fakulteta in Slovensko filozofsko društvo ABSTRACT POVZETEK Recent COVID-19 crisis had many consequences and Nedavna kriza COVID-19 je imela veliko posledic, pri education was one of the fields that was profoundly čemer je bilo izobraževanje med tistimi področji, ki se jih influenced and modified by the pandemic. Because of the je pandemija najgloblje dotaknila in jih spremenila. Zaradi social distancing new methods had to be applied, including družbenega distanciranja smo morali uporabiti nove distance and e-learning. These changes emphasized the metode, vključujoč poučevanje na daljavo in e- importance of new approaches in education, including the poučevanje. Te spremembe so poudarile pomembnost use of software that can personalize education and novih pristopov v izobraževanju, vključujoč zamenjavo differentiate instruction instead of human teachers. Not učiteljev s programi, ki lahko izobraževanje prilagodijo only could algorithms and robot teachers provide cheaper posamezniku in diferenciirajo poučevanje. Ne le, da lahko instruction for far bigger numbers of students, they also algoritmi in robotski učitelji nudijo cenejše izobraževanje seem to be less biased and more objective than humans. veliko večjemu številu učencev, zdi se tudi, da so manj However, with such steps education seems to be getting pristranski in bolj objektivni od ljudi. A po drugi strani se more and more individual and automated, thereby losing vendarle zdi, da izobraževanje s takšnimi koraki postaja one of its main traditional aims: the formation and čedalje bolj individualizirano, s čemer se izgublja eden nurturing of learning or academic community. njegovih tradicionalnih ciljev: ustvarjanje in negovanje učeče se oziroma akademske skupnosti. KEY-WORDS KLJUČNE BESEDE education, ethics, e-learning, robot teachers, artificial intelligence in education izobraževanje, etika, robotski učitelji, umetna inteligenca v izobraževanju 269 Humanist med informatiki: Jacques Berleur 1938 - 2020 Humanist among informaticists Franci Pivec IZUM Maribor Maribor, Slovenija franci.pivec@ext.izum.si POVZETEK razmerja med računalništvom in družbo in je že s prvo podelitvijo zgovorno demonstrirala svoje kriterije – prejel jo je Umrl je Jacques Berleur, inženir, filozof in teolog, ki je med Joseph Weizenbaum. prvimi opozoril na družbene in etične razsežnosti računalništva. To je raziskoval, o tem je pisal knjige, predvsem pa je organiziral 2 DRUŽBENA INFORMATIKA strokovno javnost informatikov v okviru mednarodnih organizacij, še posebej IFIP in UNESCO. Posebej se je posvečal Kdo je Jacques Berleur? Rojen v Namuru, kulturnem središču etičnim kodeksom v informatiki, ki so vse bolj potrebni, valonske Belgije, je diplomiral iz gradbeništva na Univerzi saj je stroka globoko vmešana v problematične pojave ogrožanja Louvain. Takoj za tem pa je v Fourviéru pri Lyonu vstopil v zasebnosti, nadzorovanja, širjenja laži in man jezuitski red, doštudiral teologijo in filozofijo ter bil 1971. ipuliranja javnosti. S temi temami je bil Berleur osebno in s članki prisoten tudi v ordiniran za duhovnika. V tistem času je papež Pavel VI. objavil Sloveniji. Apostolsko spodbudo, v kateri je opredeljen tudi odnos cerkve do nove informacijske tehnologije: »Cerkev bi se čutila krivo KLJUČNE BESEDE pred svojim Gospodom, če teh mogočnih sredstev, ki jih človeški razum vsak dan bolj spopolnjuje, ne bi izrabila« (Pavel VI., Jacques Berleur, IFIP, družbena informatika, etični kodeksi 1976). Vrnil se je v rojstni kraj in postal predavatelj meta- informatike, filozofije in religiologije na Facultés Universitaires ABSTRACT Notre Dame de la Paix (FUNDP), kjer je ostal do upokojitve leta Engineer, philosopher and theologist Jacques Berleur has died. 2003. Devet let je bil rektor in je v univerzitetnih krogih po svetu He was among the first to bring attention to the societal and užival nesporen ugled (koordinator jezuitskih univerz), v ethical dimensions of computer science, which was the topic of domačem mestu pa veliko priljubljenost. S kolegom na univerzi his research and his books, but mostly he organised the Gérardom Fourezom, teoretičnim fizikom in matematikom, sicer professional public of IT specialists within international pa prav tako jezuitom, sta osnovala raziskovalno področje organisations, mainly IFIP and UNESCO. Berleur was especially »informatika in družba« in pred pol stoletja postavila malo dealing with ethical codes in in information science, which are univerzo Namur v središče obravnav etičnosti novih tehnologij. getting increasingly necessary as the IT profession is deeply Razvila sta metodologijo za ocenjevanje tehnoloških inovacij in involved in the problematic occurences of privacy threats, v tej luči opredelila izpostavljeno vlogo univerz, ki morajo po surveillance, spreading lies and manipulation of the public. definiciji biti neodvisne (Berleur, Fourez, 1991). Through these topics, Berleur was also present in Slovenia, both V Sloveniji je bil Berleur nekajkrat in je poznal Goriško, in person and through his articles Ljubljano, v Mariboru pa je bil celo večkrat in je prejemnik mestnega pečata. Pod njegovim mentorstvom smo leta 2006. v KEYWORDS so-organizaciji IFIP/TC9 ter SDI in IZUM izvedli HCC7 iz serije svetovnih konferenc, ki velja za prelomno glede Jacques Berleur, IFIP, social informatics, code of ethics uveljavitve »družbene informatike« (Berleur, Nurminen, 1 UVOD Impagliazzo, 2006). Potrjena je bila definicija Roba Klinga, preminulega med pripravami na konferenco, ki mu je bila nato Letošnja že štirinajsta mednarodna konferenca Human Choice tudi posvečena: »Družbena informatika je interdisciplinarni and Computers (www.hcc14.net), ki so jo tokijski organizatorji študij dizajniranja, uporabe in posledic informacijske zaradi COVID-19 odpovedali, bi se morala začeti s posvetilom tehnologije, upoštevaje njeno interakcijo z institucionalnim in aprila preminulemu Jacquesu Berleurju. On je namreč pred kulturnim kontekstom« (Kling, 1999). Že pred konferenco smo skoraj štiridesetimi leti v IFIP (Mednarodni zvezi za obdelavo objavljali Berleurjeve članke in intervjuje (Berleur, 2003, 2005). informacij) spodbudil poglobljeno obravnavo razmerja med Sam sem ga prvič srečal na dunajski konferenci Knowright-95 računalniško tehnologijo ter človekom oz. družbo. Potrebo po (Pivec, 1995), ko me je prijazno nagovoril kot »nov obraz« in me tem je sicer utemeljil že desetletje prej takratni predsednik IFIP za poldrugo desetletje angažiral kot predstavnika Slovenskega Hans Zemanek (v rani mladosti Domžalčan), ki je na Svetovnem društva Informatika v TC9 ter v skupini za informacijsko etiko. računalniškem kongresu leta 1971 v Ljubljani (!) uspel z ustanovitvijo Tehničnega komiteja 9, namenjenega 3 ETIČNI KODEKSI obravnavanju »netehničnih« vidikov računalništva. Znotraj Berleurjeva rdeča nit v IFIP so bili etični kodeksi komiteja je Berleur leta 1977 sooblikoval delovno skupino (WG 9.2) »Družbena odgovornost in računalništvo«, ki jo je mnogo računalništva( Berleur, 1996, 2004). V novi in naglo rastoči let tudi vodil. Kasneje pa je ustanovil še posebno interesno stroki, ki je posegla v vsa področja življenja, je bilo veliko skupino (SIG 9.2.2) posvečeno »Etiki računalništva«. Njegova nevarnosti za napačne presoje, a tudi za namerne manipulacije. Pravna regulacija ni dohitevala tehničnega razvoja in v takih zamisel je tudi Namur Award, ki je namenjena raziskovalcem 270 situacijah so odločilne moralne odločitve in etično vedenje samih (Goujon in drugi, 2007), ki jo je Penny Duquenoy sklenila z raziskovalcev in razvijalcev. Družbeni razvoj vse bolj očitno naslednjimi besedami: »To je testament o delovanju Jacquesa poganjajo informacije na podoben način, kot ga je doslej Berleurja, ki zajema raznolike, poučne, prodorne in intelektualno poganjala nafta. Vemo, da je nafta tudi onesnaževala svet, tako v spodbudne tekste, navezujoče se na njegovo delo in ugled. Prav neposrednem kot v prenesenem pomenu. Se lahko to dogaja tudi nič presenetljivega ni v tem, ker je to najmanj, kar zasluži za z novim »energentom« – informacijami? V sedemdesetih je bilo njegovo neutrudno prizadevanje, pripadnost »stvari«, enkratnost, to še hipotetično vprašanje, kar danes ni več: tudi uporaba humor, toploto in ne nazadnje tudi gostoljubje, ki smo ga vedno informacij sproža vojne, povzroča neenakosti, omogoča deležni v njegovem Namuru. Hvala Jacques, vsem nam je veliko velikanske goljufije, uničuje okolje, manipulira demokratične zadovoljstvo, da delamo s teboj«. Dodajam, da je nedvomno med volitve, krati svobodo posameznikom in skupnostim itd.. Etični tistimi, ki so tudi v Sloveniji spodbudili etično raziskovanje kodeksi niso celovita rešitev, vendar so pomembni, ker prebujajo računalništva in informatike in je vredno, da se ga spominjamo. moralno vest in legitimirajo razkrivanje »informacijskega zla«, npr. dejanja »žvižgačev«. REFERENCE [1] Berleur, J., Fourez, G. (1991) Méthodoloie du Technology Assessment 4 SKLEP ESST – relations sciences – technologie - société . Namur: Centre de recherche information, droit et societe, Universite de Namur V družbi, gnani z informacijami, je ločevanje tehnološkega in [2] Berleur, J., Brunnstein, K. (ur.) (1996) Ethics of Computing: Codes, družbenega razvoja nedopustno tveganje. Slavljeni 3K – Soaces for Discussion and Laww. London: Chapman&Hall [3] Berleur, J. (2003) Poklicna deontologija, samo-urejanje in etika v kompjuterizacija, kontrola, komunikacija – so proti informacijski družbi. Organizacija znanja, 8 (4), 166-174 pričakovanjem neznansko otežili humanistično držo, ker je v [4] Berleur, J., Duquenoy, P., Holvast, J., Jones, M., Kimppa, K., Sizer, R., Witehouse, D. (2004) Criteria and Procedures for Developing Codes of poplavi informacij težko obvarovati resnico, ki je osnova Ethics or of Conduct. Laxenburg: IFIP Press humanosti. Prevlada laži, čemur brez dvoma botruje [5] Berleur, J. (2005) Usmeritve EU glede IKT: od informacijske družbe do informacijska tehnologija, je največja grožnja človeštvu. eEvrope. Organizacija znanja, 10 (3), 130-146 [6] Berleur, J., Nurminen, M., Impagliazzo, J. (2006) Social Informatics: An Kritično mišljenje še nikoli ni bilo v tako globoki krizi kot danes, Information Society for All? (Proceedings of the Seventh International v preizkusni fazi pa je že vmesnik za povezovanje dvojih ali Conference Human Choice and Computers (HCC7), IFIP/TC9, Maribor, Sept. 21-23, 2006. Boston: Springer/IFIP mnogih možganov, kar mora spodnesti naše sebstvo – kdo sploh [7] Bordat, J. (2020) Denken oder Rechnen? Die Tagespost, 12. junij 2020, smo (Hongladarom, 2015). Obramba zasebnosti je zato mnogo str. 25 več kot le pravno vprašanje. Marvin Misky, sicer »oče« izraza [8] Goujon, P., Lavelle, S., Duquenoy, P., Kimppa, K., Laurent, V. (2007) The Information Society: Innovation, Legitimacy, Ethics and Democracy In umetna inteligenca, se je leta 1970 proslavil z napovedjo, da bo Honor of Professor Jacques Berleur s.j. Boston: Springer/IFIP v treh do osmih naslednjih letih že na voljo računalnik s poprečno [9] Hongladarom, S. (2015) Brain-brain integration in 2035: metaphysical and ethical implication. Journal of Information, Communication and Ethics. inteligenco človeka, ki bo znal brati in razumeti ter čutiti 13 (3/4) 205-217 http://dx.doi.org/10.1108/JICES-10-2014-0042 Shakespeara. Seveda doslej ni niti računalnika, ki bi prestal [10] Kling, Rob (1999) What is Social informatics and why does it matter? D- Lib Magazine, 5 (1) 1-22 Turingov test »Igra imitacije« iz leta 1950(Bordat, 2020), kaj šele, [11] Pavel VI. (1976) Apostolska spodbuda o evangelizaciji. Ljubljana: da bi zmogel čutiti in fantazirati. Zgodilo pa se je nekaj drugega, Družina [12] Pivec, F. (1995) Copyright v elektronski informacijski industriji. Razgledi kar je Berleura bolj skrbelo – ljudje so nehali brati in se 20 (1995), 18-19 navdihovati nad umetnostjo! Ob Berleurjevi sedemdesetletnici so sodelavci v njegovem Namuru organizirali konferenco in mu posvetli publikacijo 271 ETIKA IN MEDIJI Etika in mediji Matjaž Gams Institut “Jožef Stefan” Jamova 39 1000 Ljubljana Slovenija Matjaz.gams@ijs.si ABSTRACT V prispevku je analizirana etika svetovnih in slovenskih medijev • Mediji so ključni za dobro delovanje demokracije: tako predvsem na konkretnem primeru pisanja o Melaniji Trump in meni 84% Američanov; 49% pravi, da so mediji ključni in požigu krščanskih cerkev. Vira za ameriške medije sta predvsem 35%, da so zelo pomembni. CNN in Fox, za Slovenijo pa večinski mediji. Če so pisanja • Skoraj polovica vseh Američanov (49%) je v vprašalnikih objektivna v časopisih, ki se proglašajo za vsaj približno označila, da so mediji zelo pristranski (angleško: very biased). 56% Američanov ocenjuje, da so njihovi viri (tisti, sredinska in objektivna, potem mora biti število negativnih in ki jih uporabljajo) pristranski, 70% jih je zaskrbljenih zaradi pozitivnih mnenj o posamezni temi uravnoteženo, hkrati pa se tega. 8% jih meni, da skušajo mediji upravljati državo in so morajo pisanja o tej temi pojavljati proporcionalno pomembnosti zato mediji postali škodljivi – to mnenje večinsko zastopajo tematike. Opažena razlika sproža razne možne interpretacije, po republikanci, ki zastopajo desničarske poglede. vsem sodeč pa gre za polarizacijo medijev in prehod iz medijev • Američani večinsko menijo, da postajajo mediji v propagandna glasila. Prodor ideologije v medije je očiten, propagandna glasila. 74% jih meni, da pisanje medijev razlaga razlogov je zapletena. usmerjajo lastniki, 5% več kot leta 2017. Mnenja so, da so pristranska poročanja namenska, pri čemer jih 54% verjame, KEYWORDS / KLJUČNE BESEDE da prostrano prikazujejo dejstva, medtem ko jih 28% verjame, da si novinarji v celoti izmišljujejo lažne novice Etika in mediji, Etics and media (angleško fake news). • Nezaupanje v medije je večje v desno usmerjenem delu populacije. 75% republikansko usmerjenih ima negativno ABSTRACT mnenje o vlogi medijev v ameriški družbi in 61% jih The article analyzes the ethics of the world and Slovenian media, opravičuje napade na medije (predvsem s strani ameriškega especially on the concrete case of writing about Melania Trump predsednika). Nasprotno pa samo 22% demokratsko and the burning of Christian churches. The source for the oziroma levo usmerjenih Američanov slabo misli o medijih American media is mainly CNN in Fox, for Slovenia the majority in 70% jih pravi, da so napadi na medije neupravičeni. media. If such writing is objective, then the number of negative and positive opinions on a particular topic should be balanced, Kot pravi Sam Gill, vodja anketiranja pri Knightu: “Večina and at the same time writing on this topic should appear relative Američanov je izgubila zaupanje v medije v smislu objektivnosti to the importance of the topics. The observed difference triggers poročanja, kar je uničujoče za našo demokracijo.” various possible interpretations, and apparently is a matter of polarization of the media and the transition from the media to the 1.2. Razširjanje mitov in neresnic propaganda bulletins. The penetration of ideology into the media Nezaupanje v medije je povezano z nezaupanje celo v nesporna is obvious, hutring the democracy, while the explanation of the znanstvena dejstva, pojavlja se čedalje več posameznikov in reasons is complicated. združenj, ki zagovarjajo mite kot ploščato Zemljo, da Američani niso pristali na Luni, da kajenje ne škodi, da so koronavirus 1 UVOD vpeljale multinacionalke z namenom cepljenja in čipiranja V tem prispevku se ukvarjamo z etiko [1][2] medijev v smislu, ljudskih mas, da cepljenje škodi – da je več mrtvih zaradi ali tisti mediji, ki zase trdijo, da so objektivni, tudi v resnici cepljenja kot zaradi bolezni (korekten opis je tule: uravnoteženo, objektivno in korektno poročajo o ideoloških in https://en.wikipedia.org/wiki/Vaccine_hesitancy). Te trditve politično vročih temah. Pregledali bomo nekaj konkretnih tem in najdemo tako v svetovnih kot slovenskih analizah, z njimi se analizirali poročanje predvsem v slovenskih medijih. srečujemo v pogovoru s kolegi in znanci. Kako so take trditve našle pot med ljudi in se čedalje bolj razširjajo, je težko 1.1. Anketa o medijih v ZDA razložljivo, saj lahko vsakdo opazi, kako ladja začne izginjati iz Po anketi Gallup/Knight poll v letu 2020 z naslovom “American vidnega polja, ko se oddalji po vodni površini, oz. vsakdo lahko Views 2020: Trust, Media and Democracy,” [3], ki je zbrala poišče zgodovinske vire, kako je zaradi bolezni črnih koz umrlo ankete 20,000 Američanov (dosegljiva na kf.org/usviews20), so 300-500 milijonov ljudi mnenja naslednja: ( https://en.wikipedia.org/wiki/Vaccine_hesitancy). Če bi slike 272 umrlih zaradi črnih koz postavili v vrsto, bi obkrožili naš planet. Melanijo Knavs, s čimer je prvič v zgodovini prva dama ZDA Šele s cepivi je človeštvo izkoreninilo bolezen leta 1979. Zato postala Slovenka. Melanija Trump je tako po Louisi Adams, ženi World Health Organisation anti-cepilce postavlja med 10 predsednika Johna Quincya Adamsa, šele druga prva dama, ki je največjih zdravstvenih nevarnosti sedanjosti – z drugimi rojena izven ZDA.1 besedami: če bi te ideje našle pot do realizacije preko politikov, Vloga prve dame ni opisana v ameriški ustavi, je pa sestavni bi posredno povzročile milijone mrtvih vsako leto. Verjeti v del predsednikovega kabineta že od ustanovitve ZDA leta 1776. ploščato zemljo najbrž ni pretirano škodljivo, vsaj neposredno, Prva dama opravlja naloge, kot so: javna osebnost, predsedniška pomeni pa zanikanje osnovnega človeškega znanja in predstavnica, glas ženske populacije, upravnica Bele hiše, poneumljanje ljudi in eno izmed poslanstev avtorja je prenašati udeleženka volilnih kampanj, gostiteljica državnih srečanj in znanje v javnost [4][5]. Prenehanje cepljenja pa pomeni reda zagovornica družbeno najšibkejših.2 Zanimivost funkcije je tudi velikosti milijonov mrtvih vsako leto zaradi povečanega pojava ta, da si vsaka aktualna prva dama izbere področje, na katerem nalezljivih bolezni. bo aktivno sodelovala in ki praviloma ni politično opredeljeno. V resnici znanost še naprej na večini področij dosega odlične Tudi aktualna prva dama se je podala po poti svojih predhodnic. rezultate, čeprav je tudi tu očiten prodor ideologije zlasti v Sodeluje v šestih dobrodelnih aktivnostih, je ambasadorka raznovrstne družboslovne vede. V naravoslovju in inženirstvu pa ameriškega Rdečega križa, podpira zdravo življenje in gibanje, je na osnovi anonimnega recenziranja vsaj v kvalitetnih revijah recimo kolesarstvo, podpira ženske aktivnosti in sodeluje pri in na kvalitetnih konferencah praktično nemogoče objaviti izboru Ženske leta v ZDA. Posebno pozornost namenja ideološko obarvane polresnice ali neresnice. Zato je toliko ameriškim veteranom z različnimi poškodbami, bori se tudi proti pomembneje iz prave znanosti in izmed pravih znanstvenikov zlorabam otrok. Med drugim je zaslužna za nastanek pobude, ki izločati tiste, ki dajejo ideologiji prednost pred stroko. je nastala v sklopu akcije oziroma iniciative »Be Best«, ki se Prodori v resno znanost so redki in kratkotrajni, zaskrbljuje osredotoča predvsem na nekaj ključnih problemov otrok, s pa prefinjenost in sofisticiranost tovrstnih podtikanj v zadnjem ciljem, da se otrokom omogoči primerne pogoje za razvoj, se jih času, kar jasno kaže, da so tudi strokovnjaki postali žrtev nauči pomena socialnega, čustvenega in fizičnega zdravja ter se ideologije. Recimo v najboljši medicinski reviji na svetu, The jih spodbuja, da postanejo čim boljši ljudje. Iniciativa »Be Best« Lancet, so leta 2020 objavili prispevek, da so antimalarijska se osredotoča na tri glavne stebre: dobro počutje otrok, spletno zdravila kot hydroxychloroquine škodljiva [6]. Povezava s varnost, ki vključuje boj proti zlorabam otrok po spletu, in politiko in ideologijo je v tem, da je ameriški predsednik Donald škodljivo uporabo mamil in opioidov.3 Melanija Trump svojo Trump po televiziji večkrat propagiral koristnost tega zdravila na pozornost in energijo usmerja v neideološke in nepolitične teme, osnovi preliminarnih francoskih študij [7], ki so bile objavljene predvsem si prizadeva za boljše odnose med ljudmi, za manj z opozorilom, da gre za prve študije. Prispevek o škodljivosti nasilja, manj zlorab, za zdravo življenje, za manj mamil in, kot hydroxychloroquine v Lancetu pa je namerna potvorba z omenjeno, predvsem za dobro šibkejših, kot so otroci. ideološko motivacijo, saj poroča o izjemno velikem številu Promocija domovine prve dame vsekakor pripomore k pacientov, nespornih rezultatih in ostalimi pokazatelji obsežne prepoznavnosti Republike Slovenije in lokalne skupnosti. študije. Ponaredek je tako kvaliteten, da recenzenti niso mogli Predvsem občina Sevnica kot kraj, kjer je bila Melanija Trump opaziti goljufij, dokler ni po objavi prišlo do poglobljenih analiz rojena in kjer je odraščala, je prvi dami posvetila veliko podatkov in virov – recimo podjetje je imelo zaposlene, ki so pozornosti 4 . Aktualno promocijo prve dame je po naročilu med drugim delali v erotičnih storitvah, nekatere relacije so bile ameriškega investitorja in umetnika apliciral tudi domačin, ki je napačne, nihče ni imel informacij o testirancih z imenom in leta 2019 v Rožnem, ki sicer sodi v občino Krško, v njeno čast iz priimkom – kljub varovanju podatkov pa je potrebno včasih kosa lesa izdelal leseno skulpturo v naravni velikosti. Na žalost dopustiti možnost preverjanja. pa je lesena skulptura zdržala le dobro leto, saj so jo v začetku Če smo prišli tako daleč, da potvarjajo celo najboljše julija 2020 neznani storilci zažgali in tako poškodovali, da jo je znanstvene objave, če določeni načelno objektivni poklici bilo treba odstraniti. Požig lesene skulpture so povzeli tako izgubljajo verodostojnost in postajajo naklonjeni eni ali drugi domači kot tuji mediji 5 , pri čemer je treba poudariti, da je politični opciji (celo nekateri znanstveniki objavljajo in celo uničevanje skulptur in kipov, ki je v zadnjem času prisotno tako nekateri sodniki sodijo po svojih ideoloških pogledih), potem so v ZDA kot Evropi, sprto z normami visoke stopnje civiliziranosti tovrstni pojavi v medijih najbrž pričakovani in toliko bolj in kulture. pogosti. Poleg dejstva, da je Melanija Trump med bolj znanimi Slovenkami vseh časov, je treba omeniti tudi, da nekateri 2 MELANIJA TRUMP svetovni in slovenski mediji o njej pogosto objavljajo kritične V pobudi na Državnem svetu, da se postavi spomenik Melaniji prispevke, ki bi se jih lahko interpretiralo kot ideološko- Trump kot odgovor na požig njenega spomenika [5,8], je politične, lahko pa tudi kot diskriminacijo žensk ali seksizem, kar napisana naslednja vsebina: Donald John Trump je na volitvah je nesprejemljivo. Zato bi z obuditvijo ideje o postavitvi njenega 8. 11. 2016 postal 45. predsednik ZDA. Od 2005 je poročen z kipa jasno pokazali, da je slovenska družba civilizirana, kulturna, strpna, dobronamerna in da ceni dosežke sonarodnjakov, ne 1 Louisa Adams je bila rojena 12. 2. 1775 v Londonu. predstavljata-sevnico-svetu.html in https://www.delo.si/novice/slovenija/ko- 2 Shah, S. First ladies in the press: analysis of New York Times coverage of prva-dama-zda-postane-pravi-posel-tudi-ali-predvsem-za-sevnico- Hillary Clinton, Laura Bush and Michelle Obama, 2015, str. 3 in 4. 73955.html, 27. 7. 2020. 3 Be Best, First Lady Melania Trumpś Initiative, dostopno na URL: 5 Požig lesene skulpture Melanije so povzeli vsi večji svetovni mediji kot so: https://www.whitehouse.gov/bebest/, 4. 8. 2020 NYTimes, CNN, BBC, TheGuardian, Reuters. 4 Več o promociji Melanije Trump in občine Sevnica dostopno na URL: https://www.delo.si/nedelo/torta-melanija-in-predsedniski-hamburger- 273 glede na področje njihovega delovanja. Ustrezno priznanje za protestantskih cerkva, od tega jih je bilo šestinštirideset njihove dosežke je treba izkazati tako športnikom, kulturnikom, binkoštnih. Nasilje se je pričelo v mestu Asendabo, potem ko so znanstvenikom, politikom in drugim, ki širijo prepoznavnost se razširile govorice, da so v eni izmed cerkva v straniščno Slovenije v svetu. Ni namreč vseeno, ali živimo v državi, v kateri školjko odplaknili izvod Korana. Pripadniki islamskih se spodbuja prijaznost, pozitivno miselnost in dobrososedske skrajnežev so požgali tudi trideset domov, šolo in sirotišnico. Po odnose, ali pa v državi, v kateri se širita sovraštvo in nestrpnost. navedbah človekoljubne organizacije 'International Christian Kaj pa o Melaniji Trump pišejo mediji? Na vprašanje v Concern' (Mednarodna skrb za kristjane), ki pomaga žrtvam Googlu (Melanija Trump Fox News) najdemo 46.900.000 pregona, se je število kristjanov, ki so v zadnjih dneh zapustili zadetkov, na (Melanija Trump CNN News) pa 14.900.000. svoje domove, povzpelo že na deset tisoč.« Velika večina prispevkov v CNN ima tako ali drugačno Podobno poroča Nova24 in novice.najdi.si. negativno konotacijo, pogosto vezano na njenega moža Donalda V medijih kot Delo, Časnik, Mladina, TV hišah RTV Trumpa. Večina prispevkov v Fox Newsu pa – nasprotno – SLO ali POP TV in drugih iskanje ne vrne vsebinsko podobnega zagovarja Melanijo in predvsem njenega moža. Pogosto so zadetka, vsaj preko Googla ne v prvih 100 zadetkih. Najde se poročanja obeh relativno objektivna in se prava razlika pokaže sem in tja kakšen kratek prispevek o notredamski katedrali. Tudi šele v poročanju o prejšnji prvi dami Michelle Obama. Melanija v desnosredinskih medijih kot Slovencu ne najdemo obsežnih se za razliko od Michelle politično ne izpostavlja in se skuša prispevkov na to temo, so le krajši kritični prispevku o ukvarjati z bolj življenjskimi vprašanji kot izboljšava uničevanju avtomobilov itd. muslimanov. izobraževanja otrok in za pravice žensk. Bolj kot pri Michelle Požigi cerkva v Franciji so že pripeljali do evropskega Obama pri pisanji o Melaniji pogosto najdemo stavke o Donaldu predloga: »Predlog resolucije Evropskega parlamenta o požigih Trumpu, ki so pozitivni ali negativni glede na en ali drug vir in uničevanju cerkva v Franciji, Evropski parlament, … objave, čeprav je Melanija politično distancirana, kar je je težko A. ker so cerkve v Franciji cilj vse pogostejših napadov, razumljivo - kot da prihaja do izjemne polarizacije medijev pri požigov in uničevanja; opisu tudi nepolitičnih tem. Razlika je opazna pri pisanju o obeh B. ker se francoska vlada ne odziva na to drastično damah o oblekah, posamezni kretnji, kako je ali ni dala roko stopnjevanje napadov na verske objekte; predsedniku, itd. Preneseno (skoraj prepisano) vsebino pogosto C. ker ti napadi pomenijo resno kršitev individualnih in opazimo v slovenskih medijih, enako kritično do Melanije. kolektivnih pravic državljanov krščanske veroizpovedi; Slovenske novice, na primer, so 16. avgusta objavile 1. poziva Evropsko komisijo, naj francosko vlado opomni na »Zasačena Melania: Donalda hladno odrinila in nadaljevala njene obveznosti do državljanov krščanske veroizpovedi, v sama«. Večer 16. junija 2020 piše: »Ne shajata dobro: skladu s katerimi mora zagotovi varnost in zaščito verskih Poznavalka razkriva, kako se posmehljivo za hrbtom kličeta objektov pred barbarskimi in obskurantskimi napadi.«, zato je Melania in Ivanka Trump«. Siol 8.11.2016 objavi: »Melania toliko bolj nenavadno da objektivni večinski mediji o tem ne Trump je znanilka temnih časov za zahodne vrednote«. poročajo (ali pa poročajo tako, da iskanje preko Googla ne uspe). Primerjava objav z Michelle Obama in Barrack Obama ne vrne Sporno je tudi požiganje križa v Strunjanu, ki se je negativnih relacij v tovrstnem slogu. Nekatere objave o Melaniji zgodilo dvakrat: leta 2002 in leta 2013. Beli križ v ognju so pripeljale celo do tožb v Sloveniji in po svetu, sodišča so ji simbolno sicer spominja na KKK, rasistično organizacijo belcev dosodila nekaj odškodnin. oziroma tistih, ki so prepričani v superiornost belcev nad črnci. Ker pa so avtorji to izvedli kot umetniški dogodek, ni bilo 3 POŽIGI CERKVA kazenskih obsodb, čeprav je nastala tudi manjša umazanost križa. Narejena je bila analiza prvih 100 zadetkov na vprašanje v Ob obeh dogodkih pa je prišlo do polarizacije mnenj v javnosti Googlu: »Požigi krščanskih cerkev«. O tej tematiki pišejo: in medijih – ali je to umetnostni dogodek ali pa gre za napade na Domovina, manj znan medij izrazite desne usmeritve: 15.7.2020: verske simbole in spodbujanje sovraštva. Med mediji se je »Požigi cerkva so se iz Francije preselili v ZDA, a osrednji pojavila podobna porazdelitev kot pri pisanju o požigih – od mediji o njih molčijo. V soboto je v zvezni državi Florida moški odločne obsodbe do pravice svobodnega kulturniškega zapeljal z avtomobilom v notranjost cerkve in polil bencin, nato delovanja. pa cerkev požgal. Osumljenec je nato iz kraja prizorišča zbežal, a so ga policisti prejeli in pridržali. To pa ni bil edini požar v 4 LAŽNE NOVICE cerkvah v Ameriki v preteklem vikendu. Preiskovalci preiskujejo Izraz »lažne novice« je populariziral šele Donald Trump med še dva primera požiga cerkva. V sumljivih okoliščinah je zgorela volilno kampanjo pred štirimi leti. Tu navajamo opis iz angleške 217 let stara katoliška cerkev sv. Gabriela v nadškofiji Los Wikipedije: Angelesu in binkoštna cerkev v Limestonu, Alabama.« »Fake news, also known as junk news, pseudo-news, Desno usmerjena Demokracija piše: »V Franciji so v alternative facts, false news or hoax news,[1][2] is a form of news povprečju dnevno napadene tri cerkve, ponedeljek, 15 april consisting of deliberate disinformation or hoaxes spread via 2019. Kaj se je spremenilo v Franciji v zadnjih nekaj letih, da je traditional news media (print and broadcast) or online social do tega prišlo? Bi bil to lahko uvoz velikega števila ljudi, ki media.[3][4] Digital news has brought back and increased the menijo, da smo kristjani med »najbolj zlobnimi bitji, kar jih usage of fake news, or yellow journalism.[5] The news is then obstaja« (Koran 98:6)? Ali pa je na to pomisliti preveč often reverberated as misinformation in social media but »islamofobno«?« occasionally finds its way to the mainstream media as well.[6] Versko usmerjeni časopis Družina navede: »Deset tisoč Fake news is written and published usually with the intent to beguncev po požigu krščanskih cerkva, 25. 3. 2011, Islamski mislead in order to damage an agency, entity, or person, and/or skrajneži so v jugozahodni Etiopiji požgali devetinšestdeset gain financially or politically,[7][8][9] often using sensationalist, 274 dishonest, or outright fabricated headlines to increase readership. analize jasno kažejo, da so mediji v Sloveniji močno polarizirani Similarly, clickbait stories and headlines earn advertising in da se postavljata dve etični vprašanji: revenue from this activity.[7] Ali ni neetično biti tiho oz. ne obsoditi nekaterih nespornih The relevance of fake news has increased in post-truth zadev kot je nasilje ali požig umetniške stvaritve? politics. For media outlets, the ability to attract viewers to their Ali ni neetično proglašati se za objektiven medij in ne websites is necessary to generate online advertising revenue. poročati nič o levih ali desnih zadevah (pri čemer se je potrebno Publishing a story with false content that attracts users benefits zavedati, da za deklarirano usmerjene medije ni neetično poročati advertisers and improves ratings. Easy access to online samo svoj zorni kot - etični problem je trditi, da si objektiven in advertisement revenue, increased political polarization and the navijati za eno stran)? popularity of social media, primarily the Facebook News Verjetno je poglavitni razlog za polarizacijo medijev Feed,[3] have all been implicated in the spread of fake polarizacija družbe, agresivna ideologizacija in politizacija news,[7][10] which competes with legitimate news stories. zahodne civilizacije. Možno pa je tudi drugače: da so mediji Hostile government actors have also been implicated in povzročili polarizacijo družbe in da zavajajo pri trditvah o svoji generating and propagating fake news, particularly during objektivnosti, ko se hkrati spreminjajo v politična ali ideološka elections.[11][12] glasila. Analiza nasilja v ameriški družbi in medijev je že taka: Confirmation bias and social media algorithms like those kadar je množica ene strani napadala in požigala, so jo napadali used on Facebook and Twitter further advance the spread of fake predvsem mediji in politiki druge strani in obratno. Verjetno pa news. Modern impact is felt for example in vaccine gre za obojestransko relacijo in je povezana s pojavom hesitancy.[13] Fake news undermines serious media coverage prevelikega kapitalskega kopičenja v elitah bogatašev in ljudskih and makes it more difficult for journalists to cover significant množicah, odrinjenih in zmanipuliranih s strani medijev v lasti news stories.[14] An analysis by BuzzFeed found that the top 20 kapitalskih elit. fake news stories about the 2016 U.S. presidential election received more engagement on Facebook than the top 20 election REFERENCES stories from 19 major media outlets.[15] Anonymously-hosted [1] ACM Code of Ethics and Professional Conduct, fake news websites[3] lacking known publishers have also been https://www.acm.org/code-of-ethics criticized, because they make it difficult to prosecute sources of [2] Embedded EthiCS, Integrating Ethics Broadly Across CS Education. (2019), CACM, vol. 26, No. 8. fake news for libel.[16] The term "lying press"[17][18] is at times [3] Gallup/Knight poll 2020, used to cast doubt upon legitimate news from an opposing https://knightfoundation.org/press/releases/gallup-knight-poll-americans- concerns-about-media-bias-deepen-even-as-they-see-it-as-vital-for- political standpoint.” democracy/ Pojav lažnih novic in ameriška kampanja sovpadata s [4] Državni svet, posveti, http://www.ds-rs.si/?q=posveti-konference- povečano polarizacijo ameriških in posledično svetovnih in predavanja. [5] Gams, M. Državni svet, blog, https://dis.ijs.si/ds/ slovenskih medijev. Kar je pred leti še veljalo za neetično oz. v [6] Science 2020 nasprotju z novinarskim kodeksom, je sedaj postalo nekaj https://www.sciencemag.org/news/2020/06/mysterious-company-s- coronavirus-papers-top-medical-journals-may-be-unraveling normalnega – zavajati bralce, manipulirati z informacijami, [7] Travel Medicine and Infectious Disease uveljavljati medijsko propaganda tipa diktatorskih, Early treatment of COVID-19 patients with hydroxychloroquine and nedemokratičnih režimov. azithromycin: A retrospective analysis of 1061 cases in Marseille, France [8] 32. seja Državnega sveta Republike Slovenije, http://www.ds- rs.si/?q=dogodki/32-seja-drzavnega-sveta-republike-slovenije 5 DISKUSIJA IN ZAKLJUČEK Pojav polarizacije medijev se odraža tudi v spletnih aplikacijah, pa naj bo to Facebook ali Twitter. Po drugi strani pa prevelika svoboda spletnih medijev sama od sebe omogoči negativne pojave spletnih množic: anonimni posamezniki se izživljajo in ščuvajo k nasilju. Ko so spletni velikani to opazili, so začeli omejevati nasilne in sovražne izjave, video in audio posnetke ali lažne novice v smislu ploščate Zemlje in anticepilcev. Pri tem so pogosto uporabljali metode umetne inteligence, ki so bile načeloma izredno uspešne. Nekaj čudnih pojavov, kot začasna izločitev agadmatorja, je le stranski oziroma občasni problemčkek. Agadmator, oziroma Antonio Radić, hrvaški šahovski igralec in “YouTuber” ima od avgusta 2020 najpopularnejši šahovski kanal s 750.000 člani. Ko pa je nekega dne rekel, da beli pogosto premaga črnega, so ga za cel dan izločili kot vir sovražnega govora. Na primeru pisanja o Melaniji Trump in požigih cerkva v Franciji smo pokazali, da nekateri mediji o tem poročajo, drugi pa praktično nič. Podobno se je pokazalo, a na drugi strani, ko smo analizirali npr. pisanje o migrantih, recimo o policijskem nasilju nad njimi, o množicah mrtvih migrantov pri prečkanju Sredozemskega morja ali o človekoljubnih akcijah migrantov. Te 275 Prispevek vernikov za bolj etično slovensko družbo The Contribution of the Faithful for a more Ethical Slovenian Society dr. Mari Jože Osredkar Univerza v Ljubljani - Teološka fakulteta Poljanska 4, 1000 Ljubljana, Slovenija Tel: +386 1 434 58 46; fax: +386 1 43458 54 mari.osredkar.ofm@siol.net POVZETEK izražati svoje pripadnosti religiji ali verski skupnosti. Strokovna Sociologi religije predlagajo, da v sekularni državi učitelji v izhodišča pravijo, da učiteljica ne sme v šoli n ositi islamske javnih šolah ne bi smeli izražati svoje vere. Postavili smo tezo, naglavne rute, profesor pa ne sme biti oblečen v redovno da prepoved izražanja krščanske vere vodi v ne etično obnašanje. oblačilo. Po mnenju prof. Črniča, naj bi bila znamenja verske Nasprotno pa izražanje vere, ki sledi evangeljskemu nauku, vodi pripadnosti v javni šoli dovoljena le izjemoma kot v bolj etično družbo. Predstavili smo idejo sekularne države, demonstracijsko gradivo v pedagoškem procesu. Črnič se izpostavili razliko med vero in religijo in končno pokazali pomen sklicuje na razsodbo Evropskega sodišča za človekove pravice, izražanja vere. ki je odločilo, da je prisotnost križa na stenah učilnic v italijanskih javnih šolah kršitev dveh človekovih pravic: pravice KLJUČNE BESEDE staršev, da vzgajajo otroke v skladu s svojim religioznim ali Sekularna država, javna šola, verska praksa, religija, etika. filozofskim prepričanjem, in pravice učencev do verske svobode.(1) Profesorja Črniča cenimo kot znanstvenika in ABSTRACT kolega, in ravno zato se nam zdi vredno in primerno, da njegovo pozicijo vzamemo za izhodišče našega razmišljanja, kako lahko Sociologists of religion suggest that in a secular state, religion kristjani prispevajo za bolj etično družbo v Republiki Sloveniji. should not be professed in public schools by teachers. We put Ne bomo se zaustavljali ob podrobnostih Črničevih člankov in forward the thesis that banning the profession of the Christian faith leads to unethical behavior. Conversely, the profession of ob predlogih za slovensko zakonodajo. Na temelju dejstva, da je faith that follows Gospel teaching leads to a more ethical society. možno prepovedati izražanje vere, postavljamo tezo, da We presented the idea of a secular state, highlighted the prepoved izražanja krščanske vere, na splošno, vodi v manj difference between faith and religion, and finally showed the etično obnašanje. Nasprotno pa spodbujanje izražanja vere, ki importance of expressions of faith. sledi evangeljskemu nauku, vodi v bolj etično družbo. Postavljamo dve vprašanji, ki izhajata iz problema prepovedi KEYWORDS izražanja vere. Ali je taka prepoved pametna? Drugo vprašanje Secular state, public school, religious practice, religion, ethics. pa je bolj praktično: Ali je vernikom sploh možno preprečiti izražanje vere? Najprej bomo predstavili idejo sekularne države, ki se je razvila v evropskem kulturnem prostoru. Da bomo lahko 1 UVOD v nadaljevanju razumljivo predstavili svojo trditev in odgovorili V reviji CEPS Journal, št. 4/2019, ki izhaja na Pedagoški na vprašanji, pa bomo izpostavili tudi razliko med vero in religijo fakulteti Univerze v Ljubljani, je profesor dr. Aleš Črnič in končno pokazali pomen izražanja vere v vernikovem življenju. publiciral članek Religion, education, and the Challenges of Contemporary Societies. V njem se je osredotočil na mesto in vlogo religije v javni šoli v Evropi in v Republiki Sloveniji. To 2 IZRIVANJE RELIGIJE IZ JAVNEGA je tema, s katero se profesor Črnič ukvarja pri svojem ŽIVLJENJA raziskovalnem delu že dve desetletji. Z dr. Marjanom Smrketom Zagovorniki ideje o prepovedi izražanja vere v slovenskih javnih in dr. Zdenkom Kodeljo je leta 2010 pripravil tudi Strokovna šolah poudarjajo, da je Slovenija sekularna država. Zaustavimo izhodišča za razpravo o določitvi odnosa med javno šolo in se nekoliko pri tej opredelitvi. Sociologi religije uporabljajo tri religijo. Rdeča nit njegovih pisanj o tej temi je prepričanje, da izraze, ki so si zelo podobni: sekularnost, sekularizem in izražanje vere in verski simboli v javnih državnih izobraževalnih sekularizacija. Že na prvi pogled ugotovimo, da vsi trije izrazi ustanovah ne morejo biti dovoljeni. Po njegovem mnenju dijaki izhajajo iz iste latinske besede saecularis, kar pomen posvetno. in študentje sicer lahko izražajo vero z nošenjem verskih V krščanski terminologiji si stojita sproti dve področji. Prvo simbolov. Nasprotno pa profesorji ne smejo na viden način zaobsega vse kar prihaja od Boga, torej Božje; kar je Bogu 276 posvečeno je sveto. Na drugi strani pa imamo to, kar prihaja od zagovarja svobodo govora, vesti in tudi svobodo na področju človeka; to je človeško ali posvetno. Iz omenjene latinske besede religije. Nihče ne more nikogar prisiliti v verovanje, kakor tudi se je razvila beseda saecularisatio. nihče ne sme nikomur omejevati svobodo izpovedovanja vere. V evropskem srednjem veku si je Cerkev podredila politično Tako imenovano versko svobodo je sprejela tudi katoliška oblast. S tem ni imela avtoritete samo na področju svetega, Cerkve v svoj nauk na Drugem vatikanskem vesoljnem temveč tudi na področju posvetnega. Razum je bil podrejen veri cerkvenem zboru. (10) Liberalni sekularizem je v 20 stoletju oz. Božjemu razodetju; civilni vladarji pa so se morali podrediti dosegel umik Cerkve v zasebno sfero in ji onemogočil vpliv na cerkveni oblasti. Popolno oblast rimskega papeža je najprej začel javno (posvetno) življenje. (11) Bistvo liberalnega sekularizma spodnašati protestantizem, ki je z »zahodnim razkolom« ni uničenje religije, temveč zahteva, naj se Cerkev umakne iz zrelativiziral katoliški nauk, dokončno pa jo je spodneslo javnega življenja in se ukvarja z duhovnostjo. Tamimi je celo francosko razsvetljenstvo, ki je razum osvobodilo izpod vere. zapisal, da je liberalni sekularizem religijo pustil prepuščeno Razsvetljenci so zahtevali laizacijo šolstva in poučevanje znanja, samo sebi, »naj uspe ali propade!« (12). Po tem načelu se ki temelji na razumu, neodvisno od Božjih resnic.(2) Francoska sekularne države niso več zanimale za religijo in so religijskim revolucija je z nacionalizacijo cerkvenih posestev pokazala, da ustanovam pustile popolnoma proste roke pri njihovem Cerkev ni več gospodar v državi, ki so jo nekdaj imenovali »prva delovanju znotraj njihovih ustanov. Lahko rečemo »sekularnost« hčerka Cerkve«. Kasnejše revolucije v Evropi, dokončno pa v polnem pomenu besede. revolucija leta 1848 je na simbolen način povedala, da je Cerkev To je veljalo do preloma tisočletja. Takrat pa je zahodni svet ovira družbenemu razvoju v Evropi. V tem času se je že izkusil islamski ekstremizem, ki je upravičenost načela uporabljal izraz sekularizacija in sicer v povezavi s cerkvenim sekularnosti postavil pod vprašaj. Država se je začela močno posestvom, ki je prehajalo v državno oskrbo. Tu ni šlo le za zanimati za delovanje religijske skupnosti. Predvsem za posestva, temveč za politično oblast, šolstvo, bolnišnice in delovanje islamskih skupnosti v Evropi. To pomeni konec gospodarstvo. V bistvu gre za »osamosvojitev dejavnosti, ki so v sekularne države oz. prehod v post sekularnost. Vredno je preteklosti bile pod nadzorom Cerkve«.(3) V tem smislu tudi omeniti, da je liberalni sekularizem naredil napako, ker je danes besedo sekularizacija opredeljujemo kot »preobrazbo duhovnost, na kar je omejil delovanje religije, razumel le kot cerkvenega v posvetno« (4), tudi kadar gre za »odvzem ali pobožne molitve vernikov. Ampak življenje po veri obsega prevzem cerkvenih posesti s strani države«(5). Profesor mnogo, mnogo več kot zgolj recitiranje molitev. Kerševan proces sekularizacije deli na tri nivoje: zmanjševanje religijskega vpliva na javno družbeno življenje, zmanjševanja vpliva religijske ustanove na njene pripadnike in zavračanje 3 VERA IN RELIGIJA verskih naukov (6). Pri sociologu Bergerju pa najdemo V slovenskem akademskem prostoru so po uvedbi komunistično razlikovanje med sekularizacijo na ravni družbe in na ravni ateističnega političnega sistema vprašanja verske problematike posameznika (7). Na ravni družbe se sekularizacija dogaja, ko se popolnoma izločili iz univerzitetnega izobraževalnega programa. dejavnost cerkvenih institucij umika ali izriva iz javnega Tekom let pa je, tako političnim voditeljem, kakor tudi življenja. Na ravni posameznika pa se sekularizacija dogaja, ko odgovornim na univerzi, postalo jasno, da je religija dejstvo, ki vernik več ne sledi v polnosti navodilom religijske ustanove. ga znanost ne more zanemarjati. Ljubljanska univerza se je zato Preprosto povedano, ko na področju vere in morale sam izbira, začela resno znanstveno ukvarjati z religijo. Toda zgolj z kaj bo sprejel in kaj ne. Predvsem, ko vernik vero izraža zgolj v sociološkega stališča. Sociolog govori o tem, kar vidi. Prešteli so zasebnem življenju, ne pa v javnosti. verske skupnosti v državi, ugotavljali, koliko ljudi obisku je Skratka, sekularizacija je dolgotrajen proces izginjanja vpliva verske obrede ter pripravili navodila za vzgojo »državnih kadrov«, kjer je bilo izpostavljeno, da je religija znamenje religije iz javnega življenja. V času komunistične Jugoslavije je zaostalosti oz. da se resen znanstvenik z Bogom ne ukvarja. bila moderno reči, da je partija cerkveni vpliv omejila na Napovedali so, da bo religija popolnoma izginila, ko bo znanost zakristijo. Država, ki je vpliv religijske ustanove na javno napredovala. Sociološka znanost se namreč lahko ukvarja z življenje zmanjšala na najnižjo možno mero, se torej imenuje dejstvi, ki jih lahko vidi, prešteje, primerja oz. količinsko sekularna država. V Evropi se kot sopomenka sekularnosti ovrednoti. Ta metodologija pa ne opazi bistva religioznega uporablja tudi izraz laičnost. Sekularna država je laična država. dogajanja. To pa je vera. Religije ne bi bilo brez vere. Kjer pa je V novejši evropski zgodovini sta proces sekularizacije pospešila vera, se pa nujno pojavi tudi religija. Skratka, sociolog religije, komunizem in liberalizem. Prvi v vzhodni, drugi v zahodni ki nima izkustva vere, zato religije v polnosti niti ne more Evropi. Vendar je pomembno poudariti, da je bil komunizem razumeti. Ateistični opazovalec religije namreč ne opazi vere. Ta antireligozen, ki je želel uničiti religijo. Če je sekularizacija mu je nedostopna, ker nima izkustva o njej. Če hočemo razumeti proces izrivanja religioznega iz javnega življenja, potem je religijo v polnosti, moramo stopiti na področje teologije. Teolog pa izhaja iz svojega izkustva verovanja in religijo lahko razume sekularnost stanje, v katerem posvetna oblast ne vpliva na v veliki večji meri od ateističnega sociologa. Vsekakor je danes cerkveno, ta pa ne na posvetno. Danes sekularnost izraža popolnoma evidentno, da velika večina ljudi veruje. ločenost posvetnosti od religioznosti, ki jo izraža načelo »ločenosti Cerkve od države!«(8) Katoliška Cerkev je sprejela dejstvo, da nima oblasti na družbeno političnem področju. Javno 4 DEJSTVO VEROVANJA življenje usmerja posvetna država. Po podatkih, ki jih najdemo v Britanski enciklopediji, približno Ideologija, ki zagovarja proces sekularizacije, se imenuje 85 % danes živeče človeške populacije pripada različnim sekularizem. Ta ideologija »desakralizira moralo in vrednote ter religijam oz. verskim skupnostim.(13) Tudi v preteklosti ni bilo osvobojenega od kakršnihkoli absolutnih resnic ustvari nov, od bistveno drugače. Morda je bil odstotek vernih še celo nekoliko človeka ustvarjen sistem vrednot«(9). Liberalni sekularizem večji. Tu ne gre za zanemarljive številke. Po podatkih 277 statističnega urada Slovenije je leta 2002 tudi Slovenija kazala nagovarjanje odsotnih oseb, ki jih vernik kliče s »ti«, imenujemo podobno podobo vernosti: nekaj čez 70 % Slovencev veruje in molitev. Ampak molitev še zdaleč ni edini izraz vere. pripada verskim skupnostim (14). Zakaj človek veruje? 5 RAZLOGI ZA VEROVANJE 6 IZRAŽANJE VERE OHRANJA VERO IN Znanost je o verovanju v zadnjem desetletju odkrila marsikaj SPODBUJA ETIČNO DRŽO novega. Najpomembnejše novejše spoznanje o veri je, da imajo ljudje (tudi ateisti) del možganov vnaprej specializiranih za Znamenje vernosti je v bistvu izpolnjevanje Božjega razodetja, oz. nauka, ki ga je verska ustanova svojim članom zapovedala. V verovanje oz. za vero in da imajo postopki verovanja svojo kemijo, svoje kemično religiji je nekaj bistvenega in nespremenljivega, veliko pa je le -biološke procese (15). Od tod sledi kar nekaj zanimivih izpeljav in analiz. Danes na splošno velja, da so obrobnega, torej v pomoč, da se bistvo ohranja. In ta pomoč se, določeni deli možganov vnaprej pripravljeni za svojo funkcijo, glede na potrebe, iz obdobja v obdobje spreminja. V krščanskem življenju je Božje razodetje nespremenljivo, to je ustava recimo za vid ali govor. Ljudje nismo nepopisan list, ki ga v Katoliške cerkve. Sem lahko prištejemo Božje zapovedi: Ne laži, celoti oblikuje okolje. Seveda je končno oblikovanje človeka in njegovih možganov skupek prirojenih in pridobljenih lastnosti, ne kradi, ne ubijaj… Kako se bo vernikovo življenje po evangeliju izražalo v posameznih zgodovinskih obdobjih, pa vendar zadnja desetletja poudarjajo pomen genetike in predispozicij človeških možganov. Dr. Noam Chomsky, urejajo odloki, zakonodaja posameznih koncilov, glede na ameriški znanstvenik, je med prvimi, sicer na področ okoliščine in potrebe. Ker je interes Cerkve, da njeni člani ju ohranjajo vero, Katoliška cerkev v cerkvenih zapovedih svojim lingvistike, to tezo postavil na abstraktnem nivoju na osnovi eksperimentov. 29. marca 2005 so mu celo podelili častni vernikom določa versko prakso, ki jo lahko imenujemo institucionalna, npr.: »Bodi ob nedeljah in zapovedanih doktorat ljubljanske univerze. Ker so sposobnosti možganov ključnega pomena za uspeh praznikih pri sveti maši, pôsti se zapovedane postne dni, spovej se svojih grehov vsaj enkrat v letu in vsaj v velikonočnem času človeštva in ker je del možganov specializiran za vero in ne za, pojdi k obhajilu, sklepaj zakon po cerkvenih določbah …« recimo, še boljšo matematiko, je verovanje očitno ena ključnih Cerkveno učiteljstvo vernikom določa, kako naj izražajo svojo lastnosti za evolucijski uspeh ljudi. Zamislimo si dve ljudstvi iz vero in jim s tem pomaga in daje oporo za ohranjanje in krepitev preteklosti. Eno verno in eno neverno. Izkazalo se je, da je njihove osebne vere. Če pa Cerkev spozna, da se je življenje evolucija za zmagovalca izbrala verno ljudstvo. Pri tem je spremenilo, se morajo spremeniti tudi cerkvena navodila. Pri potrebno upoštevati, da možgani porabijo približno 20 % religijskem dogajanju lahko versko prakso in obrede primerjamo energije, torej je verujoči del možganov velika dodatna s posodo, ki ohranja vsebino - vero. V zgodovini se je posoda že obremenitev. Pa se je dodatni vložek očitno izplačal. Rečemo velikokrat zamenjala in se še bo zaradi cilja, da se vera ohranja lahko torej, da je trditev o koristnosti verovanja zgodovinsko in neokrnjena. Skratka, verovati pomeni vero izražati tako, kakor evolucijsko dejstvo (16). zapoveduje verski nauk oz. Božje razodetje. Vera pa ni izbirna dejavnost ali človekov hobby, s katerim bi Mi pa postavljamo tezo, da človek veruje, ker je bitje se ukvarjal zaradi obilice prostega časa. Vera je odnos, v katerem odnosov, torej zato, ker je povezan z drugimi. To je najgloblji in se je človek znašel oz. mu je bil podarjen. Na popolnoma enak prvi razlog človekovega verovanja. Moderna teologija nas uči, način, kakor se je človek znašel v življenju, ki mu je bilo da je vera predvsem človekov odnos s presežnim; z vsem, kar podarjeno in ga želi ohranjati in podaljšati, tako vernik želi naravo presega. S tujko to imenujemo transcendenca. Prvo ohranjati vero. To pa lahko stori le tako, da vero izraža! Verniki človekovo izkustvo transcendence pa je odnos z drugim, s prepoznavajo v zapovedih in prepovedih absolutno avtoriteto oz. slehernim drugim, ki ga v življenju sreča. In prav v tem absolutno resnico, ki jim omogoča ohranjanje vere. vsakdanjem odnosu se človek sreča in se srečuje z nekom, ki ga Izražanje vere je vedno tuzemsko, konkretno; to so dejanja presega. Človek je namreč bitje, ki se v odnosu do drugega ne vsakdanjega življenja. Zato so vse religije tuzemeljske in zadovolji s čutno predstavo (vizualno sliko, glasom, tipom) potrebujejo nek zemeljski ustroj. Ni nekega abstraktnega drugega, temveč v bližnjem išče in spoznava, čeprav se zdi, da je komuniciranja z Bogom, ampak je le pogovor s simboli, človeka že našel in spoznal. Kaj človek prepoznava v človeku? podobami in besedami. Za vernika je izražanje vere nekaj Pravzaprav čuti, da se v odnosu do drugega ne more omejiti le na podobnega kakor je dihanje za človeško telo. Če preneha dihati, to, kar vidi, sliši ali otiplje, temveč se v drugem skriva nekaj, kar se konča telesno življenje. Tako tudi človek preneha biti vernik, je veliko več kot zgolj »neko telo« ali zgolj neka »duša«. ko se njegova vera preneha izražati. Zato resni verniki, ki želijo Verjame, da bo to »nekaj več« v drugem našel in se zato pri ohraniti svojo vero, nikoli ne prenehajo z versko prakso. svojem iskanju nikoli ne zaustavi. Ker spozna, da drugega ne Zagotovo jo spreminjajo, ne morejo pa ne izražati tega, kar nosijo more nikoli v polnosti razumeti, zaobjeti in nikdar posedovati, v sebi. Vera torej ne izginja, le izrazi vere se spreminjajo. Res je, verjame (nima pa dokazov, da bi to vedel), da v drugem obstaja da se izražanje vere po navodilih ustanove pogosto zanemarja, nek popolnoma Drugi, ki je nedoumljiv. In ker je tako drugačen, hkrati pa je tudi res, da danes ljudje intenzivneje hrepenijo in ga zapiše z veliko začetnico. Sluti, čuti, izkuša in veruje, da je veliko bolj iščejo duhovnost kot v preteklosti, vero pa izražajo na drugi le podoba nekoga, ki ga išče. sebi lasten način in s tem nehote spreminjajo ustanovo, ki ji Vera je človekova sposobnost, da v odsotnosti neke osebe pripadajo. prepoznava tudi njeno prisotnost. Kljub temu, da Boga ne vidi, Če pa podrobneje pogledamo, vidimo, da je filozofija in prepoznava njegovo prisotnost; v odsotnosti osebe, katero telo so sekularna družba te iste Božje zapovedi, s katerimi verniki pokopali na pokopališču, pa prepoznava prisotnost te osebe. To izražajo svojo vero, poimenovala z besedo »etika«, torej, kot prepoznavanje izraža tako, da osebo nagovarja. V religiji to nauk o dobrem, kot vodilo za preživetje človeka in človeštva. 278 Logika nam torej pove, da krščanska verska praksa ni nič izgubi vero iz preprostega razloga, ker se prepusti javnemu drugega kot etična drža, ki omogoča preživetje družbe. mnenju, da vere »ni moderno« izražati po institucionalnih merilih. Če uporabimo še eno primero, bi dejali, da je vera toliko zasebna zadeva vernikov, kakor je zasebna zadeva vernikov 7 FUNDAMENTALIZEM IN posejanost cerkva po slovenskih mestih in gričih. Turisti, ki EKSTREMIZEM pridejo v Slovenijo, jih morajo opazili. Iz teh znamenj lahko sklepajo, da v Sloveniji živijo verni kristjani. To je podoba Če se vernik odloči, da bo svoje življenje utemeljil na Božji slovenskih katoličanov, iz katere lahko, tudi tisti, ki bi to podobo besedi in se tega tudi striktno drži, ga imenujemo fundamentalist. sicer radi zavili v temo (nočno osvetljevanje cerkva in očitek Tisti trenutek pa, ko bo želel prisiliti tudi ljudi v svoji okolici, da svetlobnega onesnaževanja), prepoznajo podobo Boga, ki jo bi živeli kot živi on, se spremeni v ekstremista. Verski verniki nosimo v sebi. Z gotovostjo lahko potrdimo, da nihče ne ekstremizem je prisila drugih k sprejemanju vrednot, ki jih more preprečiti vernikom izražanja vere. Zakonodaja lahko spoštuje ekstremist. prepoveduje verske simbole v javnih prostorih sekularne Pri izražanju vere moramo razlikovati med različno ustanove, toda noben zakon ne more preprečiti učitelju ali pomembnimi dolžnostmi v religiji. Prav gotovo je velika razlika javnemu uslužbencu izražanje vere v javnem življenju, pa četudi med vzdržkom mesa na postni petek in abortusom. Gotovo! je predsednik države. Ne zato, ker bi bili verniki privilegirani, Toda, če nekdo ne spozna sam, da je spočeti otrok človeško bitje, temveč zato, ker noben zakon ne more človeku preprečiti etične ali če nekdo ne spoštuje svetosti človekovega življenja, ga tudi drže, četudi jo prepoznava kot Božjo voljo. To pa tudi nakazuje ekstremist ne bo mogel k temu prepričati. Zato je tudi dokument odgovor, da prepovedovanje izražanja vere ni modra politična Drugega vatikanskega koncila o verski svobodi jasen: pri poteza. Ker so Božje zapovedi temelj etične drže, bi tako dejanje oznanjevanju vere ne sme biti prisile, nobene prisile. Načeloma v bistvu prepovedalo etično obnašanje. Ločitev Cerkve od države to pravilo poznajo tudi muslimani. Tudi vernikom se posamezne omogoča avtonomno delovanje obeh ustanov, nikakor pa nima verske vrednote ne more in ne sme s silo ukazati, da se namena posameznikom onemogočati verskega izražanja. Kakor spolnjujejo. Fundamentalizem je v svoji osnovi nekaj dobrega, je danes samo po sebi umevno, da lahko vsak človek v javnosti ekstremizem pa je nekaj slabega, ker vključuje nasilje nad izraža svojo spolno usmerjenost, tako bi morala tudi slovenska drugimi. Vsekakor pa izpovedovanje vere oz. življenje po Božjih sekularna država dovoljevati in omogočati vsem, tudi javnim zapovedih ni ekstremizem. osebam, izražanje vere. S tem ne bi privilegirala nobene religije, Ker omenjamo islamske ekstremiste, velja opozoriti, da v bi pa slovenska družba postala veliko bolj etična. Zagotovo velja islamskem svetu na najdemo niti približek sekularizacije, ki je v poudariti, da izražanje vere ali pričevanje za evangelij samo po zadnjih stoletjih prežela krščansko Evropo. Zato tudi ne moremo sebi še zdaleč ni ekstremistično dejanje. govoriti o sekularnih islamskih državah. V ozadju stojijo teološki Na najpomembnejši kolesarski dirki po Franciji leta 2020 razlogi. V izvirnem islamu namreč interpretacija Božjega blesti Primož Roglič, ki si je dal na roko vtetovirati križ in se tudi razodetja ni možna. Krščanska teologija, ki pa zagovarja nujnost pokriža pred začetkom vožnje. Slovenski kolesar pa hkrati izraža razlaganja Božje besede, je omogočila in dopustila sekularizacijo visoko etično držo, ko sotekmovalce opozarja na nevarnosti. in sekularnost. Islamska teologija namreč v svojem temelju Tudi na drugih javnih igriščih športniki izražajo svojo vero. nasprotuje razlaganje Božjega razodetja, ker koransko besedilo Nekaterim slovenskim gledalcem to ni všeč. Ampak dejstvo je, je nastalo po nareku »od zgoraj«! Muslimani v Evropi, ki sicer da vera ne pomeni le prepričanja, temveč je predvsem način dopuščajo razlaganje koranskega besedila, so se v očeh življenja. Čim bolj verniki sledijo verskemu nauku, tem več pravovernih muslimanov v arabskih državah oddaljili od lahko prispevajo za bolj etično slovensko družbo. pravoverne linije. Zato v islamskem svetu šariatsko pravo še danes ureja javno življenje. Islam daje vedeti, da biti zvest Bogu pomeni svoje zasebno in javno življenje podrediti Božji volji. Ko REFERENCE se je torej islamski fundamentalizem soočil z evropskim [1] Dokument povzemamo po Ločevanje javne šole in religije v Mladina, 14. sekulariziranim svetom, je izbruhnil nasilni terorizem. Islamski 1. 2010 [2] Chadwick, Owen. 1993. The secularisation of the European Mind in the fundamentalisti ne morejo razumeti in ne sprejeti sekularizacije. 19 th Century, Cambridge University Press, Cambridge., 27. Zato so se iz fundamentalizma prelevili v ekstremizem. [3] Sruk, Vlado. 1995. Filozofija. Cankarjeva založba. Ljubljana., 296. [4] Leksikon Cankarjeve založbe, 938. [5] Flere Sergej, Kerševan Marko. 1995. Religija in sodobna družba. Znanstveno in publicistično središče. Ljubljana, 122. 8 DISKUSIJA IN SKLEP [6] Ibid. 123-124 [7] Berger, Peter L. 2000. Secularism in Retreat v John L. Esposito, Azzam V slovenski družbi in politiki pogosto poslušamo trditve, da sta Tamimi (ur): Islam and Secularism in the Middle East. Hurst&Company. London, str 39. vera in religioznost zasebni zadevi. Kadarkoli se v parlamentu [8] O načelo ločenosti Cerkve od države lahko beremo v knjigi Anton Stres, sproži debata o zakonih, ki obravnavajo področje religioznosti, Cerkev in država, Družina, Ljubljana 1998. nekateri poslanci povedo, da je Cerkev ločena od države. Ampak [9] Ezzat, Heba Raouf. 2000. Secularism, In the State and the Social Bond: vera je toliko zasebna zadeva posameznika, kolikor je ljubezen the Withering Away of the Family v Islam and Secularism in the Middle East. Hurst&Company. London, 125 zasebna zadeva zaljubljenega dekleta in fanta. Vso pravico [10] Prim. Izjava o verski svobodi, v Koncilski dokumenti, Ljubljana 1980. imata, da se skupaj, z roko v roki, sprehajata v javnosti, vso [11] Chadwick, Owen. 1993. The secularisation of the European Mind in the pravico imata, da se poročita tudi pred oltarjem. Tu ne moremo 19 th Century, Cambridge University Press, Cambridge, 27. [12] Tamimi, Azzam 2000. The Origins of Arab Secularism v Islam amd govoriti le o pravicah, temveč o potrebi. Ljubezen se mora Secularism in the Middle East. Hurst&Company. London, 15 izražati navzven, drugače izgine. Enako je z vero. Verniku [13] https://www.britannica.com/topic/religion prepovedati izražati vero je nekaj podobnega, kakor če bi [14] Prim.http://www.stat.si/popis2002/si/rezultati/rezultati_red.asp?ter=SLO človeku prepovedali dihati. Zato pa so se toliki kristjani &st=57 »zadušili« in se v času komunizma iz pobožnih ministrantov [15] Gams, Matjaž. 2001. Weak intelligence: Through the principle and paradox of multiple knowledge, Advances in computation: Theory and prelevili v zagrizene nevernike. Tudi danes marsikateri kristjan practice, Volume 6, Nova science publishers, inc. NY., 245. 279 [16] Gams, Matjaž. 2005. Znanost o verovanju, zbornik 8. multikonference Information society IS 2005, Institut Jožef Stefan Ljubljana. , 43-47. 280 Vloga religij pri oblikovanju globalne etike The role of religions in shaping a global ethics Roman Globokar Teološka fakulteta Univerza v Ljubljani Slovenija roman.globokar@teof.uni-lj.si POVZETEK worldviews and serves as prevention from any form of radicalization. Religije so v preteklosti bistveno pogojevale moralne standarde v posameznih družbah. V sodobni globalni družbi smo priča KEYWORDS močni prepletenosti različnih religij in svetovnih nazorov, zaradi interreligious dialogue, world ethos, religious instruction, ethical česar tudi lokalne skupnosti postajajo vse bolj večreligijske in education večkulturne. Številni globalni izzivi, kot so ekološka kriza, odprava revščine, preprečevanje vojn in nasilja, kličejo po oblikovanju globalne etike. Hans Küng je s somišljeniki zasnoval 1 POMEN RELIGIJ ZA ETIKO NEKOČ IN svetovni etos, ki združuje bogato moralno tradicijo vseh velikih DANES religij, da bi zagotovil svetovni mir in pravične odnose med narodi. Pomembno vlogo pri širjenju zavesti o globalni Temeljna predpostavka etike je, da je človek svobodno bitje, ki odgovornosti ima tudi religijski in etični pouk v javnih šolah. se na podlagi svojega razumnega razmišljanja odgovorno odloča. Aktualni dokumenti evropskih institucij spodbujajo, da bi bili vsi Podlaga za njegovo vrednotenje je njegov temeljni pogled na svet učenci deležni ustrezne izobrazbe na religijskem in etičnem in človeka. Presojanje o tem, kaj je vredno, kaj je dobro, kaj je področju, kar je najboljše zagotovilo za mirno sožitje med ljudmi treba storiti tukaj in sedaj, je odvisno od tega, kako človek gleda različnih pogledov in za preprečevanje vsake oblike na svet in kakšen pogled ima na uresničeno človeško življenje. radikalizacije. Glede na opredelitev, kdo je za posameznika človek, kaj je v življenju človeka najpomembnejše in kakšno je mesto človeka KLJUČNE BESEDE znotraj celotnega svetu, prihaja do preudarnih in odgovornih odločitev, kako naj se posameznik odloča, da bo uresničil svoje Medreligijski dialog, svetovni etos, religijski pouk, etična človeško življenje. Vizija uresničenega človeškega življenja je vzgoja, torej horizont posameznih etičnih odločitev. ABSTRACT Posameznik oblikuje svoj pogled na svet znotraj družbenega in kulturnega življenja, v katerega je rojen. Njegovo razmišljanje In the past, religions have significantly conditioned moral je v marsičem pogojeno s kulturo, tradicijo, jezikom in religijo standards in different societies. In modern global society, we svojega okolja. Preden posameznik pride do samostojnega are witnessing a strong intertwining of different religions and razmišljanja in odločanja o svojem življenju in o svojem worldviews, which is the reason why local communities are delovanju v družbi, je deležen vzgoje s strani svojega primarnega becoming increasingly multireligious and multicultural. Many socialnega okolja in seveda tudi drugih zunanjih vplivov, ki global challenges, such as ecological crisis, the eradication of sooblikujejo njegov pogled na svet. Osebna svoboda poverty, the prevention of war and violence, call for the posameznika je poleg drugih vplivov v marsičem pogojena tudi formation of a global ethics. Hans Küng and his like-minded associates designed a world ethos that combines the rich moral z družbenim okoljem in vzgojo. tradition of all the major religions to ensure world peace and V tradicionalnih družbah so imele glavno vlogo pri just relations among nations. Religious and ethical education in opredeljevanju smisla celotnega sveta in človekovega mesta v public schools plays an important role in raising awareness of njem religije. Religije so predstavljale osnovno kohezijsko silo global responsibility. Latest documents from the European družbe. Na podlagi njihovih temeljnih pripovedi so pripadnikom institutions encourage all students to obtain appropriate določene skupnosti razlagale njihov izvor, njihovo poslanstvo, education in the field of religion and ethics. This is the best njihove cilje. Dajale so podlago za družbeno ureditev, urejale guarantee for peaceful coexistence between people of different obredno življenje in s prazniki določale življenjski ritem. Podajale so tudi razlage za soočanje s konfliktnimi situacijami v Permission to make digital or hard copies of part or all of this work for personal or življenju in s tem prispevale k osmišljanju individualnega in classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full skupnega življenja v družbi. Kot take so bile religije s svojimi citation on the first page. Copyrights for third-party components of this work must pripovedmi in obredi tudi podlaga za moralno življenje be honored. For all other uses, contact the owner/author(s). posameznikov in skupnosti. Religije so določale kodeks etičnega Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). obnašanja, ki so ga morali posamezniki upoštevati, sicer so bili izključeni iz te družbe. Pri utemeljevanju svojega etičnega nauka 281 so se religije sklicevale na božjo avtoriteto ali na nauk povezuje različna verstva in svetovne nazore. V iskanju karizmatičnega ustanovitelja. skupnega etičnega jedra vsega človeštva se je pokazalo, da so Z oblikovanjem moderne družbe po francoski revoluciji etične norme kulturno pogojene, zato je treba vsako etično religija nima več odločilne vloge v javnem življenju. Svoje mesto vsebino najprej razlagati znotraj njenega zgodovinskega, ima zgolj še v osebnem življenju posameznikov. To, kar sedaj družbenega in verskega konteksta. Nekateri so zato prepričani, oblikuje podlago za skupno življenje, je pripadnost določenemu da je etika kot taka odvisna od kulture in posledično relativna. narodu, določeni kulturi oz. odločitev samostojnih oseb, da želijo Drugi pa trdijo, da na podlagi univerzalne človeške narave živeti v skupni državi na podlagi določenih skupnih vrednot (npr. obstajajo določene vrednote in norme, ki presegajo kulturno svobodo, enakost, bratstvo). Pri iskanju odgovorov glede izvora pogojenost in imajo univerzalno veljavo. sveta in človeka, mesta človeka v celotnem svetu ipd. se moderni Slednje je prepričan že omenjeni teolog Hans Küng. Po človek opira na spoznanja znanosti, ki se z eksponentno hitrostjo njegovem mnenju najdemo določene temeljne prvine moralnosti razvija na vseh področjih. Znanstvena spoznanja sedaj v vseh kulturah sveta. »Nenapisane etične norme predstavljajo predstavljajo neovrgljiva dejstva, na katera se lahko opirajo po prepričanju kulturnih antropologov 'skalo', na kateri je posamezniki in skupnosti pri urejanju življenja. Podlaga za zgrajena človeška družba. To lahko imenujemo 'pra-etos', ki skupno življenje ne predstavlja več etični kodeks, ki bi bil predstavlja jedro skupnega etosa človeštva oz. svetovnega utemeljen v religiji, ampak spoštovanje temeljnih človekovih etosa.« [4] To jedro lahko najdemo po Küngovem prepričanju v pravic, ki izhajajo iz univerzalne narave človeške osebe. vseh religijah in v vseh kulturah. Brezpogojno spoštovanje dostojanstva človeške osebe postane Konkretni poskus določitve vsebine globalne etike osnova za oblikovanje etike brez religijske podlage. predstavlja Deklaracija o svetovnem etosu, ki je bila sprejeta na Na najbolj ekspliciten način je ta proces izpeljal Immanuel zasedanju »parlamenta svetovnih verstev« v Čikagu 4. septembra Kant (1724−1804), ki za izvor moralnosti postavi razum, ki se 1993. Na začetku čikaške deklaracije, ki jo je zasnoval Hans mu ni potrebno sklicevati na kakšno še bolj temeljno avtoriteto. Küng, so predstavnice in predstavniki različnih verstev opisali Kant se je hotel izogniti nevarnosti relativizma zaradi pluralnosti takratno krizno stanje, ki se je izražalo v svetovnem krščanskih veroizpovedi in etiki dati temelj, ki bi bil univerzalno gospodarstvu, ekologiji in politiki. Avtorji se strinjajo, da znotraj zavezujoč. Njegova formulacija kategoričnega imperativa se različnih verskih izročil obstaja skupni etos, s katerim se je glasi: »Deluj tako, da lahko velja maksima tvoje volje vselej mogoče zoperstaviti usodnim globalnim spremembam. »Trdimo, hkrati kot načelo obče zakonodaje.« [1] Kant izhaja iz da med religijami obstaja soglasje, ki je lahko osnova za svetovni razsvetljenskega prepričanja, da lahko človek s svojim razumom etos. Obstaja minimalno temeljno soglasje o zavezujočih prepozna univerzalno človeško naravo, ki jo v enaki meri vrednotah, trdnih standardih in temeljnih moralnih prepričanjih.« spoštuje v sebi in v vseh drugih ljudeh. Z vsebinskega vidika se [5] Vsi ljudje bi lahko sprejeli to jedro etičnosti, pri čemer pa Kantova etika ne razlikuje od tradicionalne krščanske etike, avtorji poudarjajo: »S svetovnim etosom ne mislimo nove formalno gledano pa se ne sklicuje več na religiozno avtoriteto, globalne ideologije, tudi ne enotnega verstva onkraj vseh ampak na obči človeški razum. obstoječih verstev, še najmanj pa prevlado enega verstva nad ostalimi. S svetovnim etosom mislimo na temeljno soglasje glede trdnih zavezujočih vrednot, neizpodbitnih meril in osebnih 2 MEDRELIGIJSKI DIALOG ZA temeljnih drž. Brez temeljnega soglasja na področju etosa grozi OBLIKOVANJE GLOBALNE ETIKE vsaki družbi prej ko slej kaos ali diktatura in posamezni ljudje Sodobni svet bistveno zaznamuje proces globalizacije in bodo obupani.« [5] medsebojne prepletenosti različnih kultur in religij znotraj Temeljna zahteva svetovnega etosa je zelo preprosta: »Z globalnega sveta. Bolj kot kadarkoli v zgodovini človeštva je vsakim človekom po potrebno ravnati človeško.« To temeljno treba najti skupne etične temelje, ki bodo omogočali sožitje med načelo je podkrepljeno s Kantovim kategoričnim imperativom in različnimi narodi, državami, religijami in kulturami. Številni z zlatim pravilom, ki ga je mogoče najti v različnih kulturah in globalni izzivi, kot so onesnaževanje okolja, klimatske verstvih. Iz te temeljne zahteve se oblikuje širi temeljne etične spremembe, odprava revščine, preprečevanje vojn in nasilja, usmeritve, ki jih je mogoče najti v večini verstev: 1. Kultura izkoriščanje poceni delovne sile, zatiranje manjšin in obrobnih, nenasilja in spoštovanje vsakega življenja (Ne ubijaj oz. spoštuj migracije, pandemije ipd. kličejo po oblikovanju globalne etike. življenje!); 2. Kultura solidarnosti in pravično gospodarstvo (Ne Mirno sožitje, ki zagotavlja človeka vredno življenje, ni možno kradi oz. živi pošteno!); 3. Kultura strpnosti in življenje v resnici brez minimalnega strinjanja glede etičnih vrednot in drž. [2] (Ne laži oz. govori resnico in živi v resnici!); 4. Kultura enakih Pluralna družba, v kateri živijo skupaj pripadniki različnih religij pravic in partnerstva med moškim in žensko (Ne zagreši spolne in svetovnih nazorov, potrebuje temeljno soglasje glede nemoralnosti oz. spoštujte in ljubite se med seboj!). Avtorji osnovnih etičnih načel. Hans Küng je že v devetdesetih letih deklaracije spodbujajo posameznike v verskih skupnostih, da prejšnjega stoletja opozarjal, da je mogoče globalne probleme oblikujejo tudi svoj specifičen etos: »Naj povedo, kaj pravi rešiti samo s pomočjo skupnega svetovnega etosa. »Ni njihovo versko izročilo o smislu življenja in smrti, o vztrajanju v človeškega sobivanja brez svetovnega etosa narodov. Ni miru trpljenju, o odpuščanju krivice, o nesebičnem darovanju in med narodi brez miru med religijami. Ni miru med religijami nujnosti odpovedi, o sočutju in veselju. Vse to bo poglobilo, bolj brez dialoga med religijami.« [2] natančno opredelilo in konkretiziralo že prepoznani svetovni Prav na področju etike se v zadnjih desetletjih povezujejo etos.« [5] Na koncu je naslovljen apel na vse ljudi. Svet se bo strokovnjaki na različnih medverskih konferencah in projektih in spremenil na bolje samo, če bo prišlo do temeljitega in širokega iščejo skupno etično jedro vseh religij, ki bi bilo podlaga preoblikovanja moralne zavesti na individualni in družbeni ravni. pravičnejšemu in bolj humanemu svetovnemu redu. Etika 282 Veliko je podobnosti glede temeljnih etičnih načel med [9] V preteklosti je bil religijski pouk v večini držav različnimi religijami in kulturami, a kljub vsemu ne smemo konfesionalne narave, kar pomeni, da so posamezne verske idealizirati danega položaja. Dejansko obstajajo tudi skupnosti skrbele za to, da je pouk potekal v skladu z njihovimi nasprotujoče si moralne norme med različnimi kulturami. verskimi prepričanji in vzgajal učence za pripadnost njihovi Poglejmo samo norme, ki določajo vlogo ženske v družbi, norme verski skupnosti. Zaradi večreligijskega in večkulturnega glede verske strpnosti, glede oblik kaznovanja ali glede oblike konteksta prihaja do prenove na področju izvajanja religijskega vladanja. »Na usoden način je bila hotena konvergenca često pouka z namenom, da bi se učenci usposobili za življenje in onemogočena zaradi različnih načinov izražanja, zgodovinskih delovanje v raznoliki in pluralni družbi. Nekatere države so bolečin in zagrenjenosti ter zaradi pomanjkanja primernega konfesionalni pouk nadomestile z nekonfesionalnim (Danska, okolja za odprt dialog.« [6] Različne verske skupnosti imamo za Švedska, Velika Britanija), večinoma pa iščejo načine, kako bi seboj obremenjujočo prtljago iz preteklosti, ki v sogovornikih integrirale poznavanje drugih verstev in svetovnih nazorov v vzbuja odpor in nezaupanje. Krščanstvu se tako očitajo križarske uradno še vedno »konfesionalni« pouk. Eden od primarnih ciljev vojne, čarovniški procesi, zatiranje znanosti, diskriminacija religijskega pouka je tudi etična vzgoja, ki omogoča dialog in žensk in homoseksualcev … Pomembno je razčistiti s preteklimi sožitje med pripadniki različnih pogledov na svet. bremeni in poskušati razumeti določene pojave znotraj njihovega V zadnjih dvajsetih letih se je Svet Evrope večkrat izjasnil o zgodovinskega in kulturnega okolja. Hkrati je za globalno etiko nujnosti nepristranskega religijskega pouka v izobraževanju potrebno vzpostaviti polje zaupanja med vsemi udeleženci zaradi zagotavljanja mirnega in strpnega sožitja znotraj znotraj pluralnega sveta. Brez zaupanja ni mogoče zgraditi večkulturne in večreligijske družbe. Priporočilo 1720 o etičnih temeljev za prihodnost globalne družbe. izobraževanju in veri države članice spodbuja, da zagotovijo Univerzalnost etike je cilj, h kateremu stremimo in ga tudi pouk o religijah za vse učence na osnovnošolski in srednješolski sooblikujemo, ne pa že dano dejstvo. Nemogoče je točno ravni. Dokument poudarja, da sta »dobro splošno poznavanje določiti, katere so dejanske univerzalne moralne norme, hkrati pa religij in čut strpnosti, ki iz tega izhaja, bistvena za izvrševanje bi zanikanje normativne univerzalnosti vodilo v etični demokratičnega državljanstva.« [10] Zadnji dokumenti relativizem. Morajo torej obstajati utemeljene in brezpogojne ( Priporočilo 1962 iz leta 2011 ter Resolucija 2076 in Priporočilo moralne dolžnosti, ki jih je mogoče dokazati s pomočjo 2080 iz leta 2015) kažejo na obrat v stališčih Sveta Evrope do razumskega argumentiranja. Pri tem ne gre za razsvetljenski konfesionalnega religijskega pouka. Če so prejšnja priporočila ideal abstraktnega razuma ali za postopkovno racionalno dajala prednost nekonfesionalnemu religijskemu pouku, pa je sklepanje v smislu modernih naravoslovnih znanosti. Gre za sedaj izrecno povedano, da je tudi konfesionalni religijski pouk racionalnost, ki se zaveda povezave med normativno obvezo in združljiv z vzgojo za medkulturnost, če upošteva določene družbeno pogojeno izkušnjo smisla življenja in temeljnih smernice: medsebojno spoštovanje, zaščita človekovih pravic, vrednot. Na podlagi te racionalnosti ne bo mogoče postavljati demokracija, strpnost, sprejemanje razlik kot nekaj normalnega, absolutnih norm, ki bi veljale neodvisno od vsakega konteksta. skupen pogled v prihodnost. [11] Evropske institucije torej Za pravilno razumevanje potrebujemo hermenevtični pristop poudarjajo, da morajo tudi javne šole zagotoviti vsem učencem k etičnim vprašanjem: »Vsak ključni pojem je potrebno natančno določeno znanje o religijah in jih s tem pripravljajo na življenje opredeliti v svojem dejanskem pomenu.« [7] Etična pojmovanja v večkulturni in večreligijski družbi. Če je sprava prevladoval so zgodovinsko, kulturno in družbeno pogojena, zato je nujno, da poudarek na negativni verski svobodi, ki je državam nalagal, naj predstavimo pristen pomen posamezne etične norme ali etične v javnih šolah ne vsiljujejo nobenega (ne)verskega prepričanja, vrednote. Velikokrat pride do konfliktov zaradi napačnega pa je v zadnjem času opaziti bolj vključevalen odnos do religij in razumevanja pomena ali nepoznavanja kulturnega konteksta verskih skupnosti. Nevtralnost šole je mogoče doseči s določene etične opredelitve. Pri iskanju globalne etike je zato pluralnostjo pristopov in ne s splošnim izključevanjem religij. nujno, da kar se da upoštevamo zgodovinsko in kulturno ozadje Pouk o religijah in o religijskih dejstvih ima svoje mesto v javnih posameznih izjav. »Hermenevtika, ki se poglablja v življenjsko šolah in predstavlja pomembno razsežnost pri medkulturni okolje, ima za cilj, da bi zahtevo po zmožnosti univerzalizacije vzgoji današnjih otrok. [12] obvarovala pred tako uporabo, ki bi pozabila na zgodovinskost Številne iniciative na različnih ravneh znotraj evropskega in bi se zato izkazala za iluzorno.« [8] Uči nas skromnosti, svari prostora, ki v zadnjih dveh desetletjih poudarjajo pomen pred prehitrimi sklepi, da so neke norme univerzalne in da poznavanja religijskih vsebin za celostno vzgojo in presegajo kulturno pogojenost. izobraževanje v večkulturnem in večreligijskem okolju, v Če je naloga etike, da posreduje to, kar je lastno človeku, če Sloveniji niso dobile ustreznega odmeva in se jih v glavnem mu torej daje smernice, kako naj bi živel kot človek ne glede na ignorira. Zaradi napetost znotraj večkulturnih okolij potekajo v spol, raso ali družbeni položaj, potem etično razmišljanje nikoli različnih evropskih državah iniciative za spodbujanje ne more zapasti v popolno različnost, ki ne bi bila več združljiva. medsebojnega spoštovanja in globalne odgovornosti med Tudi v sodobni pluralni družbi še vedno obstaja nujnost, da preko mladimi. Ferrari ugotavlja, da vlada danes v Evropi širok argumentirane razprave o dobrem in slabem iščemo skupni konsenz tega, da morajo države in njihove šole v ta namen imenovalec naše človeške narave. okrepiti religijsko znanje. »Podajajo se vsaj naslednji štirje razlogi: (1) potreba, da se preseže religijsko neznanje, ki preprečuje razumevanje, in s tem neznanje o osrednji razsežnosti 3 POMEN RELIGIJSKEGA POUKA ZA osebnega in skupnega življenja (2) potreba, da se razume in na ETIČNO VZGOJO V PLURALNI DRUŽBI novo uredi religijsko pluralnost, ki zahteva znanje o različnih V veliki večini evropskih držav se etična vzgoja v javnih šolah religijah, npr. o islamu (3) potreba, da se sooči z vprašanjem o izvaja znotraj religijskega pouka oz. alternativnega pouka etike. smislu, ki postaja vedno bolj pereče po padcu velikih sekularnih 283 ideologij, in (4) potreba, da se vzgaja za državljanstvo, za družba v prihodnje bolj heterogena, kar predstavlja za področje vzajemno strpnost in za spoštovanje 'drugega'.« [13] Če želimo vzgoje in izobraževanja poseben izziv. Vsekakor mora šola poleg spodbujati oblikovanje globalne etike, potem je treba začeti pri znanja o tradicionalni religiji našega okolja predstaviti tudi vzgoji otrok, ki morajo poznati lastno izročilo in biti hkrati odprti osnove ostalih religij, predvsem tistih, ki imajo v Sloveniji večje za druge. Pri oblikovanju identitete posameznika in skupnosti število vernikov. Poznavanje nauka in običajev drugih verstev bo ima tudi v sodobni družbi religija še vedno svoje mesto, zato jo prispevalo k zmanjšanju predsodkov in k večjemu spoštovanju tudi javna šola ne sme preprosto ignorirati. soljudi. Treba je izpostaviti prispevek posameznih religij k Eden od zanimivih projektov, ki jih podpira EU, je tudi razvoju civilizacij, hkrati pa opozoriti tudi na konflikte in preoblikovanje vsebin pri religijskem pouka v Belgiji z napetosti med religijami v zgodovini in danes. Objektiven namenom, da bi se preprečila radikalizacija med mladih. Projekt vpogled v dejstva bo učencem pomagal razumeti pomen in vlogo nosi naslov »Educate to Build Resilience« in v njem kot partner religij za življenje posameznika in družbe in jih spodbudil, da ne sodeluje tudi Teološka fakulteta UL. [14] V Belgiji imajo dijaki glede na svojo religijo ali svetovni nazor gradijo raznoliko možnost izbire med petimi vrstami konfesionalnega religijskega skupnost v medsebojnem spoštovanju in odgovornosti. pouka (katoliški, protestantski, pravoslavni, judovski in islamski) ter nekonfesionalnim poukom etike. Projekt je REFERENCE zastavljen tako, da mladi pridobijo osnovno znanje o drugih [1] Immanuel Kant. 2003. Kritika praktičnega uma. Društvo za teoretsko religijah, kar naj bi spodbudilo medsebojno razumevanje in psihoanalizo, Ljubljana, 37. [2] Jože Trontelj. 2013. Etika kot most med znanostjo in vero. V: Roman sočutje (šest osnovnih modulov, ki dajejo temeljno znanje o Globokar, ur. Šola kot prostor dialoga med vero, znanostjo in vsaki religiji). Hkrati pa znotraj svoje skupine poglobijo umetnostjo. Zavod sv. Stanislava, Ljubljana. poznavanje svoje religije oz. nekonfesionalne etike zato, da bi [3] Hans Küng. 2008. Svetovni etos. Društvo 2000, Ljubljana, 187. [4] Hans Küng. 2006. Vorwort. V: Anton Grabner-Haider, ur. Ethos der bili bolj odporni na manipulacije s strani radikalnih skupin (štirje Weltkulturen: Religion und Ethik. Vandenhoeck & Ruprecht, Göttingen, poglobitveni moduli, ki kritično ovrednotijo izročilo posamezne 8. [5] Parlament der Weltreligionen. 1993. Erklärung zum Weltethos. 4. religije). Cilj takega pristopa je, da bi se mladi lahko identificirali september. http://www.weltethos.org/1-pdf/10- s svojo (ne)religijsko pripadnostjo, da bi bolje spoznali svoje stiftung/declaration/declaration_german.pdf (10. 9. 2020). izročilo in ga tudi kritično ovrednotili. Ob tem pa spoznavajo tudi [6] Will Kymlicka. 2007. The Globalization of Ethics. V: William M. Sullivan in Will Kymlicka, ur. The Globalization of Ethics, Cambridge izročilo drugih religij in se učijo dialoga in medsebojnega University Press, Cambridge, 2. spoštovanja ter med seboj oblikujejo prijateljske vezi. Prav [7] Klaus Demmer. 1999. Fundamentale Theologie des Ethischen. Studien zur theologischen Ethik, št. 82. Herder, Freiburg, 141. reševanje skupnih izzivov, kot so vprašanje varovanja okolja, [8] Klaus Demmer. 1999. Fundamentale Theologie des Ethischen, 105. pravična razdelitev dobrin, migracije, so priložnost za poglobitev [9] Conferenza Episcopale Italiana. 2008. L'insegnamento della religione risorsa per l'Europa: atti della ricerca del consiglio delle Conferenze medsebojnih odnosov in iskanje skupnih etičnih temeljev v Episcopali d'Europa. Elledici, Torino, 278–297. različnih religijskih in kulturnih izročilih. [10] Council of Europe, Parliamentary Assembly. 2005. Education and V zaključku ponavljamo predlog, da bi tudi v Sloveniji za vse religion, Recommendation 1720. http://assembly.coe.int/nw/xml/XRef/Xref-XML2HTML- učence v osnovni in srednji šoli uvedli nekonfesionalni religiozni en.asp?fileid=17373 (10. 9. 2020). pouk »religijska kultura in etika«, katerega glavni namen bi bil [11] Matej Pavlič. 2019. L'insegnamento della religione nelle scuole pubbliche nei Paesi della ex Jugoslavia. Edizioni Santa Croce, Roma, poznavanje izročil različnih religij in njihov pomen za osebno in 59. družbeno življenje v preteklosti in danes. [15] Poseben poudarek [12] Luce Pépin. 2009. Teaching about Religions in European School bi moral biti na vzgoji za medsebojno spoštovanje in oblikovanje Systems: Policy, issues, and trends. Alliance Publishing Trust, London, 52–54. http://www.nef-europe.org/wp- globalne etike. Opažamo namreč, da je religijska pismenost med content/uploads/2013/03/Teaching-about-religion_NEF-RelDem- mladimi v Sloveniji čedalje slabša, kar predstavlja nevarnost RELIGION-EDUCATION-Final.pdf (10. 9. 2020). [13] Silvio Ferrari. 2014. Teaching religion in the European Union: A legal krepitve predsodkov do ljudi, ki razmišljajo drugače. Že overview. V: Adam B. Seligman, ur. Religious education and the raziskava »REDCo«, ki je potekala med leti 2006 in 2009 v challenge of pluralism. Oxford University Press, New York, 26. osmih evropskih državah, je pokazala, da imajo mladi, ki ne [14] Educate to Build Resilience. http://reduc8.eu/ (10. 9. 2020). [15] Roman Globokar. Vzgojni izzivi v digitalni dobi. Teološka fakulteta, poznajo osnovnega znanja o religijah, mnogo več predsodkov Ljubljana, 139–146. pred drugače mislečimi in težje stopijo z njimi v stik. Večina [16] Religion in Education. A contribution to Dialogue or a factor of Conflict in transforming societies of European Countries. tistih dijakov, ki so imeli v šoli religijski pouk, je bolj odprta za https://cordis.europa.eu/project/id/28384/reporting (10. 9. 2020). pogovor o verstvih in svetovnih nazorih z učenci iz drugih okolij kot dijaki brez religijskega pouka. [16] Pri religijskem pouku šola pomaga učencu, da spoznava poglede posameznih religij na temeljna vprašanja in do njih oblikuje svoj odnos. V medreligijskem kontekstu sooči in preveri svoje lastno razmišljanje v odnosu do stališč drugih religij in prepričanj. V dialogu z drugače mislečimi se oblikuje njegova lastna identiteta. Drugi ga ne ogroža, ampak ga bogati in spodbuja, da prečiščuje svoj lastni pogled na svet. Bistveno pri vzgoji za medreligijski dialog je temeljno spoštovanje vsakega človeka, ne glede na to, ali se strinjamo z njegovim pogledom na svet ali ne. Zaradi sekularizacije, globalizacije, migracij, potovanj, digitalne povezanosti z vsemi deli sveta se spreminja tudi religijska podoba naše države. Predvidevamo, da bo slovenska 284 Etika in informatika Osebni pogled Niko Schlamberger Slovensko društvo INFORMATIKA niko.schlamberger@gmail.com informatiki ravnali neetično in tudi nezakonito, vendar niso bili POVZETEK člani društva in zato društvo ni reagiralo. Prispevek podaja razmislek o kodeksih etike. V začetku Dejavnost društva na področju etike pa se ni omejila zgolj prikazuje zgodovino sprejemanja etičnega kodeksa na sprejetje kodeksa etike. Do leta 2014 je organiziralo Slovenskega društva INFORMATIKA. V nadaljevanju se samostojno ali v sodelovanju šest posvetov Etični forum dotakne etike kot take, nekaterih primerov, čigava je informacijske družbe, na katerih so udeleženci predstavili svoje odgovornost poleg tiste, ki jo imajo strokovna združenja, na poglede in razpravljali o aktualnih vprašanjih etike v koncu pa podaja še nekaj misli, kako bi lahko ravnali v informatiki in družbi sploh. Zbornik šestega foruma povzema prihodnje. dejavnost društva na področju etike. V tem poglavju predstavljen oris prizadevanj društva na področju etike bi bil pomanjkljiv, če ne bi omenili dr. Marjana KLJUCNE BESEDE Krisperja, ki je dal pobudo, da je društvo sprejelo prvi etični etika, informatika kodeks, in pri ACM izposloval, da je slednji dovolil uporabo svojega kodeksa za potrebe društva. Drugi, ki ga prav tako ne 1 UVODNA POJASNILA gre spregledati, je mag. Franci Pivec, ki je bil glavni avtor sedaj veljavnega etičnega kodeksa društva. Oba, dr. Krisper in mag. Predvsem naj na samem začetku pojasnim, da sem aktiven na Pivec, sta bila tudi predstavnika društva v tehničnih odborih področju računalništva in informatike že dolga desetletja, International Federation for Information Processing (IFIP). vendar moja ožje področje delovanja etika ni bila. Prvič sem se z njo bliže srečal, ko sem bil prvič izvoljen za predsednika Slovenskega društva INFORMATIKA. Na enem od sestankov 2 ZA KAJ V BISTVU GRE PRI ETIKI? izvršnega odbora je bila izrečena – in seveda brez nadaljnjega Poklicna etika ima dolgo zgodovino. Verjetno prvi uveljavljeni tudi sprejeta - pobuda, naj društvo sprejme kodeks poklicne kodeks poklice etike je prisega, ki se ji mora prikloniti vsak etike. Pri tem se je naslonilo na ameriško združenje Association mlad zdravnik. Pripisujejo jo starogrškemu zdravniku for Computing Machinery (ACM) kot vidno tehnično Hipokratu s Kosa in je zato znana kot Hipokratova prisega. Z profesionalna organizacijo, ki je prijazno dovolilo, da njen njo so bila postavljena načela zdravniškega poklica, ki so, če kodeks društvo uporabi, seveda ne v izvirni obliki. Preveden je odštejemo navajanje grških bogov, spoštovana še danes. bil v slovenščino, nekoliko prilagojen slovenskim razmeram in Verjetno najbolj splošno znano načelo je Primum non nocere sprejet leta 1998. Poleg tega je imenovalo še disciplinsko 1. Kakor so nastajali novi poklici, tako je postajala očitna tudi komisija, ki je imela nalogo in pristojnost obravnavati primere potreba, da se strokovnjaki držijo poleg poklicnih tudi etičnih kršenja kodeksa. Prvi kodeks društva je bil obsežen, štel je norm. Pri etiki gre v bistvu za osebne odločitve, ki vplivajo na namreč kar osem strani, dotikal pa se je področij, ki niso druge. Ni namreč vse, kar je tehnično izvedljivo in pravno neposredno predmet etičnih razmislekov. dopustno, tudi etično sprejemljivo. Etična norma pove, kaj je Zaradi obsežnosti besedila je bila kasneje sprejeta pobuda, da bi kodeks poenostavili tako, da bi obravnaval le etična vprašanja, ne bi se pa dotikal področij, ki so urejena s statutom, kot na primer kdo lahko postane član društva, kakšne so njegove dolžnosti in pravice in podobno. Leta 2010 je društvo sprejelo nov kodeks, ki je bil že izvirno delo. Ta kodeks šteje tri strani in velja še danes. Za etično presojo morebitnih etično spornih primerov je bila imenovana petčlanska etična komisija iz vrst zaupanja vrednih oseb. Vredno je poudariti, da vse od sprejetja prvega kodeksa do časa pisanja tega prispevka ni bil obravnavan niti en primer nespoštovanja etičnega kodeksa društva. Vprašanje je sicer, ali v resnici ni bilo primera, ki bi zaslužil obravnavo pred etično komisijo, vendar je treba vedeti, da velja kodeks etike le za člane društva. Znanih je nekaj razvpitih primerov, ko so 1 Predvsem ne škodovati. 285 javni razpisi vključevali klavzulo, ki bi zahtevala, da izvajalci predstavijo svoj etični kodeks. 3 KAKO NAPREJ Vsi se zavedamo, da je varnost pomembna v vsakdanjem življenju, tako organizacije na splošno kot organi oblasti. Državljani zaščitimo svoje premoženje na različne načine z namestitvijo različnih varnostnih naprav v domove, avtomobile in drugo premoženje. Poleg tega organizacije najemajo varnostne službe, da čim bolj povečajo svojo varnost. Oblasti razumejo nujnost varovanja, zato imamo zakone, policijo, vojsko in podobno. Toda takoj, ko vstopimo v kibernetski prostor, se razmere spremenijo - žal ne na bolje za nas. Smo sami. Nekatere države, na primer Slovenija, so odprle portale, na katerih lahko državljani prijavijo poskuse ali zlorabo svojih podatkov ali denarja. Ne vem, kako deluje drugje, toda v tu, ko prijavim poskus zlorabe, je odgovor: Hvala, ker ste prijavili incident. Moja reakcija je, Hvala za tako storitev! Kot da bi Slika 1: Hipokrat (460–370 pr. Kr.) prišli na policijo in jim povedali, da so vas napadli, policija pa bi se vam zahvalila, da ste jim to povedali. Sporočilo je jasno: prav, zato so lahko dejanja neetična, tudi če so pravno prestopniki jo bodo vsaj v primeru spletnega kriminala poceni neoporečna, da tehnične izvedljivosti niti ne omenjamo. odnesli, saj so oškodovanci praviloma napoteni na zasebni Zgornji razmislek nas spomni na neštevilne primere, ki smo pregon. jih doživljali sami in pri katerih se gre zahvaliti verjetno le Bistvo je, da gre za odgovornost. Ljudje smo osnovna slučaju, da nismo bili močno oškodovani. Pri tem mislim na kategorija in za svoje boljše in varnejše življenje smo ustanovili sporočila po elektronski pošti, ki so zlonamerna na različne države, vlade in oblasti. Imamo pravico zahtevati, da smo varni načine: izsiljevanje, črvi, virusi in podobno. Skupni imenovalec tako v vsakdanjem svetu kot v kibernetskem prostoru. Osnovno je vdor v zasebnost. Glede tega so vlade bolj odzivne kot na vodilo je, da tisto, kar v resničnem svetu ni dovoljeno, ne sme področju varnosti, vendar se bojim, da poudarek ni v pravi biti dovoljeno tudi v virtualnem svetu. V tem pogledu države smeri. Večinoma so države sprejele neke vrste zakone o varstvu niso storile dovolj. Naslednji, ki morajo opraviti domačo podatkov, osebnih ali drugačnih, vendar je jih je težko izvesti nalogo, so ponudniki storitev. Kako je mogoče, da v svojo e- in še težje uveljaviti. pošto prejemamo izsiljevalska sporočila, viruse, črve in vse Moramo razumeti, da se zasebnost konča, ko zapustimo vrste nevarnih kod, tudi če je na voljo množica programske zasebne prostore. Na javnih mestih lahko zahtevamo osebno opreme za preprečevanje tega? Vlade bi morale uvesti stroge integriteto, da ne bomo fizično nadlegovani, verbalno napadani zahteve, ki bi ponudnike storitev zavezovale, da varujejo račune in podobno zlorabljani, vendar se v javnosti ne moremo svojih uporabnikov vsaj tako, kot varujejo svoje. pretvarjati, da smo nevidni ljudje. Lahko smo fotografirani in spremljani na javnih mestih, prvič, ker nismo doma, in drugič, 4 NAMESTO ZAKLJUČKA ker to pomembno poveča našo varnost v javnosti. Vsi vemo (a komaj kdaj priznamo), da je vsa naša komunikacija Če pogledamo po svetovnem spletu, bomo našli množico nadzorovana in registrirana, bogve kje in kolikokrat, začenši z kodeksov etike, vprašanje pa je, ali jih je res toliko potrebnih. Echelonom v sedemdesetih letih, ki je bil od takrat večkrat Verjetno je nekaj poklicev, ki jih ne moremo stlačiti v nadgrajen. Resnično verjamem, da ni izgubljena bitka, ampak Prokrustovo posteljo brez škode za njihovo izvajanje in vojna za zasebnost. Tega sicer nisem vesel, ampak takšno je dobrobit izvajalcev. Na misel pridejo zdravniki, pravniki, življenje. Torej bi se moral zakon osredotočiti na sankcioniranje učitelji in še kdo, vendar pa večina poklicev ni tako posebnih, zlorabe osebnih podatkov in ne na predpisovanje dovoljenega da ne bi mogli najti etičnega skupnega imenovalca. Kaj je na zbiranja, roke hrambe in podobno. Sankcija bi morala biti primer tako posebnega pri gradbenikih, da ne bi mogli uporabiti dovolj stroga, da bi tistim, ki bi kršili zakon, zmanjkalo posla. kodeksa elektrotehnikov ali strojnikov? Preprosto temu rečemo preventiva. Druga misel, ki se porodi, je, da so kodeksi poklicne etike v Obe zgoraj omenjeni problematiki imata skupni imenovalec splošnem predolgi in preobsežni. Urejati poizkušajo vse znane - etika. Poklicna združenja so večinoma sprejela etične in bodoče primere kršenja etičnih norm, vendar je žal tako, da kodekse, vztrajati pa morajo tudi, da njihovo članstvo spoštuje več, ko je napisanega, več ostane nenapisanega. Glede presoje sprejete etične kodekse. Zelo verjetno v glavnem ni tako. etičnega ravnanja bi morali pač zaupati tistim, ki so jih Pravzaprav obstajajo oglasi in celo konference o etičnem organizacije za to izbrale. hekanju. Po mojem prepričanju je to protislovno. Ali lahko kdo Tretje, kar bi bilo mogoče predlagati, je, da bi oblasti pri zdravi pameti pomisli na etični vlom, etično krajo ali kakšno preganjale tovrstni kriminal po uradni dolžnosti. Dejansko gre drugo etično kaznivo dejanje? Vse to se dogaja v javnosti, kljub za kriminal in odnos države do njega bi moral biti enak kot v temu pa oblasti, širša javnost in še najmanj strokovna združenja primerih klasičnega kriminala. ne reagirajo. Verjamem, da bi se položaj znatno izboljšal, če bi 286 VIRI 371X. http://library.ijs.si/Stacks/Proceedings/InformationSociety/2019/IS2 019_Volume_D%20-%20Etika%20in%20stroka.pdf. [COBISS.SI- [1] www.acm.org (obisk 21.9.2020) ID 302452992] [2] Schlamberger, Niko. IFIP TC-11 2020 International Information Security [6] Etični forum informacijske družbe (6 ; 2014) and Privacy Conference (Address) Informacijska družba po Snowdnu [Elektronski vir] : [zbornik razprav [3] Zapisniki sej izvršnega odbora Slovenskega društva INFORMATIKA in prispevkov (interna gradiva društva) v okviru 1. kolokvija Mediji v informacijski družbi] / 6. etični forum [4] Osebni zapiski avtorja informacijske družbe [5] KRISPER, Marjan (urednik), PIVEC, Franci (urednik), GAMS, Matjaž [in] 1. kolokvij Mediji v informacijski družbi ; uredniki József Györkös, (urednik). Etika in stroka : zbornik 22. Mednarodne multikonference Melita Zajc, Informacijska družba - IS 2019, 9. oktober 2019 : zvezek D = Smiljana Gartner. - El. zbornik. - Maribor : Fakulteta za elektrotehniko, Professional Ethics : proceedings of the 22nd International računalništvo in Multiconference Information Society - IS 2019, 9 October, 2019, informatiko, 2014, ISBN 978-961-248-452-1 Ljubljana, Slovenia : volume D. Ljubljana: Institut "Jožef Stefan", 2019. 1 spletni vir (1 datoteka PDF (40 str.)). Informacijska družba. ISBN 978- 961-264-161-0, ISBN 978-961-264-162-7. ISSN 2630 287 288 Zbornik 23. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2020 Zvezek E Proceedings of the 23rd International Multiconference INFORMATION SOCIETY – IS 2020 Volume E 13. Mednarodna Konferenca o prenosu tehnologij – 13. ITTC 13th International Technology Transfer Conference – 13 ITTC Uredila / Edited by Špela Stres, Robert Blatnik http://ittc.ijs.si 8. oktober 2020 / 8 October 2020 Ljubljana, Slovenia 289 290 PREDGOVOR Spoštovana ministrica, spoštovani direktor, dragi kolegi, prijatelji, sodelavci pri prenosu znanja in tehnologije! Prisrčna dobrodošlica tudi iz Centra za prenos tehnologij in inovacij na Institutu »Jožef Stefan«. To je četrti dogodek Konzorcija za prenos tehnologij v Sloveniji, ki ga sestavlja 8 pisarn za prenos tehnologij. Sodelujemo že skoraj 3 leta. Hvaležni smo Ministrstvu za izobraževanje, znanost in šport, da je priznalo poklic za prenos tehnologije in zagotovilo petletni projekt za podporo našim dejavnostim. To sodelovanje praznujemo. Rada bi se zahvalila vsem 8 partnerjem v konzorciju, ki so prispevali po svojih zmožnostih. Lepa hvala tudi ostalim konferenčnim partnerjem, ki so skušali prispevati po najboljših močeh. Prav tako bi se rada zahvalila našemu direktorju za njegovo stalno podporo v vseh letih. Čeprav smo bili pogosto prepuščeni svojim zmožnostim, smo jih smeli uporabljati v korist inštituta in tehnološkega prenosa na inštitutu. Tudi ta konferenca je rezultat tega popustljivega okolja, ki je podprlo razvoj vseh področij. To je 13. Mednarodna konferenca o prenosu tehnologij po vrsti. Od nekdaj se je prilagajala duhu časa, saj je vključevala ugledne mednarodne govornike, predstavitve industrijskih tehnologij in nagrade za najboljše inovacije raziskovalnih organizacij. Te nagrade so bila skozi leta podeljena več različnim slovenskim raziskovalnim institucijam, od katerih so mnoge sedanji partnerji našega konzorcija TTO. Skozi vsa leta je konferenca vključevala tudi B2R srečanja, na katerih so raziskovalci in podjetja lahko razpravljali o konkretnih vprašanjih. Vključevala je okrogle mize za soočanje različnih mnenj in raziskovalne predstavitve, ki so prikazale vrhunske slovenske znanstvene rezultate. Konferenca je tako raznolika in prav je tako, saj poskuša vključiti vse segmente, ki so ključni za izvedbo znanja in prenos tehnologije. Vendar se še vedno najdejo novi izzivi, s katerimi se lahko spoprimemo. Danes bo Svetovni urad za intelektualno lastnino na tem dogodku podelil dve mednarodni nagradi - IP Enterprise Trophy in medaljo WIPO za izumitelje. Zahvaljujemo se WIPO za prijazno podporo in soorganizacijo dogodka ter se zahvaljujemo slovenskemu uradu za intelektualno lastnino, ki je to sodelovanje omogočil. Druga novost konference je rubrika z znanstvenimi prispevki o prenosu tehnologij. Pomembna je, saj si prizadevamo izboljšati učinkovitost prenosa tehnologije. Pri teh prizadevanjih je potreben objektiven pristop, ki se ponuja z znanstvenim načinom razmišljanja - spodbuja analizo, razprave na podlagi podatkov in se podaja v neznano, kjer še vedno veliko vprašanj ostaja neodgovorjenih. Na primer, predlagani novi slovenski zakon o raziskavah, razvoju in inovacijah uvaja nove spodbude za sodelovanje z industrijo in sodelovanje v projektih EU. Toda zakaj bi bolj spodbujali sodelovanje v projektih EU kot sodelovanje v industrijskih projektih? Kaj natančno šteje za sodelovanje z industrijo? Kakšna naj bi bila odslej vloga spodbud, ki temeljijo na 291 komercializaciji, ki so bile na voljo do zdaj? To so pomembna vprašanja, na katera je treba odgovoriti pred izvajanjem nove zakonodaje. Prav tako je v novi zakonodaji mogoče zaznati dejavnosti prenosa tehnologije, kar je zelo pozitivno sporočilo. Ampak, ali zakon dejansko opisuje TTO z vrsto strokovnjakov? Ali pa je treba financiranje med raziskovalci na tanko razporediti, da bi se sami ukvarjali s svojimi odnosi med industrijo in akademskim svetom? Kot je povedala gospa ministrica, je ministrstvo pripravljeno podpreti izvajanje instrumenta TTO tudi v naslednjem finančnem obdobju in to pozdravljamo. Ministrstvo pozivamo, naj v predlagani novi zakonodaji jasno formalizira TTO in naj pravočasno predstavi svoje konkretne načrte za poklic prenosa tehnologije v Sloveniji, da bodo TTO neprekinjeno delovale. Naj na koncu poudarim še, da sta znanost in prenos tehnologije dolgoročni dejavnosti. Naši današnji rezultati v glavnem niso v našo korist takoj, ampak v korist družbi, v kateri želimo, da živijo naši otroci. Zato moramo visoko ceniti duh skupnosti, si prizadevati za svojo popolnost, hkrati pa pomagati tudi drugim, da jo dosežejo . Hvala vam. Dr. Špela Stres, MBA, LLM, Vodja Centra za prenos tehnologij in inovacij, Institut Jožef Stefan, vodja organizacijskega odbora konference 13. ITTC 292 FOREWORD Dear Minister, dear Director, dear colleagues, friends, co-workers of transfer of knowledge and technology! A kind welcome also from the Center of technology transfer and innovation at the Jožef Stefan Institute. This is the 4th event of the Consortium of Knowledge and Tech-transfer in Slovenia, comprising 8 Tech-Transfer Offices, which have been collaborating now for almost 3 years. We are grateful to the Ministry of Education, Science and Sports to have acknowledged the tech-transfer profession and secured a 5-year project to support our activities. We celebrate this collaboration. I would like to thank all 8 partners in the consortium, each has contributed according to their capacity. Warm thanks also to the other conference partners who tried to contribute in any way possible for them. I would also like to thank our director for his continouing support throughout the years. Although we were mainly left to our own devices, we were allowed to use them for the benefit of the institute and the tech-transfer at the institute. Also this conference is a result of this permissive environment, who supported development of all fields. This is the 13th International Technology Transfer Conference in a row. It has always adjusted to the spirit of the time, by including distinguished international speakers, Pitch Presentations of Industry ready Technologies, and the Awards for best innovation from research organizations. These awards have been through the years awarded to several different slovenian research institutions, many of them current partners of our TTO consortium. Throughout the years the Conference also included the B2R Meetings where researchers and businesses could discuss concrete issues. It included Round Tables to confront different opinions and Research Presentations to show off with the superb Slovenian scientific results. The Conference is so diverse, and it is so, because it tries to incorporate all segments, crucial for the execution of the knowledge and tech-transfer. However, there are still new territories to venture to. Today, the World Intellectual Property Office will bestow two international Awards at this event – IP Enterprise Trophy and WIPO Medal for Inventors. We thank WIPO for their kind support and co-organization of the event, and we extend our gratitude to the Slovenian IP Office, who made this collaboration possible. Another novelty of the conference is the Section with scientific contributions on tech-transfer. The section is important, as we strive to improve efficiency in tech-transfer. In that effort an objective approach is needed, and it is offered through the scientific way of thinking – it encourages analysis, data based discussions, and venturing into the unknown, where still many questions lay unanswered. For example. The proposed new Slovenian Law on research, development and innovation introduces new incentives for cooperation with the industry and for collaboration in the EU projects. But why a higher impetus for EU than for industry project collaboration incentives? What exactly counts as a cooperation with the industry? What should from now on be the role 293 of the commercialization based incentives that were in place so far? These are important questions to be answered before the implementation of the new legislation. Also, one can sense the tech-transfer activities in the new legislation, which is a very positive message. But, is the law actually outlining a TTO with a set of experts? Or is the financing to be thinly spread among the researchers to deal themselves alone with their industry-academia relations? As the Lady Minister said, the Ministry is willing to support the implementation of he TTO instrument also in the next financing period and this is a very positive message. We urge the Ministry to clearly formalize the TTOs in the proposed new legislation, and to lay out their concrete plans for the tech-transfer profession in Slovenia in time for the TTOs to operate continously. To conclude, science and tech-transfer are long term activities. The results we produce today are mainly not for our own immediate benefit, but for the society we want our children to live in. Thus we need to value highly the spirit of the community, strive for our own perfection, but also assist others in reaching it. Thank you. Dr. Špela Stres, MBA, LLM, Head of the Center for Technology Transfer and Innovation, Jožef Stefan Institute, Head of Organizing Committee of the 13 ITTC 294 ORGANIZACIJSKI ODBOR, PRIDRUŽENI PARTNERJI IN SPONZORJI / ORGANIZING COMMITTEE, ASSOCIATED PARTNERS AND FINANCERS The main organizer of the 13th ITTC Conference is Jožef Stefan Institute. The organizing committee: Dr. Špela Stres, MBA, LLM, Jožef Stefan Institute Doc. dr. Urška Fric, Faculty of Information Studies in Novo Mesto Robert Blatnik, M. Sc., Jožef Stefan Institute Marjeta Trobec, M. Sc., Jožef Stefan Institute The 13th ITTC Conference is organized in collaboration with the International multiconference Information Society (IS2020). The 13th ITTC Co-organization partners are: Slovenian Intellectual Property Office (SIPO) World Intellectual Property Organization (WIPO) 295 Chamber of Craft and Small Business of Slovenia SPIRIT Slovenia - Public Agency for Entrepreneurship, Internationalization, Foreign Investments and Technology Faculty of Information Studies Novo mesto Agricultural Institute of Slovenia Slovenian association of technology transfer professionals (SI-TT) The 13th ITTC Associated partners are: National Institute of Chemistry National Institute of Biology 296 University of Primorska University of Maribor University of Ljubljana Scientific research centre Bistra RDA Koroška - Regional Development Agency for Koroška Regional Development Agency Posavje Development Centre Novo mesto University of Malta 297 Center for Technology Transfer, University of Belgrade SIS EGIZ Centre of Excellence for Integrated Approaches in Chemistry and Biology of Proteins IP Management Poland GIS – Transfer Center Foundation Slovenian Innovation Hub - European Economic Interest Grouping, SIH EEIG 298 The Research-to-business meetings at the 13th ITTC Conference were co-organized in collaboration with the Enterprise Europe Network partners: Chamber of Craft and Small Business of Slovenia SPIRIT Slovenia - Public Agency for Entrepreneurship, Internationalization, Fore­ign Investments and Technology University of Primorska University of Maribor Chamber of Commerce and Industry of Slovenia Area Science Park Austrian Research Promotion Agency 299 Innovation Center of the Faculty of Mechanical Engineering in Belgrade Ss. Cyril and Methodius University in Skopje Fundación para el conocimiento madri+d AECIM - Empresas del Metal de Madrid Fundació Universitat-Empresa de les Illes Balears (FUEIB) Tera Tehnopolis Not Enterprise Europe Network partners: ITC – Innovation Technology Cluster DIH Agrifood – Digital Innovation Hub for Agriculture and Food production 300 The Conference is co-financed by: Consortium for Technology Transfer Enterprise Europe Network 301 302 A decade of Knowledge Transfer in Slovenia Desetletje prenosa znanja v Sloveniji Špela Stres Levin Pal Center for Technology Transfer and Innovation Center for Technology Transfer and Innovation Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39, Ljubljana Jamova cesta 39, Ljubljana Spela.Stres@ijs.si Levin.Pal@ijs.si ABSTRACT periods in which the Slovenian governments attempted to In this paper, we describe the last decade of the Knowledge manage IPR collectively, using different mechanisms, through Transfer development in Slovenia. Knowledge transfer is based Technology Transfer Offices (TTOs). These were the periods of on the development of legislative tools, governmental financial 2009-12, 2013-2014 and 207-2019 (the instrument is active tools and performance of the Public Research Organizations in until June 2022, not yet completed). Slovenia. The overview shows and evaluates in numbers what Since the independence of Slovenia in 1991, a particular has been achieved. It also presents the fields in which legislative system with respect to public research generated IPR knowledge transfer experts will have to act further in has been established. The legislative system, in the case of collaboration with Government, Professional Associations and Slovenia affects the strength and the quality of a national IP Public Research Organization (PRO) leaderships. Conclusions management regime. are drawn to suggest further steps on the path of KT development in Slovenia. 2. THE LEGISLATIVE CONTEXT Keywords 2.1 Slovenian legislative context The Republic of Slovenia has established universities and spin-off, spin-out, R&D contracts, Intellectual Property Rights public research institutes (PRIs) with Institutes Act (1991) [2] (IPR) sales, legislation changes, public research organizations, and The Higher Education Act (1993) [3]. Financing of boundaries, conditions, technology transfer, eco-system research work on universities and PRIs (jointly named Public Research Organizations, (PROs)) is implemented with the POVZETEK assistance of the Slovenian Research Agency in accordance with V prispevku opisujemo zadnje desetletje razvoja prenosa znanja various regulations [4]. v Sloveniji. Prenos znanja temelji na razvoju zakonodajnih orodij, vladnih finančnih orodij in raziskovalni uspešnosti The researchers compete for the financing of their research javnih raziskovalnih organizacij v Sloveniji. Pregled v številkah plans. They do so in regular time intervals (every year for prikazuje in ocenjuje, kaj je bilo doseženega. Nudi tudi vpogled projects, every four to six years for programmes). Evaluation of v področja, kjer bodo v prihodnje strokovnjaki za prenos znanja the proposals is done on the basis of certain criteria. Thus, it is v sodelovanju z vladnimi, strokovnimi združenji in vodstvi possible to claim that the financing of research from the public javnih raziskovalnih organizacij (JRO) morali nadgraditi budget is project and programme organised. To a certain dosedanja prizadevanja. Sklepne ugotovitve predlagajo degree, such a frequent selection and unavailability of stable nadaljnje korake na poti razvoja KT v Sloveniji. long-term financing should support positive selection in the research sphere and enable researchers to work creatively in a Ključne besede relatively secure environment.1 spin-off, spin-out, pogodbe za raziskave in razvoj, prodaja With the Act on inventions arising from employment (1995) pravic intelektualne lastnine, spremembe zakonodaje, javne [5], the Republic of Slovenia has introduced an arrangement raziskovalne organizacije, meje, pogoji, prenos tehnologije, similar to the Bayh-Dole Act of the USA. The inventions arise ekosistem from PROs. All the inventions resulting from the state budget financing, are owned and managed by the PROs. Certain conditions regulate the management of the mentioned 1. INTRODUCTION inventions. These conditions need to be met, for the PROs to Slovenia is a small country with 2 million inhabitants in Central become the owner of the actual invention. These conditions are Europe and 6980 registered researchers [1], the 19th in thus described in Article 21 and 22 of the Act on inventions arising measured research strength out of 127 evaluated countries. from employment and are related to the Industrial Property Act. The efficiency of the Intellectual Property Rights (IPR) All EU member states (except Italy and Sweden) – manage their management system in a country can be evaluated through the inventions in the way the Republic of Slovenia does, with successful commercialization of patents and secret know-how respect to the responsible PROs. The state renounces the right originating from Public Research Organizations. The of ownership of the inventions in favour of the PROs. commercialization is taking place through new company Consequently, these PROs, as legal entities, are also responsible creation, IPR licensing and sales and direct R&D collaboration for commercialization of inventions. Researchers are not with companies. personally responsible for the commercialization of inventions, The efficiency of the IP management system in Slovenia can be 1 sought from a comparison of the results of three separate time- The status of researchers as civil servants and the absolute impact of the ARRS selection system are not discussed here. 303 but may capitalize financially (in Slovenia minimum is in the Unfortunately, such offices have not been given further amount of 20 % of the gross related PRO income) in case of legitimacy until 2011, when the Resolution on Research and successful commercialization takes place. The researchers are Innovation Strategy 2011-2021 [9] Slovenia has been adopted. thus incentivized to participate, and practically all PROs in Therefore, IPR in PROs was typically generated on a day-to- Slovenia nowadays have internal PRO Acts distributing the day basis without proper assessments of it being made, without benefits defined by the law. commercialization procedures having been considered. With the Supportive Environment for Entrepreneurship Act The question of IPR for the market has been raised several (2007) [6] and the accompanying Record on Keeping Rules on times through the years, but since there was little interest in the Innovative Environment [7]) a legal base for a supportive looking at this problem from an integrative point of view, environment for innovation was created in Slovenia. integral solutions were not implemented for almost another Entrepreneurship incubators, university incubators and decade. technology parks were explicitly mentioned in Article 2 of the Record on Keeping Rules on the Innovative Environment. Each 3.2 The institutional level of those supportive organizations was supposed to, in a manner PROs in Slovenia were very agile in collaboration with the described in the Record, support development and cooperation industry during the 1970’s and 1980’s. This resulted in some of the start-up and young enterprises. Technology transfer very early adoptions of internal Acts on acquiring and offices were mentioned by the Record on Keeping Rules on the management of the IPR by the PRO, which enabled at least Innovative Environment but were not financed through being incentivizing the researchers with rewards on IPR production (if part of the listed entities by the same Record. not management of IPR). The quickest to act was Institute of Last but not least, based on the Industrial Property Act (2001) Chemistry (KI) in 1979, followed by Jožef Stefan Institute (JSI) [8] the Slovenian Intellectual Property Office (Article 5 of the in 1998, University of Ljubljana (UL) in 2006, National Industrial Property Act) was founded, with the main function to Institute of Biology (NIB) in 2007, University of Maribor (UM) accept patent and other intellectual property right applications, in 2009, University of Primorska (UP) in 2010 [10]. All such manage the related procedure, related registers of rights, Institutional Acts underwent several changes through the years. provide information services and represent the Republic of Unfortunately, the PROs were not quick to pick up the pace Slovenia at WIPO, EPO and other international organizations. with IPR management, to enable systematic, sustainable and consistent management of IPR generated, and to prevent any 3. TECHNOLOGY TRANSFER issues, as defined in relevant competition, integrity and OFFICES corruption legislation. In a substantial proportion, the Slovenian science and research The PROs were creating TTOs at different times and with activity is financed from public funds - in part from the national different efficiencies. The first TTO in Slovenia was founded at public budget, partly from the EU budget (European projects). JSI in 1996, followed by UM in 2005, University of Ljubljana A considerable proportion of the funding also comes directly in 2007, KI in 2010 (first jointly with JSI, then separated in from the Slovenian enterprises, which are the generator of 2012), UP in 2010, NIB in 2010, Agricultural institute of public budget. Slovenia (KIS) in 2015, Faculty of Information Studies Novo mesto (FIŠ) in 2017 Therefore, the public research organizations (PROs) are well [11], [12]. aware of the fact that the increase in competitiveness of the Several of the TTOs changed their organizational structure to Slovenian economy also depends on the quality of the become more agile and to be able to sustain themselves. Some cooperation between science and industry. several times, formal incorporations ranging from an outside However, looking at the commercialization side of Intellectual company 100% owned by the University, through a separate Property Right (IPR), in the end of the first decade of the 21st and financially independent Unit of an Institute to an office or a century, it was obvious that the knowledge and technology section within some other entity (the Rectorate of the transfer potentials were not being fully exploited. The reasons University, a Faculty or an incorporated Institute of the could be sought in the less developed parts of the innovation University). support system – the intermediaries, which would assist in the commercialization of IPR – the Technology Transfer Offices 3.3 The EU context (TTOs). The Framework for Research, Development and Innovation suggests that the field of establishing new enterprises, arising 3.1 The governmental level from the knowledge, developed at the research organizations, The legal framework for active management of the IPR should be regulated. According to this Framework, generated by the PRO, has been set during the period of 1991- commercialisation via spin-offing is allowed (and desirable), if 1995. The transfer of knowledge and inventions to the market the profits from commercialisation activities are provided as should have been, by law, since 1995, supported by the PROs funds for further research activities. themselves. In particular the PROs should have been managing On the other hand, European and domestic competition law the IPR, generated/owned by the PROs. In practice the prohibit anti-competitive agreements. Thus, any anti- management and transfer activities should have been actively competitive provisions in commercial agreements are void and carried out by the entities, defined by legislation through the unenforceable which could lead to the entire agreement being Act on inventions arising from employment. These entities are unenforceable. However, the European Commission has called the technology transfer offices (TTO) of the PROs. In produced a number of so-called block exemptions which make addition, the Offices of technology transfer were in explicitly certain 'safe harbours' available to companies. mentioned in the Record on Keeping Rules on the Innovative Environment. The Technology Transfer Block Exemption (TTBER [13]) covers technology licensing agreements in relation to most intellectual property rights (IPRs), providing a safe harbour to 304 companies active in this business area and in business relations 4.2.3 KTT-2 project: 2017-2022 with Public Research Organizations (PROs), too. If an A long three-year period followed with no financing. During agreement falls within the terms of this block exemption, the that time the Association of Technology Transfer Professionals companies concerned can be confident that it will not be subject of Slovenia (Association SI-TT) tirelessly tried to intervene to scrutiny. with the Ministry of Science, the Ministry of Economy and the Furthermore, "Commission Recommendation on the Government Office for Development and European Cohesion management of intellectual property and knowledge transfer Policy, for the KTT project to be renewed and the TTOs to be activities and Code of Practice for universities and other public financed again. This difficult period was intermittent only by research organizations", requests the establishment of control harsh and belligerent negotiations among the existing TTOs. over the performance of technology transfer activities to the The negotiations were initiated by the JSI, but were difficult to industry, which since 2013 EC countries, including Slovenia, lead due to different and partially articulated points of view. are recommended to follow. There was a period of genuine despair due to government’s focus on the NUTS3 division of the funds, and the 4. THE FINANCING OF THE TTOs unwillingness to introduce an umbrella accounting, which 4.1 The lack of dedicated financing would affect KTT as operating throughout the country (instead of in a particular NUTS3 region). During this period, with no Even though changes have been observed during the first clear framework and leadership from the side of the decade of the 21st century, in European and national legislation, government, the idea of the exclusionary operation of a possible the problem of operationalization of TTOs through dedicated new consortium grew among some TTOs. The idea was that financing in fact remained open. A situation at the end of the some TTOs would be members, others would be left out. first decade of the 21st century was still a gross neglect of the Consequently, the willingness of partners to rationally check TTOs and their activities by the government. their capacity, capabilities and achievements with the aim of On the one hand this forced most TTOs to have only 1 or two cooperation remained low, the uncertainty caused the tensions employees, mainly dealing with other issues of the institution and the competition among the partners to grew. The actions of (e.g. PR, research project administration). The two exceptions the leaderships of the PROs, which held separate meetings for in size and activities, JSI with 6-15 employees and later Universities and for Institutes, did not add a positive note into TehnoCenter UM with 4-8 employees at the time, however, had the confusion and distrust. Actually, the only joint meeting of little institutional financial support, and had to provide the PRO leaderships was organized by JSI on June 12th 2014 in financing for their work from projects (EU projects, work for order to evaluate possible further steps, already before the KTT industry). project (phase 2) ended. Thus, the long-lasting effort for financial support to the TTOs After 3 years of turmoil, finally, in June 2017 the government from the side of the government began already in 2008. decided to finance TTOs of Slovenia with a 5-year project. The current KTT project's mission is twofold: the strengthening of links and increasing the cooperation of PROs and industry and 4.2 The three phases of the projects the strengthening the competences of TTOs, researchers and The first partial solutions to the TTO financing started to be enterprises. Most (80%+) of the finances go to human resource generated by the government with the support of the financing. Association of Technology Transfer Professionals of Slovenia (Association SI-TT) already in 2009. Those were the KTT As of now, all TTOs in Slovenia are jointly collaborating in this projects and they can be divided into three groups. project. This collaborative all-inclusive TTO setup is considered by most of the utmost importance for coherent 4.2.1 INO projects: 2008-2011 further development of the TTOs in Slovenia, but was not an initiative of the government. The government anticipated a Firstly, the INO projects of 2008, 2009, 2011 were financed by competitive call where some of the TTOs would outbid the the (former) Technology and Innovation Agency (TIA) with the others, practically eliminating some or preventing others from support of the Ministry of Science. These projects involved developing skills at their institution. Such a development would partners as Slovenian Business and Regional Development have had disastrous effects on the development of the Agencies, but also some of the Public Research Organizations. Technology Transfer scene in Slovenia. Moreover, the rules of The glass ceiling has been broken, but the projects still focused the project prohibited active assistance from one PRO to the mainly on promotion and organization of events. These projects other, so no PRO can or could take on a case from the other explicitly focused on counting the number of leaflets produced PRO. Some PROs would thus in the exclusive model remain and workshops organized. Less focus was devoted to actual Key completely unsupported, as far as knowledge and technology Performance Indicators (KPIs) that would influence the transfer is concerned. Both of these features (long gaps between industrial progress of the country, as number of contracts and financing and the possible exclusion of some TTOs) need their size, patents filed etc. urgently to be rethought for further development – and prevented. 4.2.2 KTT project: 2013-2014 Secondly, the initial project KTT, lasting from 2013 through Against the spirit of the 2017 governmental call, the JSI as the 2014, was the first project within which in particular technology consortium leader managed to join forces with all existing transfer in Slovenia was systematically (albeit not sustainably) TTOs, small and big, some already in existence for a while and funded. During this first period national funds from the kicking-off and some just created. This was not an easy Ministry of Economy were made available for such financing. enterprise: some of the larger PROs in Slovenia were at the time There were 6 partners involved in the project, but (due to late interested in forming an exclusive consortium, leaving the other evaluation and late start) the project only lasted for 16.5 TTOs out of the loop, preventing their further development. months. Their idea was that not all the TTOs in Slovenia, but only a selected few should have access to the financial support. Against all odds, thanks to the efforts of the JSI and the timely 305 support of the Ministry of Science in 2017, this did not happen. 4.3 The Center for technology transfer In 2017 all of the institutions that could join the consortium, and innovation of JSI were invited to do so, and the coordinator made their accession possible, although with several difficulties regarding the quality The Center for Technology Transfer and Innovation at the Jožef of the official documentation initially provided. Stefan Institute is currently the coordinator of the project KTT (2017-2022), the coordinator of Enterprise Europe Network The current KTT project, 2017-2022, comprises 8 partners, all Slovenia, and is a financially independent unit of Jožef Stefan public research organizations (PROs), represented by their Institute, Slovenia, involved in many different international respective technology transfer offices (TTOs), namely, 4 projects. leading institutes and 4 renowned universities. CTT has been the coordinator of the INO projects in 2008, This helped to forge a network of TTOs in Slovenia, striving for 2009 and 2011, with different partners (e.g. NIB, KI, UM); the development – competing, but under the leadership of JSI with coordinator of the KTT project 2013-2014 under the a logic of the utmost inclusivity. supervision of Ministry for economics and development; and is also the coordinator of the KTT-2 project 2017-2022 under the Every operational TTO in the country has its place in this supervision of the Ministry of Science, Education and Sports. It current TTO project and it should remain so. should be noted, however, that the coordination of the current On the other hand, inclusivity also has its negative issues. In a project KTT-2 was offered by the JSI to all other partners. In huge project with many partners not necessarily everything is particular it was offered to the UL as the largest university in running smoothly. Sometimes also tensions tend to interrupt the Slovenia, with similar innovation output as JSI. The offer was day-to-day business. The issue of research competition, which not accepted, not in 2017 and not in 2020, when it was appears to be rather smoothly managed by the researchers and repeated. the PRO leaderships, is often exhibited as a ruthless and futile CTT prepared the project documentation and the proposed brawl on the level of the TTOs. Such tensions are enabled and financing was split according to the size (in research FTE) of propelled by the fact that besides by the exhaustive expert work the PRO. The UM was awarded extra financing, following its of the TTO, results can currently still also be defined and proposal to coordinate the activities of the consortium in the achieved in a political manner as they are not concrete and Eastern NUTS3 region of Slovenia, and due to a claim of a precise enough. significantly higher output than the corresponding one, relative The situation resembles the Performance Enhancement System to the research FTE. JSI made this increase possible by (PES) crisis of the Enterprise Europe Network (EEN) from the reallocating a share of their own budget to the UM. In addition, period 2014-2016, when the European Commission worked a share of the proposed KTT 2017-2022 budget was split tirelessly to improve the standards of the PES results to a solid equally among all 8 partners, disregarding their size in research and concrete set of PES, which can be easily comparable capacity, to acknowledge that events and public relations through the EEN partners. The analytics is done by the EASME activities require the same effort regardless the size of the and is of utmost importance in EEN development and partner institution and the level of results offered by the particular improvement. An improvement is sought from the side of the PRO. Ministry to enable such monitoring and analysis of the results in The employees of CTT helped lobby for such the KTT-2 a contextual content manner, in addition to the (albeit very consortium project in their roles within the Association SI-TT. complicated) financial monitoring. They worked coherently and tirelessly for more than 15 years Based on this experience and example, the scientific approach towards a common goal: a creation of a network of Slovenian to defining the technology and knowledge transfer KPIs is of Technology Transfer Offices. This network is now partially the utmost importance in Slovenia. In particular it is necessary operational. These activities resulted in an active consortium of to enable fair comparison among the KTT partners, based on 8 TTOs and JSI and CTT is currently responsible for executing monitored, unalterable and unique parameters. It is important to this project financing scheme. ease out the tensions of the unproductive competition in the We urge the government to decide about further support of the world where the Technology transfer industry itself needs still TTOs in Slovenia as soon as possible to allow for planning of to be professionalized. The objective numbers, comparable any transition necessary. Apart from the problem that the among the partners, would enable a better standing and a financing is running out in June 2022 and that the newly community, focused purely on development instead of power employed and trained personnel will need to plan their further games. existence, there are also two other issues to be covered. Lastly, a capacity of all partners to accept the creation of a Firstly, even though well informed from the relevant community of equals who do the best they can in their own professional body, the Association SI-TT, the Ministry for fields and on their own institutions, without making a special effort to prevent others’ excellence Science, Education and Sports decided not to include any , could also be further mention of the need for, existence or possible financing of the improved. Technology Transfer Offices in the proposal for the new There are as of today no confirmed information on prolongation Legislative Act on Research, Development and Innovation in of this financing, thus the same issue as in 2014 will resurface 2019. Several corrections have been made to the proposed Act in two years, in June 2022. What comes next? The system has since then, none of them explicitly denoting the role of been set up, people have been brought together to create new Technology Transfer Offices in the system. and larger, operational TTOs, and educated. The government And secondly, to allow for the creation of spinoff companies should be urged to officially lay out their plans to enable planning of the TTOs’ future activities. with possible financial investments from the side of the Public Research Organizations, high-level parts of legislation would need to be altered, for example the Act on Public Finances. This can only be done with strong political support and understanding of all involved stakeholders, who, to a great 306 extent have limited understanding of the spinout/spinoff monitoring from the side of a PRO can ruin the spinoff’s situation. The new Act on Research, Development and prospects for growth. Secondly, the same limitation applies for Innovation, proposes to overcome this obstacle by overriding the consultancy available to the Organization, which is in the legislative background, but remains yet to be approved. addition to being inexperienced and partly professional, also costly. Thus, to this day, in the absence of legislative changes, there is only one option for successful and fair creation of new The non-moderated situation with unclear options of the enterprises from the institutions of knowledge. This option is entrepreneurial researchers yields unregistered spinout the creation of spinout companies with the ultimate requirement companies of the Public research organizations. This situation for the transparent accounting for the public expenditure. is easily moderated via internal policy acts, structuring the process of company creation according to the current legislative 5. PURPOSE OF THE TTO limits. Such processes are in place at least at the JSI and UL, possibly also at other PROs in Slovenia, but not all researchers FINANCING resort to take such routes. 5.1 Industry relations The legislation should be adopted to allow not only for The goal of all of the KTT projects was and is to support the creation, but primarily for successful management of IPR as an industry in Slovenia, rather than an outflow of knowledge investment in spinout companies. abroad or great profit for PROs. Collaboration between PROs and SMEs in Slovenia should be strengthened. 5.3 Investing into IPR The general process of collaboration [14] is based on several Intellectual, and for the purpose of this article in particular parallel processes. First the internal processes of research industrial property, is of high importance for development of institutions need to provide the context and the content of particular peoples, companies, countries. Indeed, the use of possible collaboration, and with assessments of technology and legally protected intellectual property for development of the market the principle decisions are taken. Then the IP rights country is a strategic decision that cannot be done overnight. management can commence. This phase usually lasts for more than two years in which enough time is provided to carry out Patent system has many positive and less positive aspects, the processes of finding a domestic or foreign partner for therefore many experts from various universities call for a licensing, continuing R&D collaboration or to build up a team reform of this system in order to realise its prime objective – “to for spin-off creation. support and encourage innovativeness”. Slovenian companies prefer contract and collaborative Despite the above stated, it is important to invest in patents and cooperation to buying licenses and patent rights. Also, a other forms of intellectual property (IP). Investments in relatively low added value per employee and a low profit intellectual property increases licensing opportunities and the margin are not stimulating the research-industry collaboration. IP position of the Slovenian knowledge worldwide. On the other hand, Slovenian knowledge, as high profile as it Currently IP costs can be supported within some national turns out to be in terms of highly cited publications per capita, is small in volume due to Slovenia’s small number of instruments (e.g. RRI, Eureka, some start-up funding initiatives), but mainly for companies. KTT is so far the only inhabitants. As a consequence, the trademark of Slovenian instrument enabling financial support for investments into IPR science, IPR or R&D services is not well known abroad. at the side of PROs. Primarily domestic, but also international R&D connections Instruments that support investment - and not merely paying for should be improved to allow for maximum development of the intellectual property rights - should be further developed in trademark of Slovenian science for industrial use. Slovenia. 5.2 Creation of new companies from 5.4 Strengthening the TTOs competences PROs The goal of the KTT project is to establish technology transfer Companies from PROs can be created either as spinouts (a centers in Slovenia as integral parts of PROs, which shall, first separate legal entity, which is licensing the IPR from the PRO, and foremost, strive to serve the interests of the researcher and but the entity is owned by the inventors) or as spinoffs (an the PRO. The TTOs shall assist the researcher throughout the entity owned partially by the PRO, at least in the share of the entire procedure of the industry-research cooperation, by raising invested IPR). competences and educating, taking care of legal and administrative issues, and promote research achievements The process of building a team for creation of new companies among the industry. Lastly, TTOs shall support the cooperation from PROs, involves team building, and education in already established by research groups. entrepreneurship. If provided and guided, it can result in spin- off creation, VC involvement and market activities. To achieve that goal, a further stable financing should be provided, divided into two parts: a smaller part to be devoted to Issues, limiting the entrepreneurship activities, are connected to further promotion activities (events, brochures etc). The the pull-push principles of technology transfer and the majority of the financing should be devoted to actual market conditions in the state economy. Firstly, the legislation does not activities leading to capitalization of the created IPR. allow for the Public Research Organization (with a limited option for the Universities to do so) to co-own and co-manage It is true that a significant part of knowledge, created by the the newly created business. This severely limits the PROs, is transferred via other paths: teaching, publications, Organization’s interest in the activity. Secondly, even if the conference, STEM activities. The TTO should be involved in creation of spinoffs were allowed, there is a limited capacity of all of those as an information provider, when needed and business-oriented experts within the Public Research appropriate. Organizations, who would be capable of monitoring and steering the spinoff company from the side of a PRO. Too rigid 307 However, the first and most important task of the TTO should Table 2: Overview results reported in the periods 2009-2012 be commercialization of IPR and secret knowledge, as there is [15], 2013-2014 [11] and 2017-2019* [16], normalized per no better equipped place or better educated people to do that for duration of one year. the benefit of the PRO and the (domestic) economy. Survey: 2009-2012 KTT: 2013/2014) KTT: 2017-2019 Patents filed to IPO with full report / / 12 TTOs competences should be further developed and TTOs Patents filed wherever / 49 / Patents granted in Slovenia 29 / / themselves further financially supported. Patents granted with report (different patents in the same family count as many) 7 / / IP License & Sales 275.472,33 € 62.909,09 € 363.086,00 € 6. THE KT ACTIVITIES RESULTS: R&D Sales 7.098.928,33 € / 1.361.706,00 € Spinouts 5 4 / STATISTICS AND METHOD Number of employed in SO companies younger than 5 years 6 / / In the following we present the results of the KT activities in New companies in collaboration with PROs thought TTOs / / 16 Slovenia in the past decade. Metrics for collection of this data was not comparable in different periods due to different responsible bodies collecting the data and different understanding of what is actually important. 6.2 The period 2009-2012 The 2009-2012 numbers were a result of a SI-TT survey [15]. 6.1 Incomparable metrics Based on the collected data of the three largest Slovenian public Results on KT activities, collected during the periods of 2009- research organizations - institutes and three universities, an 2012, 2013-14 and 2017-2019 are very diversified. One of the analysis of the results of work in the field of technology transfer reasons of the diversification is the way in which the data were in the period 2009-2012 has been prepared. collected and the purpose of its collection. The logic at the time was that the granted patents are of For example, in the category of patents filed, data was not importance, not the filings. The reason for this was an active collected in period 2009-2012, in the period 2013-14 the pursue of the researchers at the time to file as many patent number of patents filed wherever in the world was collected and applications at the national Patent Office, as the filing itself in the period 2017-2019 the full report patents were sought for. sufficed to gain significant extra points according to the national evaluation at the Agency for Research and Only in the period 2009-2012 patents granted were collected Development of Slovenia. and were divided between those granted in Slovenia (without full report) and elsewhere (also possible without full report, but The Association SI-TT as an association of Knowledge transfer more likely with one). professionals was at the time also aware of the importance of other KT categories: R&D, licensing and IPR sales contracts, IP license and sales were collected in all three periods and R&D spinout creation. In their survey it went into as much detail as sales in period 2009-2012 and 2017-2019. collecting data on actual employees in these companies. Number of created spinouts were collected in period 2009-2012 On the other hand, the numbers in this survey were not and 2013/2014 and not in the last period, as the Ministry for monitored or cross-checked in any way. They were self- Science (somehow) concluded this was not a result of the work reported by the TTOs to the SI-TT questionnaire and no proof of the Technology Transfer Office. of actual achievement of the numbers was sought for or delivered, thus their accuracy might be limited. Also, the Table 1: Overview results reported by the TTOs in the reported data are considered to be the data about the PRO periods 2009-12 [15], 2013-14 [11] and 2017-2019* [16] activity as a whole, not about the share of activity in which the Survey: 2009-2012 KTT: 2013/2014) KTT: 2017-2019 TTO was involved. (36 months) (16.5 months) (24 months) Patents filed to IPO with full report / / 24 Patents filed wherever / 67 / Patents granted in Slovenia 87 / / 6.3 Project results 2013-2014 Patents granted with report (different patents in the same family count as many) 21 / / The 2013-2014 numbers are a result of a reporting, done to the IP License & Sales 826.417,00 € 86.500,00 € 726.172,00 € R&D Sales 21.296.785,00 € / 2.723.412,00 € Ministry of Economy and Development in autumn of 2014, Spinouts 14 6 / within the first KTT project, financed by the Ministry. Number of employed in SO companies younger than 5 years 18,4 / / New companies in collaboration with PROs The Ministry of Economy was financing the project KTT 2013- thought TTOs / / 32 14 with national financing. It focused on the Licensing and Sales of IPR and on spinout creation. R&D contracts were at the time considered to be less indicative for a TTO activity (and Number of employees in the spinouts created in the last 5 years new company creation was considered to be part of the TTO were only collected in the period 2009-2012. activity) [11]. Number of new companies to be put into collaboration with the Some monitoring was done by the Ministry of Economy to seek Public Research Organization was only collected in the period proof for delivered results, so the results can be considered as 2017-2019. partially relevant as for measuring the activity of the TTO (not Numbers can be found in Table 1. the PRO as a whole). The overall results can be seen from Table 2, normalized to the 6.4 Project results 2017-2019 length of 1 year. The 2017-2019 numbers are a result of a reporting, done every 6 months to the Ministry of Science, Education and Sports. The results were also presented at the 12th International Technology Transfer Conference [16]. 308 The Ministry of Science sought to finance the KTT 2 project FTE, number of granted and valid patents (Domestic and with money from the Structural fund, meaning that a local internationally) and WoS PRO specific results. component with direct benefit for the companies of Slovenia The data was collected from yearly reports of the largest had to be proven during the project. Research organizations in Slovenia: JSI, UL, UM, UP, KIS, KI, The overall project goals for 5 years (until July 2022) include NIB and UNG, Thomson Reuters Database as of 1.10.2015, 40 patent applications at patent offices that perform full URSIL database as of 1.10.2015, ARRS webpage with financial examination; 300,000.00 EUR of income from license data as of 1.10.2015, SciVal as of 1.9.2015 Web of Science as agreements; 8,000,000.00 EUR income from contract and of 1.9.2015. The 8 institutions covered 79.07% of the ARRS collaborative research agreements, and 40 new Slovenian budget at the time, meaning that 20.93% of the research companies served according to the public call [17a]. institutions, financed by the ARRS were not covered by this survey. Number of students at the Universities was not The consortium has already delivered the required results for considered as a relevant indicator, as the IPR generated by the the new companies served and the license agreements key students is not owned by the Universities. In addition, number performance indicators, and there are reasonably optimistic of employees was also not considered, as the employments can results achieved in the first two out of five years in terms of range from a full FTE to just a few percent of work obligation, number of patent applications and contract and collaborative which cannot be treated equally. Also, in the category patents research relations (50% and 40% of the final mark achieved, granted at least one university included patents granted to respectively) [16]. employees (and not the institution itself). The data is mainly accurate as an indication of the part of the Results of the survey are shown in Table 3 below. PRO activity in which the TTO is involved (not the activity of the PRO as a whole). Also, the ministry of Science established a The results show a discrepancy between the amount of precise set of data and documented proofs to be submitted financing received for R&D activities from the Slovenian before confirming the results, thus they can be considered as Agency, the number of FTE employed to perform the R&D mainly relevant. work (teaching staff FTEs are not included) and the output in terms of number of valid and granted Slovenian patents, number of valid and granted foreign patents and number of publications. In this comparison, data on R&D contracts could not be obtained from public sources. Table 3: 2015 Quality assessment of 8 Slovenian Research organizations made on the basis of the publicly available data. Figure 1: A comparison of 5-year goals and the 2-year performance of the KTT project. The Ministry of Science in 2017-2019 focused on R&D contracts primarily with national legal subjects, on the new companies brought into collaboration and the national licensing deals. Spinout creation deemed to be out of the scope of the governmental support. Nevertheless, it is possible that the majority of the reported (as requested) licensing deals are actually being done with unregistered spinout companies of the Public research organizations. Also, since the Ministry is only monitoring the contracts and not their realization, it is not clear, how much of the reported amounts can actually be considered a PRO income (for As the data covers 79,07% of all national research financing incentive distribution). from the ARRS, it is indicative and helps us understand the distribution of knowledge transfer activities throughout the A huge drop in R&D collaboration can be seen from the data. majority of the STEM oriented PROs in Slovenia. The The KPI of both projects were predefined by the two Ministries. discrepancies could assist us in understanding the year to year The difference in KPI definitions can be seen from Table 1. difference in performance as shown in Table 1 and Table 2. To obtain comparable results in order to estimate the Further research should be done in this domain. development of the TT profession in Slovenia, it is pertinent to use a similar metrics in every one of the time periods. However, 7. FURTHER DEVELOPMENT some estimates can also be done when taking a look at the more At the general level, primarily domestic, but also international granular level of data - how the results are distributed over the R&D connections should be improved to allow for maximum PROs in a particular year and in which particular fields. development of the trademark of Slovenian science for industrial use. 6.5 Scientific output comparison The legislation should be adopted to allow not only for In an attempt to resolve the reason for the anomalies and drops creation, but primarily for successful management of IPR as an in performance, an analysis of publicly available data on investment in spinout companies. Research intensity and outputs was performed already in 2015, incorporating financing available to a PRO, its research staff in 309 Instruments that support investment and not merely paying for 8. CONCLUSIONS intellectual property rights should be further developed in This paper was written to give an overview of the Slovenia. history/genesis of the current Slovenian technology and TTOs competences should be further developed and TTOs knowledge transfer system, unfolding several issues that will themselves further supported. need to be addressed in the future to make the knowledge transfer and innovation system of Slovenia to become fully Projects funded from the ERDF funds, such as KTT 2017-2022, operational. The mistakes made during the short, but significant often have relatively complicated reporting, which represents an history od knowkledge and technology transfer in Slovenia, administrative work load for TT managers and results in a mustn’t be lost or else the same mistakes will be repeated. The diminished amount of financing spent from the ERDF in the paper thus describes the effects of having project-based funding project as a whole. The Ministry of Science needs to establish a of TT with varying scopes and focuses: coherent financing over the years, which is not project based. i. The lack of continuity makes it hard to keep staff and develop In the Slovenian case, the Proof of concept fund is not competences over long time; established, which prevents research entrepreneurs to develop their inventions further towards the market. Continuing support ii. Changing focus leads to changes in direction (what you of the Ministry and their collaboration with the SID bank could measure is what you get) and the mixture of results of the TTOs lead to a breakthrough in this domain. The SID bank should in Slovenia in the past decade nicely shows the effect of the continue with a steep pace the creation of the fund to be changing policy; established by the end of the 2021. iii. It becomes hard to keep track of the overall development of There is a lack of support for spinouts. Start-ups can enter TT in Slovenia, which needs to be improved in order to enable easily a technology park and perform a day-to-day business; in quality control. contrast, a spinout has to carry out many internal procedures iv. Exact and exactly measurable KPI should be determined to within the PRO from which it originates in order to start prevent the reporting manipulation of the support system and operations. On the other hand, the scale-up phase is well the PROs. supported (for example, by the national project SIO). Spinout support should become part of the Technology and Knowledge v. Constructive, systematic, sustainable, inter-connected and Transfer policy in Slovenia. consistent solutions should be sought for, without excluding TTOs. They are players in the field of public research The Slovenian legislature (ZIDR) provides incentives for organizations support. inventors, when the invention is licensed or sold (min. 20% of gross royalty, in practice around 33% of net royalty). There is a In other countries, the political systems have tended to fund the lack of recognition for Technology Transfer (TT) managers start-up phases of TT, but they have also had an expectation (compared to inventors). The Ministry of Science should make that PRO’s would take over responsibility with time. This has sure that the incentives for TT officers should become part of not always happened. Even if the basic funding of the TTO the legislation governing the incentives for researchers. office is secured by the government or PRO, the missing PoC link funding often has to continue on national/regional level for Professionalization is also sought for. For example, the Council many years for TT to mature. Also, Seed funding for spin-outs for science and technology (SZT) should follow the lead of the is also a long-term need that may require political support. European Commission and involve not only researchers and industrialists, but also technology transfer professionals into The recommendations of the paper require further thoughts on their developments of the policy inputs. As such, the current the need of priorities for government intervention. These SZT lacks a very important component, and that is the priorities will hopefully be set by the governmental/political knowledge and experience of the man or the woman in between structures in Slovenia through the new law on scientific the worlds. The European Commission has already rectified this research and innovation activity. The law is at the moment in the past years, where the TT experts participate very being coordinated interdepartmentally within the Slovenian successfully in several high-level Advisory Boards and Expert government. However, the principles and the recommendations groups. The Slovenian government should follow that lead. and the priorities should then also be followed by the PROs. Last but not least, technology transfer needs stable funding, as a Last but not least, Technology transfer is a young discipline. TTO is generally not able to finance itself – apart from the rare There should be a sensible amount of healthy competition also cases where industry buys high licenses (a large license can in Technology transfer. However, this competition should support a TTO for up to 10 years), and this is not applicable to remain cordial and motivational, and avoid any destructive Slovenia with its IP reluctant SMEs with lower than average steps, especially if for the purpose of self-promotion. EU27 technology absorption capacity. Having created a Scientific Section to address the issues of In case when the TTO is supported by the government, it is Technology and Knowledge transfer within the 13th important that there is good cooperation between the TTO and International Technology Transfer Conference, clearly shows the government (not just administrative supervision but also the opportunity for further joint research (nationally and content guidelines for future work, content analysis, KPI worldwide, and beyond mere best-practice examples) on definition fine tuning, including the development of a toolbox technology and knowledge transfer from a scientific point of for successful technology transfer as a collection of contracts, view, influencing the entrepreneurship potentials and setbacks good practices and business models. of the researchers and businesses. In essence, a TTO is an important part of the innovation chain and has to be recognized as such. 9. ACKNOWLEDGMENTS We would like to thank the Ministry for Science, Education and Sports for their continuing support in establishing a resilient and productive KT sector in Slovenia. Special thanks also to the 310 four independent reviewers for their constructive comments and Slovenski raziskovalci na razpotju. Vinkler, J. ed. Založba suggestions that improved this manuscript. Many of those were Univerze na Primorskem, Koper. used in the conclusions. Š.Stres would like to thank her family http://www.hippocampus.si/ISBN/978-961-6832-07-6.pdf for bearing with her during all those times of incessant work. [11] Habjanič, A., Stres, Š., Zorc, A., Alešnik P., Virag, L. Also, she would like to extend her gratitude to all the 2015. Prenos tehnologij na javnih raziskovalnih supportive colleagues who helped create, steer and pursue their organizacijah v Sloveniji. Habjanič, A. ed. Združenje common vision of an inclusive, vibrant, consistent and profesionalcev za prenos tehnologij Slovenije, Ljubljana. interconnected (knowledge and technology transfer) future in http://tehnologije.ijs.si/wp-content/uploads/2018/04/TT- Slovenia. brosura-2015_11092015_2.pdf 10. REFERENCES [12] Stres, Š.,Pal, L., Habjanič, A., Žilič, E., Blatnik, R., [1] Number of Researchers per million inhabitants by Country. Lutman, T., Benčina, M, Leban, M., Lipnik, A., Oblak, [internet]. [cited on March 30, 2020]. Available from: M., Rener, A. 2017. Pal, L., Stres, Š. eds. Pisarne za prenos tehnologij v Sloveniji. Združenje profesionalcev za http://chartsbin.com/view/1124 prenos tehnologij, Ljubljana. [2] Zakon o zavodih. [internet]. [cited on March 30, 2020]. http://tehnologije.ijs.si/gradiva/Brosura%20SI-TT.pdf Available from: http://zakonodaja.gov.si/rpsi/r00/predpis_ZAKO10.html [13] The Technology Transfer Block Exemption. [cited on September 9, 2020]. Available from: [3] Zakon o visokem šolstvu. [internet]. [cited on March 30, https://www.pinsentmasons.com/out-law/guides/the- 2020]. Available from: http://www.uradni- technology-transfer-block-exemption list.si/1/objava.jsp?urlid=2003134&stevilka=5826 [14] Š. Stres, Public R&D in natural sciences as a market [4] Seznam aktov, ki vodijo delovanje ARRS. [cited on March potential - an study of examples with assessment of 30, 2020]. Available from: http://www.arrs.gov.si/sl/akti/ situation and practical proposals for solutions, PODIM 2010. [5] Zakon o izumih iz delovnega razmerja. [cited on March 30, 2020]. Available from: [15] Š. Stres, P. Kunaver, Analiza rezultatov dela na področju http://zakonodaja.gov.si/rpsi/r02/predpis_ZAKO5122.html prenosa tehnologij slovenskih javnih raziskovanih institutov ter univerz 2009 -2012, Institut »Jožef Stefan« [6] Zakon o podpornem okolju za podjetništvo. [cited on za Združenje profesionalcev za prenos tehnologije March 30, 2020]. Available from: Slovenije, SI-TT, (March 22 2013) http://pisrs.si/Pis.web/pregledPredpisa?id=ZAKO5073 [16] Stres, Š. 2019. Slovenian KT system. In: Stres, Š., Pal, L., [7] Pravilnik o načinu vodenja in vsebini evidence subjektov Podobnik, F., Odić, D., Blatnik, R. Proceedings of the inovativnega okolja. [cited on March 30, 2020]. Available 12th International Technology Transfer Conference – 12. from: https://www.uradni-list.si/glasilo-uradni-list- ITTC. Institutu “Jožef Stefan”, Ljubljana. rs/vsebina/2005-01-5316/pravilnik-o-nacinu-vodenja-in- http://library.ijs.si/Stacks/Proceedings/ITTC vsebini-evidence-subjektov-inovativnega-okolja [17] JR TTO. 2017. Javni razpis Spodbujanje dejavnosti [8] Zakon o industrijski lastnini. [cited on March 30, 2020]. prenosa znanja preko delovanja pisarn za prenos Available from: tehnologij. Ministry of education, science and sport. http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO16 http://mizs.arhiv- 68 spletisc.gov.si/si/javne_objave_in_razpisi/okroznice/arhiv_ [9] Resolucija o raziskovalni in inovacijski strategiji okroznic/okroznice_razpisi_in_javna_narocila/javni_razpis Republike Slovenije. [cited on March 30, 2020]. Available i/indexb365.html?tx_t3javnirazpis_pi1%5Bshow_single% from: http://www.uradni-list.si/1/content?id=103975 5D=1550 [10] Ruzzier, M., Antončič, B., Zirnstein, E., Fatur, P., Nagy, T., Sešel, L., Zelič, U., Slovša, P., Stres, Š. 2011. 311 Patents on plasma treatments in agriculture Nina Recek Peter Gselman Mitja Krajnc Jozef Stefan Institute Interkorn d. o. o. Žipo d. o. o. Jamova cesta 39 Gančani 94 Šetarova 21 1000 Ljubljana 9231 Beltinci 2230 Lenart v Slovenskih goricah +38614773672 +38625422250 +38631307350 nina.recek@ijs.si peter.gselman@interkorn.si info@zipo.si Blaž Kozole Maja Rupnik Tamara Korošec Trac d. o. o. NLZOH Institute of Agriculture and Forestry Trubarjeva cesta 5 Prvomajska ulica 1 Vinarska ulica 14 8310 Šentjernej 2000 Maribor 2000 Maribor +38631726699 +38624500183 +38631770939 blaz.kozole@trac.si maja.rupnik@nlzoh.si tamara.korosec@kmetijski- zavod.si Gregor Primc Jozef Stefan Institute Jamova cesta 39 1000 Ljubljana +38614773672 gregor.primc@ijs.si ABSTRACT soil is treated. The influence of plasma processing on the water- Patents in the field of plasma agriculture are analyzed in this soaking capacity or microbiological picture is studied. paper. The first patent application in this technological niche appeared in 1995 and disclosed a method for seed treatment 2. PLASMA SEED PROJECT using non-equilibrium gaseous plasma. Since then, over 60 The project is focused on the development of methods for seed patents were filled in different countries, representing about 7% treatment and lasts about 3 years. The following partners are of published scientific papers in journals indexed by the Web of involved in developing a device suitable for treating seeds in Science. About half of the patent applications were submitted to the continuous mode: Interkorn Ltd. (Beltinci), Department of the Russian office, followed by Chinese, US, and Korean Surface Engineering, Jožef Stefan Institute (Ljubljana), Trac offices. Five or six patent applications have been submitted Ltd. (Šentjernej), Žipo Lenart, National Laboratory of Health, annually in the past few years. No Slovenian application has Environment and Food (Maribor), and Institute of Agriculture been registered so far. and Forestry (Maribor). The project coordinator, Interkorn Ltd., is the largest provider of seed coatings in Slovenia. It provides Keywords processing of seeds from separation to cleaning and deposition Plasma, agriculture, patent, search of various coatings. Processed seeds are further distributed among farms. Quality control and ecological production are among the company's priorities. The company produces and 1. INTRODUCTION treats seeds of corn, wheat, barley, other cereals, and soybeans. Plasma agriculture is among the most promising fields of The treatment of seeds is performed on an automated line, scientific research and industrial developments. It is an which allows for a high quality of processing and traceability of interdisciplinary niche where non-equilibrium thermodynamics seed batches. It has almost 100 regular customers who provide meets farming and food industry. There are hundreds of feedback about harvesting and storage. The company has research groups currently involved in developing plasma specialized in treating seeds to protect them against fungi techniques to treat seeds, plants, crops, storage and packaging (molds), worms, and birds to enable optimal harvesting. The devices, food, and feedstock. Many are academic, and they are unique coatings are adopted for use in the west Pannonia concentrated on chemical and biological modifications caused region, which has specific climate and soil conditions and by plasma treatment. Some groups have studied the influence of ecosystem. The company also provides services for seeds' plasma treatment on germination and growth of plants. Few treatment before storage to minimize the proliferation of molds, groups have also performed field experiments and studied the which may produce toxins that are harmful to humans and role of plasma parameters on the amount and quality of crops. animals. The scientific coordinator is Dr. Nina Recek, a Indirect treatments are popular, too. In such cases, either water researcher of the Department of Surface Engineering at Jozef for spraying or watering plants is treated by gaseous plasma or Stefan Institute. Other project partners are involved in research 312 on plasma-seed interaction and development of different components for a prototype of the line, which will be used to treat various seeds in the continuous mode. The goal of plasma treatment is to disinfect seeds and improve water uptake and, thus, faster germination as compared to untreated seeds. 3. LITERATURE SURVEY 3.1 Scientific papers Over 900 scientific papers have been published in journals ranked in the Web of Science. At the time of writing this document, 23 papers are highly cited in the field – received enough citations as of March/April 2020 to place them in the top 1% of their academic fields based on a highly cited threshold for the field and publication year. One paper is labeled as "hot paper" – such papers were published in the past two years and received enough citations in March/April 2020 to place them in the top 0.1% of papers in its academic fields. The majority of these papers deal with scientific aspects, but some Figure 2: Number of scientific papers published in the past ten also report experiments in the fields. The number of papers years in plasma agriculture. rewarded with "highly cited in the field" for the past decade is presented in Figure 1. 3.2 Patent applications While the number of scientific papers indicates the scientific importance of the subject, technological importance is revealed from the patents applied at various patent offices worldwide. The first patent in the field of plasma agriculture indexed in the ecpacenet database has the priority date 1995-07-05 [1]. The patent by Filippov, Bitjutskij, and Fedorov discloses a method for pre-sowing seed treatment. The method provides plasma treatment of seeds with low discharge intensity and pressure of inorganic gas, resulting in increased nutritive value of products and reduced power consumption. Since this pioneering work, numerous patents have appeared. Figure 3 represents the number of patents filed per year. The number is slowly increasing. By the time of writing this paper, as many as 67 patent applications appeared in the database. One of the last applications was also Russian [2]. Disclosed is a method for grain disinfection, which involves exposure of the treated grain to a stream of cold plasma at atmospheric pressure. Cold plasma flow is generated due to negative corona discharge between Figure 1: Number of highly cited papers in the field published anode and cathode with pulsed voltage in air. Grains with the in the last decade. moisture content of 7-14% are placed on the anode surface and treated for 10 minutes. According to the authors [2], the The number of scientific papers published in journals indexed invention provides a stable disinfecting effect when processing by the Web of Science for the past decade is plotted in Figure 2. grain (for food and sowing) intended for storage. One can observe a graduate increase in the published papers. The number of papers published per year has tripled in the last Russian inventors are particularly active in filing patent decade, which indicates the scientific importance of the applications in the field of plasma agriculture. Figure 4 reveals interdisciplinary field of plasma agriculture. the number of patent applications submitted to patent offices in different countries. The Russian office received as many as 33 applications. Next on the graph is the Chinese office with 20 applications, followed by the US office (6 applications) and the Korean patent office (3 applications). Other patent offices received only one application each. 313 Nevertheless, another method for the treatment of liquids by gaseous plasma is disclosed by Chieh [6]. An agriculture plasma liquid apparatus includes an inlet pipe, an outlet pipe, an air inlet port, and a plasma liquid generating device. The diameter of the inlet and outlet pipes is rather large. The plasma liquid generating device is connected to the air inlet port to suck air from the air inlet port, communicates with the inlet pipe and the outlet pipe to import liquid flow from the inlet pipe and generate plasma particles into the liquid flow outputting through the output pipe. This solution is useful since many bubbles are formed within the innovative device, so the contact area between gaseous plasma and liquid is large compared to standard solutions. A more powerful device for the treatment of water with gaseous plasma is disclosed by Lu et al. [7]. The utility model discloses a high-temperature thermal conductance water plasma generation system. Its structure includes high-temperature Figure 3: Number of patent applications registered in the thermal conductance water plasma generator group, waterway Espacenet database. system, and thermal energy system. The central part of the high- temperature thermal conductance water plasma generator is a Of particular importance are patents on the indirect treatment of high-temperature heat pipe, including an inner tube and seeds, usually treating a liquid by gaseous plasma and then urceolus. The high-temperature heat transfer medium is soaking seeds in plasma-treated liquid. For example, mounted between the inner tube and the urceolus at the bottom. RU2702594 (C1) [3] discloses a method of activating water or The waterway system constitutes a water tank, filter, high- aqueous solutions. The method involves exposing a particular pressure unfamiliar water pump, solenoid valve, and hot water volume of treated water or aqueous solutions to plasma. tank. The thermal energy system includes an oil tank, a high- Contactless activation is carried out. Water or aqueous pressure oil pump, an oil flow control valve, a fuel nozzle, and solutions are exposed to a continuous electrodeless plasma an electronic ignition wire that gradually connects. The high- flame created by a UHF-plasmatron, which generates a low- temperature thermal conductance water plasma generation temperature plasma jet in a vapor-gas medium at atmospheric system causes water decomposition, so the water is transformed pressure. Device for contactless plasma activation of water or into a gaseous plasma rich in hydrogen and oxygen. The device aqueous solutions contains a flame UHF-plasmatron with a is very efficient. According to inventors, more than 90% of capacitive coupling, which includes a magnetron and water passing the device is converted. This device can rectangular as well as coaxial waveguides. The coaxial extensively be used for engines, industry and civil boilers, waveguide is hermetically isolated from the rectangular agriculture, chemical industry, and even medicine, as claimed waveguide by a radio-transparent quartz tube-insulator. The by the authors. central conductor of the coaxial waveguide is a copper tube configured to supply plasma-forming gas and ends with a Rocke and Wandell disclose a simultaneous on-site production nozzle with a hole to form a directed jet of plasma-forming gas. of hydrogen peroxide and nitrogen oxides from air and water in The working part of flame UHF-plasmatron is placed through a low power flowing liquid film plasma discharge for use in the seal into a sealed chamber containing a vessel with treated agriculture [8]. A reactor system that includes a single reactor water or water solution fixed on a rod-elevator. The invention or a plurality of parallel reactors is disclosed. A method that provides contactless plasma activation of water or aqueous includes: injecting a mixture including liquid water and gas into solutions, enables the exclusion ingress of electrode material at least one electrically-conductive inlet capillary tube of a into the activated liquid, and provides a high degree of purity of continuously flowing plasma reactor to generate a flowing treatment and safety. liquid film region on one or more internal walls of the continuously flowing plasma reactor with a gas stream flowing A similar device useful not only for water treatment is disclosed through the flowing liquid film region, propagating a plasma by Hummel et al. in the patent application submitted to the US discharge along the flowing liquid film region from at least one Patent Office [4]. Here, methods and systems for generating a electrically conductive inlet capillary to an electrically plasma-activated liquid or gas and applying the plasma- conductive outlet capillary tube at an opposite end of the activated liquid for agricultural use are disclosed. A system continuously flowing plasma reactor, dissociating the liquid embodiment includes a hand-held device that can be pointed water in the plasma discharge to form a plurality of dissociation and directed at different target areas of a plant. A method products, producing hydrogen peroxide and nitrogen oxides embodiment includes generating a plasma discharge in a gas from the plurality of dissociation products. Both nitrogen environment or a liquid environment and applying the gas or oxides and hydrogen peroxide are useful for the sterilization of liquid to a plant. agricultural products in an ecologically benign manner. Another method for plasma treatment of water is disclosed by Go and Lim [9] presented an invention related to a plasma Rothschild [5]. The invention generally concerns a machine generator for agriculture and stockbreeding. The plasma that creates and infuses charged air products into a flowing generator comprises a pair of main bodies, disposed of in an water system. A plasma discharge is not in direct contact with upper portion and a lower portion with a predetermined gap the flowing water but is separated from the plasma by a void between, a plurality of electrode rods, installed in a direction volume space. The resulting activated water may be used as an perpendicular to the pair of main bodies and evenly spaced, an industrial wash, antibacterial wash, a medicinal drink, or can be electrode plate installed in a direction perpendicular to the pair used in agriculture, e.g., for irrigation of crops, plants, or seed of main bodies installed behind the plurality of electrode rods treatment. with a predetermined gap between, an electrode sheet disposed on the electrode plate spaced apart from the plurality of 314 electrode rods with a predetermined gap between, configured to diaphragm-type electrolysis units. Further removing water generate plasma due to a reaction between a plurality of remained on the surface of products after the washing process electrode rods and current, and an insulating plate interposed by blowing with the use of gaseous plasma flow until complete between the electrode sheet and an electrode terminal provided removal of water is achieved. Plasma is produced in a medium on the electrode plate to prevent moisture from being of inorganic gas or a mixture of inorganic gases at a frequency introduced into the electrode terminal. The plasma generator of electromagnetic field of 4-40 MHz and at specific produces reactive gaseous species and radiation in the electromagnetic power of plasma discharge. Apparatus has at ultraviolet and vacuum ultraviolet range of wavelengths, which least one washing chamber, one drying chamber, one or more was found beneficial for sterilization or at least disinfection of transportation mechanisms, one or more diaphragm-type different products. electrolysis units with power sources, a plasma source with two electrodes, a plasma guide, a high-frequency generator, one or Lee [10] invented a technique for sterilization of water using more reservoirs for inorganic gas, and vacuum oil-free pump. gaseous plasma technology. The invention relates to a water The effect of this method is prolonged shelf life of fruit and sterilization device for agriculture and fishery having a variable vegetable products. plasma device that reduces the costs of production by simplifying an existing plasma generating device. It also raises The search for patents, as presented in this document, indicates the productivity of agriculture and fishery and enables the use that both direct and indirect plasma treatment result in a good of seawater and freshwater for agriculture and fishery by finish of agricultural products. The indirect plasma treatment properly sterilizing harmful bacteria existing in the seawater has a definitive advantage that treated material is preserved and freshwater by controlling the quantity of plasma through since the products are exposed to radicals only (not to powerful frequency variability. The water sterilization device for gaseous discharges). On the other hand, direct plasma treatment agriculture and fishery having a variable plasma device is faster since the concentration of reactive species within the according to the present invention comprises a power supply plasma is, by definition, more substantial than in any medium device for supplying power necessary for the device, a water treated by plasma. The users can choose between these two pump for receiving power from the power supply device and extremes or use a combination of direct and indirect treatment. introducing water, a variable plasma generating device for In such a case, the liquid can be treated with a powerful sterilizing water being introduced from the water pump by discharge, while products are exposed to mild plasma generating plasma and controlling the strength of generated conditions. plasma by controlling the frequency of power supplied, a first connection pipe having one side intercommunicating with the water pump and the other side intercommunicating with the variable plasma generating device, a sterilized water storage tank for storing water sterilized and discharged by the variable plasma generating device, a second connection pipe having one side intercommunicating with the variable plasma generating device and the other side intercommunicating with the sterilized water storage tank, a pollutant and foam discharge device installed on the top of the sterilized water storage tank to discharge foam and ozone, and a sterilized water discharge hole installed on the bottom of the sterilized water storage tank to discharge sterilized water in the sterilized water storage tank. Liu et al. disclosed a method for improving the germination of Stevia rebaudiana seeds. The method relates to a crop seed treatment technique in the technical field of agriculture. The method comprises the following steps: selecting and sterilizing seeds, preparing 6 to 8% aqueous solution of polyethylene glycol, soaking seeds into the prepared solution at the Figure 4: Number of patent applications registered in different temperature between 20 and 30 °C for 24 to 48 hours, then countries. filtering seeds, cleaning seeds by using clear water, and airing seeds for later sowing. It is generally recognized that molecules 4. CONCLUSIONS of the polyethylene glycol can change biological membrane Several innovative techniques have been protected with patent structures of various cells in cell engineering, in a way that lipid applications in the interdisciplinary field of plasma agriculture. molecules on a plasma membrane at a contact point of two cells The most innovative countries are China and Russia. The patent are dispersed and recombined. These molecules can also change applications span from direct treatment of seeds, plants, or the osmotic regulation capability of plants, influence on plant crops to indirect treatments using gaseous plasma to modify the physiology and are favorable for absorbing nutrition and chemical properties of liquids. Several techniques are inducing the activity of stimulation cells. The method can applicable on a large scale, but the beneficial results in terms of remarkably improve the capability of resisting adverse improved germination, growth, or better quality or quantity of situations when the Stevia rebaudiana seeds are germinated so crops are rarely reported. Plasma agriculture, therefore, remains that these seeds still maintain a higher germination rate and a technological challenge. Although the scientific literature germination energy in adverse situations. reports better germination of seeds treated by gaseous plasma either directly or indirectly, the descriptions of patented As early as in 2007, Russian inventors disclosed a technique for solutions lack of quantitative reports. In most cases, patent treating fruit [12]. The processing and storage of fresh-cut literature does not mention any field experiments, so it is not vegetables, berries, fruits in agriculture, food-processing, and easy to judge direct applicability. Another deficiency of patent related branches of industry is disclosed. The method involves literature is the lack of details about the exact treatment washing fruit and vegetable products with water preliminarily parameters. The patents disclose types of discharges used for activated in one or two electrode chambers of one or more 315 plasma generation but hardly mention the useful range of [6] Chieh, L. J. Agriculture plasma liquid apparatus, discharge parameters. TW201914969 (A), (2019). [7] LU, Z. L., ZHAO, W. X., BI, LY, High Temperature 5. ACKNOWLEDGMENTS Thermal Conductance Water Plasma Generation System, This work was supported by the EU Regional Development CN205855991 (U), (2017). Fund and Ministry of Education, Science and Sport, project [8] Rocke, B. R, Wandell, B., Simultaneous On-Site PLASMA SEED TREATMENT [contract #C3330-18-952005]. Production of Hydrogen Peroxide and Nitrogen Oxides from Air and Water in a Low Power Flowing Liquid Film 6. REFERENCES Plasma Discharge for Use in Agriculture, WO2015138921 [1] Filippov, A. K., Bitjutskij, N. P., Fedorov, M. A., Plant (A1), (2015). Seed Treatment Method, RU2076557 (C1), (1995). [9] Go, D. S., Lim, S. T., Plasma generator for agriculture and [2] Potoroko, I. P., Naumenko, N. V., Yacheslavovich, L. A., livestock industry, KR102024678 (B1), (2019). Kalinina Irina Valerevna, K. I., Method Of Grain [10] Lee, S. S., Water Sterilization Device With Variable Disinfection , RU2707944 (C1), (2019) Plasma Device, KR20130132352 (A), (2013). [3] Sergejchev K. F., Lukina, N. A., Andreev, S. N., [11] Liu, X. Y., Ma, H. Y., Ren, G. X., Shi, Y., Method for Apasheva, L. M., Savranskij V. V., Lobanov A. V., improving germination of stevia rebaudiana seeds, Method for Plasma Activation Of Water Or Aqueous CN101836529 (A), (2010). Solutions And Device For Its Implementation, RU2702594 (C1), (2019). [12] Fillipov A. K., Fedorov, M. A., Fillipov, D. A., Fillipov, R. A., Method for Processing of Fruit and Vegetable [4] Hummel, R. M., Watson, G. A., Kulaga, E., Jacofsky, M. Product and Apparatus for Performing the Same, C., Method and Apparatuses for Cold Plasma in RU2006103152 (A), (2007). Agriculture, US2019313582 (A1), (2019). [5] Rothschild, A., Machine and Method For Activated Water, US2016016142 (A1), (2016). 316 Rare earth-based permanent magnets: A proposed way to the circular economy Kristina Žužek Rožman Xuan Xu Spomenka Kobe Department for Nanostructured Department for Nanostructured Department for Nanostructured Materials, Jožef Stefan Institute Materials, Jožef Stefan Institute Materials, Jožef Stefan Institute Jamova 39, Ljubljana Jamova 39, Ljubljana Jamova 39, Ljubljana 00 386 1 4773 877 00 386 1 4773 898 00 386 1 4773 251 tina.zuzek@ijs.si xuan.xu@ijs.si spomenka.kobe@ijs.si Tomaž Tomše Benjamin Podmiljšak Sašo Šturm Department for Nanostructured Department for Nanostructured Department for Nanostructured Materials, Jožef Stefan Institute Materials, Jožef Stefan Institute Materials, Jožef Stefan Institute Jamova 39, Ljubljana Jamova 39, Ljubljana Jamova 39, Ljubljana 00 386 1 4773 545 00 386 1 4773 818 00 386 1 4773 418 tomaz.tomse@ijs.si benjamin.podmiljsak@ijs.si saso.sturm vključiti jih v industrijsko pomembne procese, da bi zmanjšali ABSTRACT odvisnost Slovenije in Evrope od ekonomsko in strateško občutljivih zalog ter povečali njihovo konkurenčnost na Critical raw materials, especially the rare earth metals like Dy, mednarodnih trgih. Nd, Sm, and recently also the transition metal Co are becoming more and more important to Europe’s future energy Članek prikazuje strateško vprašanje Evropske unije na independence, and offer the ability to be competitive in smart področju prenosa tehnologije, ki bi moralo biti v korist mobility and renewable energy innovation. The primary goal of raziskovalni skupnosti in gospodarstvu. Vendar se to vprašanje the efforts from the Department for nanostructured materials ne obravnava na ustrezni ravni: znanstveniki si skupaj z from Jožef Stefan is to implement the state-of-the-art industrijo prizadevajo rešiti tehnične težave, vendar na politični laboratory-developed & economically efficient technologies for ravni še niso dovolj podprti. the recycling and reprocessing of critical metals from end-of- life products. The aim is to integrate them into industrially Ključne besede relevant processes in order to reduce Slovenia and Europe’s Kritične surovine, redkozemeljski elementi, trajni magneti, Nd- dependence on economically and strategically sensitive supplies Fe-B, Sm-Co and to increase their competitiveness on international markets. This article depicts a strategic issue of the European Union in the field of technology transfer, which should benefit the 1. INTRODUCTION research community and the economy. However, this issue is not being addressed at the proper level: the scientists and EU plans for the transition to a low-carbon society and energy industry are working to solve the technical problems, but are efficiency by 2050 (the so-called European Green Deal) [1] will not supported sufficiently on the political level. require radical solutions, especially with the aim of reducing greenhouse gas emissions, which are projected to reduce by as Keywords much as 80%. The segments that will contribute the most are the development of green energy and electric mobility. The Critical raw materials, rare earth elements, permanent magnets, latter will require highly efficient electric motors to achieve this Nd-Fe-B, Sm-Co goal. The efficiencies of electric motors (mass versus POVZETEK efficiencies) based on permanent metal magnets of rare earth elements (such as Nd2Fe14B and SmCo5, Sm2Co17) both Kritične surovine, zlasti redke zemeljske kovine, kot so Dy Nd, sintered and bonded are known to be higher than induction Sm in v zadnjem času tudi prehodna kovina Co, postajajo vse motors, which contributes mainly in terms of miniaturization of pomembnejše za prihodnjo evropsko energetsko neodvisnost in devices with preserved or even improved efficiencies. From this ponujajo sposobnost konkurenčnosti na področju pametne point of view, permanent magnets are a hot subject to further mobilnosti in inovacij iz obnovljivih virov energije. research with the aim of improving their state-of-the-art properties. However, rare earth metals based on rare earth Primarni cilj prizadevanj Oddelka za nanostrukturne materiale Jožefa Stefana je uvajanje najsodobnejših labora metals are on the list of the most Critical Raw Materials (CRM) torijsko razvitih in ekonomsko učinkovitih tehnologij za recikliranje in important for the EU, which will require their comprehensive predelavo kritičnih kovin iz izrabljenih izdelkov. Cilj je treatment in the form of their complete use without and waste 317 and their efficient recycling of both systems using novel magnets for powertrains in e-vehicles, and consumption is recycling processes that are being developed on the department. expected to grow to 150,000 tons in the next 10 years. Here, the EU is in a difficult position, as it has no active rare earth mines, 2. CRITICAL RAW MATERIALS so it has to import up to 90% of rare earth-based permanent magnets, while European producers of permanent magnets can 2.1 EUs dependency on critical raw be counted on the fingers of one hand. Here, Slovenia is materials and their applications in strongly represented by two manufacturers of permanent permanent magnets magnets, namely Magneti Ljubljana d.d. and Kolektor Group d.d., which have managed to maintain a competitive advantage One of the major problems EU has been facing since 2011 is to this day, that gives Slovenia and enormous potential and ensuring a sustainable access to Critical Raw Materials [2], in advantage. particular elements of the lanthanide group, i.e. rare earths. The group understands 15 + 2 elements, the most characteristic and 2.2 Novel solutions in Rare earths-based useful of which are permanent magnets: Neodymium, permanent magnets circular economy Samarium, Dysprosium and Terbium with lately also Co, that is a transition metal. A key factor influencing that is their natural 2.2.1 The state of the art of the technology abundance and related production in only a few countries, such From SICIRS it is evident that, diverse methodologies for as China, Brazil, Russia, Australia and the Democratic Republic recycling Nd-Fe-B magnets have been summarized in detail by of Congo. Limited access and the political manipulations many authors [4,5,6]. The recycling approaches can be broadly concerning the CRM issues are attributed to the way some of classified into physical/mechanical processing, these countries use trade and tax policies to reserve their natural pyrometallurgical and hydrometallurgical separation & resources exclusively for their own use. China for the moment recovery. Physical/mechanical processing, including resintering controls as much as 84% of the world's rare earth mineral [7,8], hydrogenation disproportionation desorption and production. Although the trade restrictions that have peaked in recombination [9-11], of sintered Nd-Fe-B magnet scrap will 2011 have declined at the moment, fear of a new material crisis typically have a smaller environmental footprint compared to still persists. recycling routes, which rely on stripping of the REEs. The pyrometallurgical routes can be used to remelt the REE alloys and extract the different REE in the form of oxide, halide, fluoride or other metallic compound which can then be reduced to metallic form [12-17]. However, these pyrometallurgical processes operate at a temperature of around 750–950 °C and are thus energy intensive. Hydrometallurgical recycling processes designed for Nd-Fe-B magnets are promising due to the mild operating temperature, relatively simple equipment and the continuous separation ability [18, 19]. In hydrometallurgical processes, however, Nd-Fe-B magnets are completely dissolved with an acid. The roasting pretreatment at 900 °C is generally required. Iron, which is the major component of Nd-Fe-B magnets (60–70%) consumes large amount of acid, alkali and other precipitation agents that cannot be recycled in the whole process [5, 19]. REEs are concentrated by solvent extraction A Figure 1: Current consumptions of Nd-Fe-B PMs by and then are precipitated with either oxalic or carbonic acid. application and future predictions [3] The precipitate is further calcined at 950 °C to form REOs, which can then be returned to the initial manufacturing process A key component of the Europe Green Deal is to accelerate the for Nd-Fe-B magnets [20]. We also reviewed the patent "transition to sustainable and smart mobility", as transport documents using the queries below, from Patbase document accounts for a quarter of CO2 emissions. That is why the system. Results were the following: The most populated field is electrification of the transport system is receiving large the one including ((Nd2Fe14B or NdFeB or Nd-Fe-B) as earth investments and research at the global level. Company Tesla, as particulate material)) in the title or abstract AND FT=(grain the first mass producer of electric vehicles alone, is increasing boundary*) anywhere in the text. This yielded 97 patent production to 500,000 vehicles by the end of 2020 and with the families. On the other hand, using earth particulate material)). expansion of its production plant in Shanghai and the opening Yielded some less, 74 families. On the other hand the search of a new one in Berlin in the coming years reached as many as showed that ((Nd2Fe14B or NdFeB or Nd-Fe-B) and single one million new e-vehicles on the market. Also, other major car crystal anodic etching is a rather unpopulated field with 0 manufacturers such as Toyota, Honda, Kia, Renault e.g. invest patent families present at the moment and that our technology is significantly in development and e-production. Volkswagen not only operational, but worth exploring in the sense of alone is expected to produce as many as 1.5 million e-vehicles novelty. by 2025. In 2011, the EU gave priority to rare earths as the most critical CRMs, but in the years since, it has focused In the proposed method the Nd2Fe14B grains are recovered by mainly on permanent magnets made out of them based on two electrochemical etching of the bulk sintered Nd-Fe-B magnets alloy systems, namely neodymium-iron-boron (Nd-Fe-B) and or magnet scraps using an anodic oxidation process presented samarium-cobalt (Sm-Co). The latter systems are given the in Fig. 2 [21,22]. In this process the metallic Nd-rich phase in highest priority, as they are crucial in e-vehicles in their drive the grain boundaries is oxidized to Nd3+ as ions on the anode. motors, servo controllers, starting motors and regenerative The liquid electrolyte used in this process is formed of a non- brake generators. The projected consumption and use of aqueous solvent in order to prevent the Nd2Fe14B grains from permanent magnets based on Nd-Fe-B and Sm-Co is shown in oxidation. This allows direct reuse of the collected Nd2Fe14B Figure 1. Today, the industry consumes 50,000 tons of these grains for new magnet making. 318 economically negligible amounts of waste that do not prove economically sustainable for recycling. 2.2.3 The solutions to be used for sustainability Persistent measures to achieve greater sustainability and independence from external suppliers, thus include, among other things, the recycling of industrial wastes and end-of-life products. Permanent magnets based on Nd-Fe-B and Sm-Co systems (as Co, as it is similar to rare earths subjected to major political and economic manipulations) due to the high content of these metals represent the most valuable secondary source of these raw materials. Currently, less than 1% of all rare earths Figure 2: Selective electrochemical etching for recycling of Nd- used are recycled, mainly because they are dispersed in many Fe-B permanent magnets applications, and are difficult to extract. A lot of labor force is therefore needed and the economic calculation does simply not add up. 2.2.2 The economics of the recycling Currently, the only way to recycle rare earth-based permanent One of the purposes of the paper is show that although the magnets from waste streams of electrical and electronic magnets are needed in Europe, the fact that the rare-earth equipment is by crushing and recycling using physical, elements come mostly come from outside Europe presents an chemical or pyrometallurgical pathways, which are costly, intriguing moment in the development of the technology transfer energy consuming and environmentally unfriendly. Upon that processes in Europe, in line with the recycling recommendations. the developed novel feasible and green solutions for recycling REEs-based permanent magnets are of tremendous impact. The The economics of the process of recycling in the field of the rare proposed technology for selective PMs leaching [22] and a earth magnet shows that investing into some local technology related technology (EP 019 197 716.4) for complete that would enable extraction from recycled components would electrochemical PMs leaching and REE recovery are in the benefit the environment and the countries of the EU that do not patent procedure at EU Patent office. Efforts are also being poses rare earth material sources. However, also such advanced made towards permanent magnets circular economy also on the recycling would still carry costs that result in ‘virgin materials’ national (ARRS L2-9213, L2-1829) with Magneti Ljubljana being cheaper. Thus, considering the economics of the processes Ltd and Kolektor Group Ltd and international level via several and the recommendations of the EU, we must conclude that the European projects that encompasses the mentioned industrial changes into a sustainable economy will remain impossible partners in Slovenia and all over EU (ETN-DEMETER, H2020 without legislative changes within the EU that are crucially SUSMAGPRO, ERA MIN II MAXYCLE, EIT RAW needed to encourage this activity and contribute to the circular MATERIALS INSPIRES). Within H2020 proposal economy. SUSMAGPRO TRLs of 7-9 are aimed via three pilot plants for recycling of EoL permanent magnets that are planned in Thus, as a result of our research, we would like to propose some Europe. Recently we got awarded the EIT RAW MATERIALS concrete measures to improve the position of the recycling proposal on recycling REEs-based permanent magnets from processes of the rare earth metal components in the EU. white goods, where we collaborate also and also with Slovenian A novel recycling route for end of life (EoL) Nd–Fe–B magnets companies Domel Ltd, Gorenje Ltd, Surovina Ltd and Zeos is thus proposed based on the electrochemical etching. Ltd. Electrolyte can be recovered by distillation and re-used in a closed-loop thus minimizing safety risks and environmental impacts. Upon that the overall REEs mass balance from the 3. CONCLUSIONS initial magnet is 100% preserved that forms a circular economy. The total energy consumption of the magnet-manufacturing Despite success stories, the challenge still persists when process using the proposed electrochemical recycling route is transferring the technologies form lab scale to functioning estimated to be ~2.99 kWh kg–1, which is much lower than production lines, as the requests from the industry are strictly hydrometalurgy (30.0-33.4 kWh/kg) and directly comparable to connected with the economic feasibility. direct reuse (3.0 kWh/kg) [8], if we consider the conventional additive of the Nd–Pr hydride (4 wt.%), inclining to as feasible However, the proof of concept of the novel technology is possible production, albeit very green and sustainable. We have shown on the lab scale reaching TRLs 3-4 and represents only shown that recycling process costs are actually a barrier in an initiation that a technology could be feasible. Upon that much more investments would have to be made for “technology enlarging the usage of such processes industrially in the EU. transfer” projects, to bridge the Thus we propose a more targeted intervention that would tip the exact TRL gap between 5-7 like balance towards the recycling processes not only in regard to SUSAGPRO. In order for EU to become CO2 zero efficient in the rare earth materials, but all that are not applicable in to compete with the far East when it comes to be CRMs significant enough amounts to be economically viable. The independent, the investments in the whole value chain on situation could greatly be improved if the EU could import the recycling of PMs have to be made. Slovenia for example has an relevant waste from other regions of the world, which would extreme potential to act as a role model or as a feasible enable cost reductions of the processes, based on the quantity. permanent magnet circular economy closed loop example, as it On the other hand, the EU could even – maybe – become self- holds a geographical, professional and economical potential as sufficient in the supply of the rare earth materials. This is also a to serve as a central location for the collection of waste magnets policy that would provide a significant and a wide-ranging and their remanufacturing based on rare earths from the central impact in other European recycling technologies, dealing with and eastern parts of the European Union. The later has been recently successfully recognized by the EIT RAW materials scheme via funded INSPIRES project. The use of local 319 suppliers would significantly reduce carbon emissions and it is products with ‘designer properties’ that exceed those of starting expected that in a few years Slovenia could produce 10 to 40 materials. Waste management, 2015. 44: p. 48-54. tons of Nd-Fe-B alloy magnets per year on the basis of [9] Zakotnik, M., I. Harris, and A. Williams, Possible methods recycling within the European SUSMAGPRO project. And the of recycling NdFeB-type sintered magnets using the successful model could be later applied in different EU HD/degassing process. Journal of Alloys and Compounds, countries, using the recourse from EoL wind mills for example 2008. 450(1-2): p. 525-531 (like Scandinavian countries). However, this is not going to be [10] Farr, M., Production of anisotropic injection moulded possible without legislative changes within the EU that are NdFeB magnets from end-of-life sintered magnets. 2018, crucially needed to encourage this activity and contribute to the University of Birmingham. circular economy, not to forget the most important thing the [11] Lixandru, A., et al., A systematic study of HDDR stimulations from the local governments and European processing conditions for the recycling of end-of-life Nd-Fe-B Investment Bank. magnets. Journal of Alloys and Compounds, 2017. 724: p. 51- 61. This would strongly encourage local productions of rare earth [12] Shirayama, S. and T.H. Okabe, Selective Extraction and secondary minerals and permanent magnets. Otherwise, the Recovery of Nd and Dy from Nd-Fe-B Magnet Scrap by European rare earth industries i.e. permanent magnets will Utilizing Molten MgCl2. 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Tudor, Commercial-scale recycling of 508.4 NdFeB-type magnets with grain boundary modification yields 320 Real-time fluorescence lifetime acquisition system Matej Mrak Rok Pestotnik Rok Dolenec Andrej Seljak Center for Technology Transfer and Innovation Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39, Jamova cesta 39, Jamova cesta 39, Jamova cesta 39, 1000 Ljubljana, Slovenia 1000 Ljubljana, Slovenia 1000 Ljubljana, Slovenia 1000 Ljubljana, Slovenia +386 1 477 3381 / / +386 477 3287 Rok.Pestotnik@ijs.si Rok.Dolenec@ijs.si Andrej.Seljak@ijs.si Matej.Mrak@ijs.si ABSTRACT fluorescence lifetime (FL) imaging microscopy was nearly 155 We have developed a novel method for measuring the MUSD; the actual production was about 545 units. fluorescence lifetime instead of or in addition to its intensity. The major players in global Fluorescence Lifetime We demonstrated an acquisition system that is extremely fast, Imaging Microscopy market include Leica, Olympus, Zeiss, compact and significantly less expensive than current Becker & Hickl, HORIBA, PicoQuant, Bruker, Nikon, Lambert approaches. We are seeking for partners among optical and Jenlab. instrumentation manufacturers for licensing and technical cooperation agreements. We expect this technology to enter the biotech market, which alone (but not limited to the FL imaging microscopy) is This article covers the analysis of technology transfer processes expected to hit 727b USD in 2025 [5], providing tangible in correlation with expectations of newly developing biotech benefits for society. Many emerging applications require market. It concludes that technologies scaling project synergies sensors with a wide field of view, good spatial resolution and and outreach are of crucial importance for the development of very fast acquisition times - a parameter envelope not yet the technology for market purposes. reached by present research. Our goals are to develop a device that uses a wide field Keywords illuminator (diffused laser) and a wide field detector, using a Fluorescence lifetime; silicon photomultiplier; waveform single laser pulse, capable of continuous sub millisecond frame sampling; knowledge transfer; innovation; patent search; role of rates. Global Fluorescence-Lifetime Imaging Microscopy market analysis, technology commercialization. market is projected to reach $ 1.8 Billion by 2020, with a GAGR of 4% from 2016, and Asia will have a big dynamic 1. INTRODUCTION momentum on the market growth. This paper describes the application of high-energy physics technology for real-life applications. This is an area, 2. TECHNOLOGY DESCRIPTION which has always been considered to have a large potential, but 2.1 Background too little has been realized. In particular in the detector area Fluorescence is the emission of light by certain substances estimates show that there could be numerous unused (fluorophores) after they are illuminated with light of specific technologies. excitation wavelengths. Measurements of the fluorescent light Based on the mature technology developed for high-energy emitted by various samples are used in a very wide range of physics, we developed a technology that targets primarily at applications, such as imaging of cell structures, tracking of medical, biomedical, biotechnology and pharmaceutical fields, antibodies and DNA sequencing in biology, detection of cancer all of which experience significant market growth in the current cells in medicine and quality control in pharmacy. Besides time period, in particular in the past ten years. The application intensity, the fluorescence lifetime (FL) can also be measured, areas include a detection of the presence of certain organic as pioneered in application of fluorescence lifetime imaging compounds, measurements of the properties of samples or microscopy (FLIM). This has many advantages over the base tissue through the concentration of certain organic compounds, method, such as independence from fluorophore concentration, non-invasive determination of the chemical environment in the reduced damage to the sample (photobleaching) and ability to sample and non-invasive medical diagnostics and guided measure properties of the microenvironment in which the surgery. fluorophore is located (pH, oxygenation…). In this article we will first touch upon the promising Currently, FL measurements require sophisticated and market capitalization. We will describe the technology at hand expensive instrumentation. Typically, the fluorescence lifetime into more details, including the benefits, arising from it, the is determined with time correlated single photon counting state-of-the-art and the technology scaling. Secondly, we will (TCSPC) method, which is intrinsically slow. Mature touch upon the patent databases searches which assisted us in technological developments in the field of high energy physics estimating the technology potential, commercialization and IP (HEP) enable direct waveform sampling technology as protection strategy. Lastly, we will touch upon further important and a very cost-effective tool for fast FL applications. technology development and market development plans. By measuring the photodetector signal resulting from complete fluorescence response, FL can be estimated even from a single 1.1 Market evaluation excitation pulse. In the last several years, global market of fluorescence Real-time Fluorescence Lifetime Acquisition System lifetime imaging microscopy developed smoothly, with an (RfLAS) was assembled from low cost, commercially available average growth rate of 4%. In 2016, global revenue of 321 components in order to demonstrate the feasibility of such Secondly, having built up the necessary experience, and approach. Calibrated FL standards with lifetimes in the range of deep understanding of the system, we will make an integrated 2 ns – 9 ns were used to test RfLAS accuracy and performance scalable sensor, the real breakthrough in FL high speed for different levels of available fluorescence light intensity and imaging. The sensor will integrate efficiency optimized SiPMs, photodetector configurations. Using our prototype, we show bump bonded to the electronics wafer, which could be produced that FL of all three fluorescence standards could be measured in different technologies, with different performances, for with an accuracy better than 10% from only a single pulse of different applications. excitation light, which improves below 1% level by averaging Taking in consideration mass production, these sensors can be over only a few tens of pulses. Therefore, RfLAS demonstrates made at a very competitive price. CMOS technology is also that FL can be acquired practically in real-time for a much very affordable at scale, has a known roadmap and is very well lower price point than current state of the art. supported. These factors provide a secure path to aggregate The three critical components – the photodetector, scalable solutions. waveform sampler and data processing algorithms – lend themselves perfectly for implementation in a single chip. These 2.4 Project synergies and outreach are also areas of expertise of the authors, and the institutes they During the initial phases of the technology development, are affiliated with. The envisioned integrated detector would we were searching for cooperation with potential users and push the performance and robustness beyond the present state, partners, focused on fast FL acquisition. We will be able to and more importantly, using CMOS technology at scale, would quickly form a consortium capable of advancing RfLAS. collapse the price per unit, opening possibilities to use FL Laying the foundation in the dissemination program, we should obtained information in much wider areas as currently build quickly a community of users to provide application test available. cases and feedback, and most importantly increment to TRL 5- 7. 2.2 State of the art For additional dissemination, we intend to leverage one of In TCSPC method, FL is determined from a histogram of the strong points of our technology, its simplicity. We will take measured time delays between excitation pulses and individual an abundant amount of knowledge gained and develop an open fluorescence photons, resulting from said excitations. If more source, open hardware, single channel FL acquisition toolkit, than one photon is detected per pulse, the accuracy is degraded composed of hardware solutions based on off the shelf (pile-up effect), so the fluorescence signal has to be at a single components, data acquisition software and library of end-user photon level. The excitation pulse has to be repeated many experience. The feedback and exposure will directly benefit the times in order to obtain sufficient time delay histogram project, and increase the speed of development. statistics, leading to long acquisition times and possible photo bleaching of the sample. 2.5 Technology application and The acquisition times are even longer if imaging is required. In this case, laser excitation is scanned over the demonstration cases sample, and sufficient TCSPC statistics have to be accumulated Measurement of FL is a still growing field of research with for each scan position (image pixel). Alternative imaging many applications not realized. A technique, improved in approach is possible with single photon avalanche diode acquisition speed, and even more importantly, lower entry cost, (SPAD) arrays, recently developed specifically for FL has the potential to advance many fields of science and open application with time-to-digital converters (TDC) implemented new industrial applications. We have discussed concrete on a single chip. These devices have an intrinsic limiting factor, applications with potential users, including a pharmaceutical the sensitive area is somewhere between 1% and 20 % [1] as production company, high tech company developing most of the space is used for electronics, and prototypes have a monitoring and metrology technology for food industry and relatively small pixel count. national health institute. FL is also measured using frequency-domain technique, With just this batch of early adopters, RfLAS would improve where it is derived from phase shift between modulated development and monitoring of biopharmaceutical production. excitation illumination and resulting modulation in fluorescence This includes an increase of the quality of food available to signal, and gated detection, where FL is estimated from ratios consumer and reduction of wasted food by measuring the of fluorescence signal at specific time gates. ripeness of fruits and detecting presence of bacteria on food products; advance the accuracy and speed of diagnostics of Currently, FL measurements require sophisticated and histological samples; and contribute to a wide range of material expensive setups, and certain time to reconstruct the FL. In case science research. of imaging, a few frames per second can be achieved at best for sufficient image resolutions [2]. 3. ANALYSIS OF MARKET OPTIONS 2.3 Technology scaling 3.1 Technology assessment In our development plan, we will first build from the Supported by a group of specialists we performed a state selected off the shelf components, a highly integrated multi- of the art examination for the mentioned technology. channel version of the device. It will be fully decoupled from We found that technology has a significant advantage over laboratory equipment; therefore, it can be lent or sold to early the current state of the art. Some technologies touch on similar adopters. These are crucial for us, we need early feedback, measurement methods and use language and definitions in dissemination, and to validate and demonstrate the device in a patent claims to cover a very wide range of almost all real operational environment. An extremely important aspect is measurement options, but do not cover the details of also presence on the market. Having a community of users, and photodetector implementation. This is one of the significant a device that can be demonstrated in real operating improvements of our technology: we use silicon environments will create the foundation for the third step. photomultipliers (for photodetectors), in connection with the 322 digitization of the signal from the photodetector using a chip 2.Fluorescence AND lifetime AND photomultiplier AND and the principle of fast waveform detection. waveform AND sampling (6 records) There are also related patent applications and patents, 3.Fluorescence AND waveform AND photodetector (51 which describe significantly slower, more complex devices or records) use alternative technology (TCSPC), which requires higher 4.Fluorescence AND waveform AND sampling AND laser energy input to operate. The higher laser energy also photomultiplier (14 records) results in photobleaching, which is in our technology avoided due to single photon regime of acquisition. The most related The results obtained with the second, third and fourth patent application, which also uses a silicon photomultiplier in search sets contain 71 results. Upon examination, 6 of the 51 conjunction with the use of a digitization chip and direct hits turned out to be highly relevant and 2 relevant. Of the other waveform sampling, does not describe a significant 14, 4 were highly relevant and two relevant, and of the last six, improvement in technology. These are namely the simultaneous 3 were highly relevant and 2 relevant. It turned out that the capture of several sensors simultaneously, capturing the most relevant search was under point 4, where the largest share spectrum, which is an important analytical contribution in the of relevant hits was. However, the search under point 3 is also submitted patent application of the presented device in the important for finding market orientation. analysis and processing of fluorescent times. 3.2 Benefits and market placement A silicon photomultiplier is a very fast photodetector, whose response to a single photon is faster than the fluorescence lifetime. Therefore, the shape of the electronic signal, i.e., the waveform, output by the silicon photomultiplier will follow the exponential decay of the fluorescence light resulting from a single pulse of excitation. If the resulting waveform is sampled with sufficient accuracy, the need for long accumulation of single-photon arrival times and large excitation light intensities can thus be avoided. Excitation light with low intensities reduces the risk of photo bleaching. Silicon photomultiplier photodetectors and waveform sampling chips developed for the needs of high-energy physics experiments have become low-cost, off-the-shelf components. Thus, the method allows a cost-effective way to measure the fluorescence Figure 1: Top Assignees in the World in the field of lifetime and, at the same time, avoids lengthy data acquisition fluorescence lifetime measurements and photo bleaching of the sample. Even though we kept in mind that a proper Freedom-To- The main advantages of the method proposed over TCCSP Operate analysis (FTO) can only be performed when the are cost-effective compared to common TCCSP technology, product is defined, the patent analysis also has given the long accumulation of single-photon arrival times and large authors insight into which companies have shown an interest in excitation light intensities of TCCSP are improved and this type of technology. Top Assignees in the World can be excitation light with low intensities reduces the risk of photo found in Figure 1. Derwent Innovation overview of the field bleaching. shows a current prevalence of US Universities and Japanese The technology is in late early stage of development and is companies in the closest technology searches. fully available for demonstration. It has been developed with Due to the results of the review of the state of the art, we the core funding of Slovenian Research Agency and also decided to prepare documentation for the disclosure of the supported in part by ATTRACT Phase I. Due to the situation in official invention. it makes sense that intellectual property is the technology and market field, it was determined, that it is properly registered with the JSI (it can also be used as a high relevance that its IPR status is arranged. technical improvement / hidden knowledge) - also in terms of the possibility of rewarding inventors for inventions created 3.3 Database searches during working hours. We have prepared an overview of the state of the art with the help of the commercial patent database Derwent Innovation. 3.4 Market assessment In the review, we considered patent applications and patents The size of the market for measuring fluorescence time, filed anywhere in the world, and searched using the following according to data from companies engaged in market research, key phrases: fluorescence lifetime, silicon photomultiplier, is currently estimated at over 250 mil. EUR at an estimated waveform sampling, and a specific content keyword that the average annual growth, since 2016, somewhere around 4%. The authors of this contribution consider as a part of their secret advantage over the existing offer is mainly in the relatively knowhow and is not going to be revealed. favorable design / price of the technology (silicon photomultiplier), speed of data capture and processing, We tested different combinations of words and compared prevention of photobleaching and especially in the possibility the obtained results with each other. We reviewed the results of of simultaneous capture of multiple wavelengths of light, the following search strings in more detail: obtaining important additional information for further 1.Fluorescence AND lifetime AND silicon AND processing. photomultiplier AND waveform AND sampling AND specific Of course, the market analysis would be more significant content keyword (No records) and in particular more reliable, if we could identify the first specific application(s) to be addressed by the technology, and 323 then count the potential end users and multiply by the assumed The physical aspect requires multiple R&D cycles which is price of the equipment to arrive at an accessible first market. slow and costly. To mitigate the failure in this task, we will start This is an ongoing process which we hope to continue in the by assembling some of the ideas we already have on low cost next steps. CMOS fabs and unveil potential issues toward high integration. At each iteration, interested users shall be able to test our We have already established contacts with companies, but devices in their respective environments. without adequate protection of intellectual property, contacts cannot grow into more serious forms of conversations and 4.2 Liaison with student teams and socio- exchange of technical information. economic study Following proper registration of intellectual property with Our group are open for collaborations, and look forward to the JSI, the marketing plan is expected to include: (i) the establish reliable partnership with users, partners and preparation and publication of a technology offering in stakeholders. Our plan envisages their presence from the very commercial databases; (ii) contacting the main players from the beginning and will provide support in their future endeavors, by list we created as part of internal market research; (iii) providing them with better and more advanced instruments. Of depending on the response from the main players, active special interest are Master students, the next generation of marketing to other potential partners (through direct contact of STEM engineers, which will, one hopes, adopt our technology. potential partners, participation in international partnership It is very rewarding having the possibility to empower the events and active marketing within sectoral groups, a project of younger generation, and give them tools to cover the fear of the European Commission). missing out new opportunities in such an early stage, searching for other possible applications of the developed chip, that may 3.5 Continuation of intellectual property include PET, encrypted LIDAR, and other machine vision protection applications Given the high technological potential (according to the state of the art) and the high market potential, it makes sense to 5. CONCLUSIONS apply to the Office for the Protection of Intellectual Property, The researchers come from a Slovenian public research which conducts a full test, UK-IPO, which we also propose to organization. Their research involves experimental particle find out within 6 months the invention is new and on an physics on large particle accelerators and development of inventive level. Namely, we will receive an international complex detectors. They have analyzed their options with opinion on the patentability of the technology (ISR - transferring the technology in question, performed market and International Search Report) from a certified ISA (International technology assessment and decided upon an IP and market Search Authority), on the basis of which we will be convinced strategy. Future steps involve in particular wider interaction of the novelty and inventive step of the proposed technology. with potential customers and further development towards a The selection of an office that performs a full test is also a product for the market. precondition for co-financing the work of patent attorneys Even though the process of the transfer is described in a within the Technology Transfer project financed by Slovenian historically relevant manner, the authors also acknowledge, that Ministry of Science and Sports. there have been many setbacks within the process itself. It is not Technology and market assessments proved the relevance that every step has been performed flawlessly, without mistake, and the need for patent application protection. setback, delay or disappointment. For example, it took a long time to arrange the internal take up of the technology at the 3.6 Technology commercialization public research organization, even longer to arrange for the dual We are in the process of obtaining IP protection for the ownership between the two primary owners, both public core aspects of our development, with patent applications research organizations. We need to point out these facts, currently filed in UK and European offices. We are in talks with although we are, for non-disclosure issues not entitled to two companies interested in technology, with one we are in the discuss the details here. process of signing NDA. Other private entities expressed The partners are sought among optical instrumentation interest for the development of front ends and data display manufacturers. As a public research organization, the software. The multichannel instrument will support our researchers are available for different sorts of collaboration: commitment to advance as quickly as possible to step three of Potential partners are offered a license to the granted patent our development program, to enable the community and users under licensing agreement. Technical cooperation for the to have on disposal a price competitive and robust instrument development of a complete instrumentation device for for their application. measuring the fluorescence lifetime by this method is also considered a viable option. 4. FURTHER TECHNOLOGY, IP AND The timing of technology development is suitable for MARKET DEVELOPMENT PLANS inclusion in technological processes in the market. With the 4.1 Envisioned risks analysis of the market and patent saturation, we gained an overview of the state of the art and the possibilities for further Our main target is the development program of highly market orientation. In our opinion, with the timely protection of integrated sensors, potentially having some degree of data intellectual property, we have achieved an optimal position for processing on chip. Modelling, design, production, assembly further marketing activities. and testing of such devices are, in a vast majority, also areas of expertise of the authors [6, 7], and the institutes they are affiliated with. We intend to prepare a simulation of such a 6. ACKNOWLEDGMENTS device, to predict its performance and share the performance This project has received funding from the ATTRACT envelope with early adopters to shape its final form. project funded by the EC under Grant Agreement 777222. 324 Technology marketing support has been obtained through CTT, [4] Tsai, H. M. et al., 2017. Note: Rapid measurement of JSI. fluorescence lifetimes using SiPM detection and waveform sampling, Review of scientific instruments, 88: pp. 7. REFERENCES 096107. [1] Bruschini, C. et al., 2019, Single-photon avalanche diode [5] Biotechnology market analysis accessed 11/8/2020 imagers in biophotonics: review and outlook, Light: https://www.grandviewresearch.com/press-release/global- Science & Applications, Nature. biotechnology-market [2] Liu, X. et al., 2019. Fast fluorescence lifetime imaging [6] Seljak, A., et. al., 2018, Prototype readout system for a techniques: A review on challenge and development, multi Mpixels UV single-photon imaging detector capable Journal of Innovative Optical Health Sciences, 12(5): pp. of space flight operation, JINST 13(02): pp. T02003- 1930003. T02003. [3] Ritt, S. et al., 2010, Application of the DRS chip for fast [7] Dolenec, R., et al., 2017, Ultrafast detection in particle waveform digitizing, Nuclear instrument and methods in physics and positron emission tomography using SiPMs, physics research A, 623, pp. 486 – 488. Nuclear instrument and methods in physics research A, 876, pp. 257 – 259. 325 Regulated toxicity-testing: Spinning out a company in a rapidly changing market Janez Štrancar Špela Stres Jožef Stefan Institute Center for Technology Transfer and Innovation Jamova 39 Jožef Stefan Institute 1000 Ljubljana, Slovenia Jamova 39 +386 1 477 3226 1000 Ljubljana, Slovenia Janez.strancar@ijs.si Spela.stres@ijs.si ustanovah ustvari povezan novi IP. Prikazuje, kako postaja ABSTRACT omenjeni IP izziv za institucijo, in korake, ki jih je treba sprejeti, da se tehnologija pretvori v podjetje v nek turbulenten sektor. Today, various chemicals and materials are introduced into our daily life. To guarantee their safety, number of tests have to be Članek se loti tudi glavne dileme, kako naj nove tehnološke applied, ranging from simple testing on cell cultures ( in vitro) to rešitve ostanejo skrite, če jih morajo regulatorji najprej sprejeti. costly animal tests ( in vivo). In case chemicals are planned to be S tem je povezano tudi vprašanje, kako lahko prepričamo odbore delivered to a human body, many clinical tests are also required na raziskovalnih institucijah in tudi vlagatelje, da zadevna to be performed on humans. Logically, earlier stages of testing tehnologija dejansko ima (ogromen) poslovni potencial. are used in selection, for example, of drug candidates or vaccines, or in early decision, for example, to remove dangerous materials Ključne besede from R&D pipelines as soon as possible. Unfortunately, the very Biotehnologija, spinout podjetje, prenos intelektualne lastnine, expensive intermediate step – in vivo animal-based testing often napovedovanje bolezni, nadomestki za živalska testiranja. provides wrong answers. Alternatives are being searched for and entire market is about to change with political decisions 1. INTRODUCTION overtaking scientific and technological developments. This article covers a relatively new field of how to deal with a 1.1 The prior art of the technology situation arising from the fact that an associated novel IP is Currently, drug, vaccine and material development workflows generated in public research institutions. It depicts how it heavily rely on expensive animal testing, used to reduce selection becomes challenging for the institution and steps to be taken to of possible candidates later on entering the preclinical and spin the technology out into a company to a particular turbulent clinical testing phases that need to prove these candidates do not sector. harm human health. Unfortunately, molecular driven disease The article also touches upon the main dilemma on how to keep mechanisms are very much different between test animals and the novel technology solutions hidden if they need to be adopted humans [1], leading to almost catastrophic 95% probability of by the regulators first. Related to this is also the question, how failure of, for example, drug candidates at the end of drug can one convince the committees at the research institutions as developments cycle [2]. well as the investors that the technology in question actually do This makes the later extremely cost inefficient with costs of 300 hold (enormous) business potential. - 2000 MIO $ per drug development [3]. Other sectors, such as Keywords material safety testing, somewhat ignore this fact and stoically wait for the solution that more exposed and rich pharma sector Biotechnology, spin out, IP transfer, disease prediction, animal can bring out. alternatives. To boost the launch of numerous new material and chemicals in POVZETEK a safe, hazard-free way, the material-related health adverse effects should be more reliably predicted [4,5]. Currently, the Danes se v naše vsakdanje življenje uvaja različne kemikalije in most promising alternatives involve test assays [6] and QSAR materiale. Da bi zagotovili njihovo varnost, je treba uporabiti [7,8] models, but neither in vitro nor in silico tools can reliably številne teste, od preprostih preskusov na celičnih kulturah ( in predict in vivo adverse outcomes [9,10]. Particularly, the vitro) do dragih testov na živalih ( in vivo). Če je predvideno, da models unsuccessfully predict the systemic and chronic adverse se kemikalije vnašajo v človeško telo, je treba na ljudeh opraviti effects [11]. tudi veliko kliničnih testov. Logično je, da se prejšnje faze The need of urgent development of more reliable prediction testiranja uporabljajo pri izbiri, na primer pri ožanju nabora have been expressed by all the important policy- and decision- kandidatov za zdravila ali cepiv, ali pri zgodnji odločitvi, na primer za čimprejšnjo odstranitev makers around the world (OECD, US EPA, NIH, EC, ECHA, potencialno nevarnih snovi iz etc.), which have highlighted the necessity of exploring the razvojnih aktivnosti. Žal zelo drag vmesni korak - testiranje na živalih in vivo pogosto daje napačne odgovore. molecular mechanisms behind and identification of the key Zato se iščejo events in toxicity pathways associated. alternative, ki bodo spremenile celotni trg, kar sicer nakazujejo že politične odločitve, ki prehitevajo znanstveni in tehnološki During the last 5 years, 12 partners, joined within the razvoj. SmartNanoTox European project, have worked pushed the Ta članek zajema sorazmerno novo področje, kako se spoprijeti mechanistic-prediction of toxicity-related diseases beyond the scientific frontiers. Within this consortium, our group of s situacijo, ki izhaja iz dejstva, da se v javnih raziskovalnih biophysicists at Jožef Stefan Institute in Ljubljana has led one 326 of the most distinguished breakthroughs in the field in the last in terms of testing capacity, that originate in limited number of decade – the first mechanistic explanation of the transition from animal tests that can be performed in the EU and other players acute to chronic inflammation. This discovery enabled us to around the world. predict a spectrum of inflammatory outcomes without animal On the other hand, there is new material development sector with tests for the first time [12]. a fast growth of 20% per year that also requires extensive 1.2 The story behind the market and the toxicology testing [17]. With 10.000 patents filed every year to protect various nanomaterials and their applications in addition opportunity to around 50,000 publications on the same subject, this sector The only way to solve the lack of predictive testing that doesn’t will soon require much larger testing capacities. The only rely on animal tests is to develop living organ models (for testing possible boost can thus come from new technologies and new purposes) that develop physiologically relevant responses to players to guarantee material safety throughout new smart various drugs and other toxicants [13,6]. Several research groups prediction approaches [12]. and companies (Figure 1) are struggling to make such animal replacement models in a form of miniature and reliable organ copies. Figure 3: Target markets of acute & short-term repetitive dose toxicology testing in safety assessment of various substances and nanomaterials presented in the context of Figure 1: Small R&D institutes (black arrows), spun out regulatory framework and political decisions. from large universities (grey arrows), led the fields of in vitro model development. Some initial investments are shown with respect to the source – private (black) and public (green). To resume, the market is driving into a dramatic change: • animal tests are considered as golden standard, but are phasing out; • alternatives are lacking, imposing huge pressure on the regulatory bodies. This opens new exciting opportunity for new knowledge-based companies, but at the same time impose great risk due to unpredictable development of regulatory framework. The main contributions of the new companies in this field would Figure 2: The important moments and decisions that boosted cover exactly the market's greatest pains: the animal-free testing transition from animal-based testing into in vitro - or of drugs for human use and the prediction of the drug effects on organoid – based testing and forced big pharmaceutical the molecular level. companies to get more involved into the in vitro model development Not surprisingly, based on our new technology, which is registered as a secret know-how of the Jožef Stefan Institute, we decided to address this market need and participate in the product But, as expected this become a tedious, far from straightforward development and service provision in the new animal-free drug task full of trial-and-error steps. This makes the current testing as explained above. developments look like being stuck and represent big challenge for regulatory bodies, which actually don’t have clear plans on 2. INITIAL STEPS TOWARD THE how to implement political decisions [14] (Figure 2) and public SPINOUT COMPANY pressure (to eliminate animals from testing). The initial steps we took were connected to shaping the idea into In terms of market size, toxicology testing market (Figure 3) a market plan and creating a team to enable the creation of the currently values at around 20.000 MIO EUR per year [15]. market plan, sorting out the IP issues with possible other Around of 10% of this market is driven by REACH EU institutions and settling the IP relations within the research legislation [16], which implies testing procedures for about organization. thousands of substances that are produced annually with amounts greater than 1 ton per year. 2% of this REACH-associated Interestingly, in the need for a business plan, expressed by any of segment includes acute & short-term repetitive dose exposure our first investing contacts, we faced a lack of the expertise to testing with 10,000 animal tests required per year. Value of this create this business plan. Writing a business plan thus lead to market is around 400 MIO EUR per year. Taking into account complementing the existing team members. In our case, we have that most of the market need to be changed, this clearly represent identified the need for getting involved someone with more a big opportunity for biotech companies that can bring new economic background. This was a strenuous task for a group of alternative solutions to the testing market. Currently, the testing scientists that have rarely think about nonscientific issues. But, market exhibit 12% annual growth. But is soon to reach its limits when solved, another perspective enlightened the problem of 327 value creation leading us to much better vision of what the 3. SPINNING OUT AND THE IP company can do and where it can be after 10 years. Recursively, TRANSFER the business plan have become much more solid while increasing the core team and focusing to its strengths. Generally, a complex knowledge, required to elucidate basic While constructing financial projections for our business plan, mechanisms and further develop mechanisms-based testing or we have “accidentally” discovered where the business models of even disease prediction, as alternative toxicity testing concepts, the current service providers fail and where our scientific logically arise from large publically financed projects that mostly discoveries can really make a difference on a market (and in our run in well-equipped research laboratories in public research budget). As said before, the toxicity testing, as we know today, institutions. requires many in vitro and in vivo tests. Even without clinical The IP created has passed a well-defined procedure that, in our tests, all these tests cost lot of resources, making the business case at Jožef Stefan Institute, involves IP recognition by an very resource-limited and, if you want to pay experts with a expert panel followed by IP transfer to newly registered spin out reasonably good salary, struggling with either low added value company. IP must remain confidential during the processes and or being uncompetitive on the market. The problem is that it is at the same time ambitious enough. This becomes challenging required to run them all, but the results are not really being used due to several reasons: in a smart ways or assembled in bigger picture. They are just there to be reported. • procedures usually involve many different experts and some of them might have competing interests, but are involved in As discussed earlier, in the mean time, our scientific discoveries accordance with their elected position in the panels; brought us several steps further, identifying how to use simple but well defined in vitro tests to predict disease development, that • protection of IP in a form of patents might be problematic was till now possible only with much more expensive animal because the patent application is disclosed to public sooner tests. This in turn release the business model from its limitations than the company might start making revenue to defend its to human resources and make it more knowledge dependent IP, making it more vulnerable; The strategy of filing a patent (with higher added value). This will be beneficial for our and then preventing the disclosure by withdrawing the company and the market, because the company business will be patent it in 18 months (and filing it again, in the same or in more competitive and the market prices will decrease at the same a modified form) has been disregarded. Patents might later time. on be filed, at this point in time the invention is protected as a secret know how; Conceptualizing a new company in our case was a challenging task, yet alone in a field that is about to change dramatically and • hiding IP in a form of secret knowhow might leave the where the constraints are blurring rapidly with time. impression that the inventions are not novel enough; many experts evaluating the proposal for IP recognition and The way that a company can be prepared to deal with such a company-associated business plans might therefore doubt challenge is stricktly by assembling together one big brain with about the potential of the idea; out-of-the-box thinking ability. Inspired by many extraordinary business cases from the human history, we learnt the following • the use of university-internal panels to evaluate invention lessons, while trying to set up our own company, Infinite- disclosures and IP can be considered of limited usefulness biotech: and it remains to be proven that the panel adds value in the • eyes of the VC’s. The core team need to dream about it, feel it by heart, and be ready to invest more than it can predict in the worst The role of IP-transfer-dedicated department is thus even more thought scenarios; important. In our case, both the Center for Technology Transfer • and Innovation at the Jožef Stefan Institute and the Scientific Although there is always one that lead them all, the Council of the Jožef Stefan Institute, were flexible and ambitious brainstorming is the real weapon of the team; the main enough to recognize the dilemma above and support us in all leader needs others to challenge each other while searching possible (right) ways: the IP has been registered by the institute for solutions that really makes the core idea; in a timely manner, the Scientific council confirmed the creation • The core team members must complement each other in of the spinout company and the Center for technology transfer terms of expertise and at the same time be ready to listen to and innovation made way and glued together all the necessary each other and adjust their ideas; nevertheless, they build pieces for the procedures to come together and obtain the general entire story from scratch; so they must function as one big official support. organism; Last but not least, as mentioned before, the IP is often created • Finding market opportunity is hard, but even harder is within larger publically financed projects, likely to involve creating business out of it; the team have to search for their several partners. This inevitably exposed entire process of setting strengths enabling them to create high added value and be up a spin out company to a problem of shared IP, which can delay recognizable by the market; entire process substantially. While some universities almost hysterically claim their shares even when it is hard for them to To conclude, although everyone expects that you have the core prove their participation yet alone their contribution, this team ready and you have already clarified all the business points fortunately did not happen in our case. ahead of writing the business plan itself, its actual the act of assembling the business plan that enables you to clarify of the Partners of the H2020 project SmartNanoTox easily realized that details. It helps you to search for the missing expertise and the core idea has originated from the work of our laboratory. complement the team members as well as to clarify many in However, in relation to multi-partner research projects and particular business/finance related points of the very same shared IP, it is important to distinguish between inventorship and business plan. the commercial rights. Inventorship is well-defined and one can contain inventorship even in larger projects. On the other hand the commercial rights can be shared, but the consortium 328 agreement should clearly state, that the partners will not block addition, any effort of entering the market as soon as possible commercialization. However, in our particular case no partner pays off with better business plan. In particular, it helps a claimed his share – despite the fact that the general trends were company to identify the group of services and products that have clearly defined already in the afore-mentioned H2020 project. higher added value and larger market potential. Further developments of spin out core technologies might thus be heavily 4. SEARCHING FOR THE FIRST influenced with the experiences gained through the first sales INVESTMENT activities. After exploring different possibilities, the best investor turned As expected, the fact that our idea and technology is disruptive out to be a person (“angel”) that is aware of the lack of solution to the established market, adds to the complexity that we have and that can see the market niche your new company is trying to experienced in their search for investors. address. In many cases, he/she is the CEO of already another While transferring the IP might be enough to start making company. He/She is able to clearly see the potential of your service-based revenue, it is actually far from sufficient to make knowledge and is willing to invest his/her resources (and/or revenue from products that allow a company to run into more attract others as well) and wait the minimum amount of time stable and less human-work-dependent business model. Keep in needed for the company to develop its core technologies for the mind that the research labs often focus on the basic mechanisms future. thus developing solutions up to a relatively low technological 5. CASE SPECIFIC DATA AND THE readiness level (TRL). Rarely, the TRL exceeds that of a proof- of-concept or a demonstrator yet alone that of validation of IMPORTANT MILESTONES technology in a lab or real environment. Up to a prototype, which The following details of our case timeline wants to illustrate the is really the one of the most important milestones of the company above and put all the discussion into a proper perspective: to enter the market, there is long way to go. • To speed up the required development cycle, a spin out company Market niche identification: 2017 • urgently needs an investment, which usually exceeds several First idea of the company: July 2018 MIO EUR. And despite the numerous venture capital funds (VC) • Decision to protect IP as secret knowhow: September 2018 and national agencies that all create an impression of • First round to potential investors / contact type / contact straightforward access to financial sources, the investment into a location: December 2018 / scout, mentor / Switzerland business, whose potential is yet to be truly developed, is very • 1st version of the business plan: February 2019 difficult to find. • First Financial plan and complementing the team: March 2019 On a first sight, incubators might look the best option for spin out • Second round to potential investors / contact type / contact company. Nevertheless, they are expected to support startup at location: June 2019 / intermediary / Germany regional or national level. However, it turned out they are • Third round to potential investors / contact type / contact completely inappropriate choice for spin out companies arising location: June 2019 / venture capital (VC) fund / Slovenia from public-funded basic research due to extremely limited • Final decision to make the company a spin out of Jožef financial support that fails to meet the need for large investment Stefan Institute: October 2019 after IP transfer. As stated previously, the TRL of the knowledge • in a given situation rarely exceed the proof-of-concept making it 2nd version of the business plan: October 2019 • far less attractive for direct financial investments. Start / End of the process of IP recognition (as secret knowhow): October 2019 / December 2019 During establishing our spin out company, we have learnt the two • Approval of the scientific council of Jožef Stefan Institute: very important factors that influence the decision of an investor January 2020 to invest into such story are: • Fourth round to potential investors / contact type / contact • location: November 2019 / angel related to venture capital a proof that the entire business endeavor does not belong to a “green field” category; (VC) fund / Austria • Major breakthrough done on scientific side relevant for • a proof that a company can start making revenue associated company business: September 2019 – January 2020 with the core technologies. • Negotiation for IP transfer conditions and formal In business, a “green field” means an idea that can be written on cooperation with date of signing the contracts: February 2020 – July 2020 a piece of paper with a dubious value that might hide lots of • Fifth round to potential investors / contact(s) type / possible pitfalls and obstacles, far from being developed to a contact(s) location: March 2020 – June 2020 / venture TRL high enough to start running even a small revenue. Despite capital (VC) funds & angels / Austria, Switzerland, its more or less clear message, we have noticed a very important Germany difference in feedback of the scouts and VCs related to the IP • origin. At the beginning, we approached them as a team with First demonstrator of the technology planned to use in a potentially powerful idea of the business and they rejects us product: April 2020 • almost instantaneously. Later on, when we approached them Sixth round to potential investors / contact type / contact already as a legal entity with IP transfer in progress, their location: April 2020 / angel, CEO, mentor / Slovenia response has changed. Although they were aware of the origin of • First round to offer services: June 2020 the IP – in both cases it originates from a large/renowned • Complete marketing/sales plan for the company’s services: research institution, their attitude change simply because of the September 2020 fact that there was an expert panel, which has already identified As can be noticed, from the market niche identification to a value of this IP before them. Passing this milestone has clearly complete marketing/sales plan three years have passed. The main brought us closer to reach the final investment. issues we encountered were twofold: Not surprisingly, ability of the company to start making revenue • In the field of registering the technology at the Public with its core knowhow is very important signal to investors. We research organizations (PRO) the deadlines constantly noticed that this is particularly important for large VC funds. In 329 moved because we were not sure if the registration is of the Scientific Council, all at the Jožef Stefan Institute, for their necessary and for what reason; as it turns out, the great support in the process of spinning out the company. registration itself is needed to enable the PRO to officially participate in the creation of the company in Slovenia; these 8. REFERENCES clarifications took about a year to settle in with the team and [1] Yue et al. A comparative encyclopedia of DNA elements in the responsible at the research department; • the mouse genome. Nature 2014 515:355 In the same field the time lag was also a consequence of a rigid PRO structure in the sense of the time urgency in [2] Seok et al. Genomic responses in mouse models poorly which a typical spinout company finds itself; however, the mimic human inflammatory diseases. Proc. Natl. Acad. Sci. procedures were carried out in the end in a timely manner; 2013 110: 3507. these procedures were ultimately carried out in less than two [3] Al-Huniti, Nidal (June 20, 2013). "Quantitative Decision- months; • Making in Drug Development". AstraZeneca. p. 23. In the field of clarifying internationally on how to create a Retrieved March 13, 2016. suitable team and how to attract with confidence a suitable [4] Bañares et al.,. CompNanoTox2015: novel perspectives amount of financing necessary to pursue with further from a European conference on computational technology development; these procedures took about two nanotoxicology on predictive nanotoxicology, years; the main issue being that a researcher at a PRO is not Nanotoxicology 2017, 11, 839. in a position to devote a significant amount of time into the [5] Clippinger et al., Expert consensus on an in vitro approach development of the market relations; • to assess pulmonary fibrogenic potential of aerosolized With this in mind it needs to be said that an additional issue nanomaterials, Arch. Toxicol. 2016, 90, 1769. might be seen in the state of the mind of the researchers who [6] Huh et al., Reconstituting organ-level lung functions on a believe that themselves are the only people who can chip, Science 2010, 328, 1662. properly present the technology and attract financial [7] Forest et al., Importance of Choosing Relevant Biological support. End Points To Predict Nanoparticle Toxicity with In any case, the marketing and sales plan has been completed in Computational Approaches for Human Health Risk September 2020. We plan to continue with the technology Assessment, Chem. Res. Toxicol. 2019, 32, 1320. development and plan to deliver the services to the market in [8] Dekkers et al., Towards a nanospecific approach for risk early 2021. assessment, Regul. Toxicol. Pharmacol. 2016, 80, 46. [9] Maynard et al., React now regarding nanomaterial 6. CONCLUSION regulation, Nat. Nanotechnol. 2016, 11, 998. [10] Nel et al., Policy reforms to update chemical safety testing, Scientific studies have clearly identified the need for a major Science 2017, 355, 1016. change in the toxicity testing framework and the politics decides [11] Drasler et al., In vitro approaches to assess the hazard of to realize this as fast as possible. This has created an exciting nanomaterials, NanoImpact 2017, 8, 99. opportunity for business that can be started directly from basic research discoveries. [12] Kokot et al. Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining Because of the huge pressure to bring the future into reality faster in the Lung Epithelium. Accepted in Adv.Materials 2020 than the new tech evolves, several milestones have to be met (doi= 10.1002/adma.202003913), linked to BioRXiv almost instantaneously: discoveries of the basic concepts, https://doi.org/10.1101/2020.02.27.966036 acceptance of the regulatory frameworks and establishment of the alternative testing market (and the trust in the same) that can [13] Jud et al. Ultrathin Ceramic Membranes as Scaffolds for replace the classical animal testing. Investors became reserved, Functional Cell Coculture Models on a Biomimetic Scale. simply because it is such a big step to the future. Despite the fact BioResearch 2015 4:1. that the future is already here and a revolution of the testing [14] REGULATION (EC) No 1907/2006 OF THE EUROPEAN market is inevitable. PARLIAMENT AND OF THE COUNCIL of 18 December In June 2019, I have been involved in an interesting discussion 2006 concerning the Registration, Evaluation, on tissue-on-chip technologies and the associated startup Authorisation and Restriction of Chemicals (REACH) - companies. The key dilemma associated with these small https://eur-lex.europa.eu/eli/reg/2006/1907/2014-04-10. companies was: why they still get big investments if they can’t and don’t make big revenues. [15] http://www.altex.ch/resources/altex_2009_3_187_208_Ro Yet. The answer given by the CEO vida.pdf . of one of the first companies of this kind was marvelous: investors invest into teams that will be capable of reacting to the [16] https://echa.europa.eu/regulations/reach/understanding- new market as soon as it will become approved (by the reach. regulators). [17] International Conference on Modern Trends in 7. ACKNOWLEDGMENTS Manufacturing Technologies: E.Inshakova et al. World market for nanomaterials: structure and trends 02013 (2017) We want to acknowledge my entire core team to solve numerous & EPO + USPTO search. challenges during the process of setting up the company. I also want to express my gratitude to prof. I. Muševič, head of Condensed Physics Department, and prof. D. Mihailović, head 330 Status quo of computer-implemented inventions in Slovenia and EU Urška Fric Nina Tomić Starc Faculty of Information Studies in Novo mesto Agricultural Institute of Slovenia Knowledge and Technology Transfer Office Technology Transfer Office Ljubljanska cesta 31 A Hacquetova ulica 17 8000 Novo mesto, Slovenia 1000 Ljubljana, Slovenia + 386 (0)7 3737 884 +386 (0)1 2805 262 urska.fric@fis.unm.si Nina.TomicStarc@kis.si Property Organization (WIPO), is clearly and precisely defined ABSTRACT in Slovenian and EU legal instruments, this does not apply to In Slovenia there is no legal basis for computer-implemented computer-implemented inventions [2]. A computer- inventions, and in the EU such inventions are not yet clearly implemented invention means any invention the performance of defined. Over the last twenty years there have been many heated which involves the use of a computer, computer network, or debates in the European arena concerning a single legal other programmable apparatus, the invention having one or instrument, but a final solution remains elusive. In Slovenia and more features that are realised wholly or partly by means of a the EU, legal protection of computer-implemented inventions computer program or computer programs1 [3]. Due to the recent thus remains on thin ice: there are certain non-obvious shift in innovation towards things of a digital nature, computer- combinations for obtaining a patent, but ultimately the decisive implemented inventions account for a large proportion of factor may as well be how the patent application is written. This present-day inventions and creations, and as such represent an status quo therefore necessitates an examination of this field: to important segment of intellectual property [5]. Patents and all arrive at a legal basis that would regulate the patenting of other intellectual property rights are the pillars of any computer-implemented inventions it is necessary to identify and innovation system and provide instrumental support in the address the most critical points. This is the issue that this article development of technology and in the growth of national deals with. It starts by presenting examples of computer- economies [6]. And although efforts to put in place appropriate implemented inventions, followed by an overview of the state legal instruments started over two decades ago, they ground to a of play – the status quo concerning legal protection in Slovenia halt in 2005, when, after a series of heated debates, the and the EU. European Parliament voted down a proposal for a directive of the European Parliament and of the Council on the patentability Keywords of computer-implemented inventions, which the European Commission (EC) had issued in 2002 [7]. At least part of the Computer-implemented inventions, patent, copyright, status reason why there is still no appropriate legal instrument is that quo, Slovenia, EU. such inventions are highly specific and demonstrating their technical contribution2 and industrial applicability3 may pose a 1. INTRODUCTION significant challenge. But to a large extent, the reasons lie After Slovenia joined the European Union (EU), adopted the elsewhere – perhaps in the poor understanding of certain euro, and entered the Organisation for Economic Cooperation exemptions that apply in granting patent protection to and Development (OECD), its integration into the European computer-implemented inventions. arena drastically improved, as did its international competitiveness. At present, information technology and This status quo necessitates an analysis of this field and requires digitalisation are highly developed, the country’s rankings in a that the most critical points be identified and addressed in variety of international indices prove that Slovenia is an trying to create a legal basis for the patenting of computer- advanced and digitalised country. Other EU members are implemented inventions in Slovenia and the EU. This article likewise considered advanced and digitalised, as the cutting- presents computer-implemented inventions, the history thereof, edge digital technologies they use make it possible to upend and examples past and present. The focus is on the status quo in existing business models and create new ones, facilitate the this field, in Slovenia and the EU, whereby we explore the development of new products and services, improve the possible ways of securing legal protection for computer- efficiency and competitiveness of the economy, and contribute implemented inventions with the current legal instruments, in to socio-economic development in general [1]. The particular when such inventions can be patented and when they digitalisation of the entire society and economy underpinned by intensive use of information and communication technologies has significant growth potential and as such provides the 1 A computer program is an algorithm written in a programming groundwork for the long-term development and language (e.g. C++, JavaScript, PHP, Python, etc.) that can run on a competitiveness of Slovenia, the EU, and Europe in general [1]. computer [4]. 2 Technical contribution means a contribution to the state of the art in a We live in an era where information technology may be field of technology that is new and not obvious to a person skilled in considered one of the most important industries; consequently, the art. It is assessed by consideration of the difference between the management of industrial property and copyright, which are in state of the art and the scope of the patent claim considered as a whole, the domain of intellectual property rights and are the subject of which must comprise technical features, irrespective of whether or not this article, are extraordinarily important. these are accompanied by non-technical features [3]. 3 Industrial applicability assumes that an invention is applicable in Whereas the legal protection of intellectual property rights, as industry if the subject of the invention can be produced or used in any defined by the Convention Establishing the World Intellectual economic activity, agriculture included [8]. 331 can be copyrighted. Finally, we highlight the open issues that vehicles to be recognised as computer-implemented invention, should inform future work, in particular in the context of how numerous experts will need to identify intellectual property and where technology transfer offices (TTO) can help issues related to autonomous vehicle technology, and to accelerate the adoption of such legal instruments and improve navigate the complex intellectual property landscape within this their clarity. rapidly developing sector [12]. 2. COMPUTER-IMPLEMENTED 2.2 Status quo of Legal Framework: INVENTIONS Slovenia 2.1 Theory and Practice The Slovenian Industrial Property Act (ZIL-1-UPB3), which Computer-implemented inventions are defined as inventions the determines the types of industrial property rights and the performance of which involves the use of a computer, computer procedures for granting and registering these rights, the legal network or other programmable apparatus, the invention having protection of rights, and the representation of parties, stipulates one or more features that are realised wholly or partly by means in Article 10, which determines the subject matter of patent of a computer program or computer programs [3]. A computer- protection, that “patents shall be granted for any inventions, in implemented invention can cover topics related directly to all fields of technology, which are new, involve an inventive information and communications technology (ICT), e.g. step and are susceptible of industrial application” [8] . Article compiling back-ups or data compression, or it can be indirectly 11, which determines exceptions to patent protection, stipulates that (1) “ related to ICT and only used to control other appliances or Discoveries, scientific theories, mathematical devices [9]. Although programs for computers are as such methods, and other rules, schemes, methods and processes for explicitly excluded from patentability (at least at the European performing mental acts as such shall not be considered Patent Office (EPO)), a product or a method that is of a inventions within the meaning of Article 10, and that (2) A technical nature, i.e. it produces a further (technical) effect patent shall not be granted for: (a) inventions, the exploitation beyond the normal functional interaction of a program and of which would be contrary to public order or morality; (b) computer, may be patentable, even if the claimed subject matter inventions of surgical or diagnostic methods or methods of defines or at least involves a computer program [9]. treatment practised directly on the living human or animal body, with the exception of inventions relating to products, in The first patent application for a computer-implemented particular substances or compositions for use in any of these invention in Europe was submitted in Great Britain in 1962. methods. [8]. This means the Slovenian Industrial Property Act The application was made by British Petroleum CO. Ltd., and does not deal with computer-implemented inventions. P. V. Slee and P. M. J. Harris. The patent for the invention A computer arranged for the automatic solution of linear Software4 that does not provide a technical contribution can programming problems was granted in 1966 [10]. The therefore be protected only by copyright, whereby ideas cannot computer-implemented invention is described as a computer be copyrighted. The appearance of a command line interface5 or comprising quick-access storage, slow-access storage, and an a graphical user interface6, on the other hand, can be protected arithmetic unit, arranged to automatically solve a linear as a registered design. At the Slovenian Intellectual Property programming problem by means of an iterative algorithm [10]. Office (URSIL) it is possible to get a patent for computer or mobile applications, but only under the condition that a technical contribution is demonstrated. One such example is a patent granted in 2012 for the invention A mobile application and procedure for the processing of environmental information, which solves technical problems in preventing the generation of waste, reducing the amount of generated waste, channelling waste into reuse, appropriate disposal of individual types of waste, reducing environmental pollution and reducing the demand for the production of new raw materials that subsequently pollute the environment as waste [13]. This was the first such patent granted in Slovenia. Another such example, also granted patent protection in 2012, is the invention A system for automatic detection and monitoring of harmful insects, which solves the problem of the time-consuming inspection of insect traps [14]. With the help of cameras in traps it detects and monitors harmful insects [14]. The third such example is the invention A system and method for printing and delivering of publications such as newspapers on-demand, which was Figure 1: Drawing of patent application GB1039141A for granted patent protection in 2019 and is classified as a special the invention A computer arranged for the automatic solution purpose printing device and device combining printing and of linear programming problems other functions [15]. The printing and delivery system consists One example of a computer-implemented invention that is of at least two internet connected units and a mobile application widely used every day and was granted patent protection in Europe is the electronic anti-lock braking system (ABS). In 1969 ITT Teves (Continental) unveiled an electronically 4 Software is a group of computer programmes that constitute a whole supported ABS system as a premium add-on feature of the in combination with hardware in a computer. 5 Mercedes Bens S-class, and in 2004 electronically supported A command line interface is an interface in the form of lines of text ABS systems became standard on all new cars in Europe [11]. that shows a prompt on the screen into which a user enters a command and executes it with the enter button. If the command is Another example of a computer-implemented invention that valid, it is executed. will probably change our everyday in the near future are 6 A graphical user interface displays elements such as icons and other autonomous vehicles. However, in order for autonomous tools. It is an interface between the user and the software. 332 that transmits location data to the printing and delivery device, 3.2 Employment and works made for hire includes account management functionalities, and sends The ZASP stipulates that the employer or person ordering the instructions for printing and billing [15]. work is entitled to all economic rights to a computer program if it is created by an employee in the execution of his duties or by 2.3 Status quo of Legal Framework: EU an author under a contract for a work made for hire. Economic In 2002 the EC issued a proposal for a Directive of the rights and other rights of the author to such a program are European Parliament and of the Council on the patentability of assigned to the employer or person ordering the work, computer-implemented inventions. After a series of heated exclusively and without limitations. In accordance with the debates among MEPs, the European Parliament rejected it in applicable regulations, the employer or person ordering the 2005 [3]. The adoption of this directive would have created a work and the employee (author) may agree otherwise, which single set of rules for the patent protection of computer- has also been confirmed by the Supreme Court of the Republic implemented inventions in the member states. The European of Slovenia in judgement II Ips 552/2003 [20]. In practice, Patent Convention Stipulates in Article 52(2) (c) that programs however, at least regarding computer programs created in the for computers are not regarded as inventions [2]. Recognizing course of an employment relationship, the worker and employer that the European Patent Convention (EPC)7 established a tend not to agree otherwise in the employment contract. The European Patent Organisation (EPO), which is responsible to Directive treats the transfer of economic rights to a created grant European patents. This is carried out by the EPO computer program the same way as the ZASP, but it deals only (supervised by the Administrative Council), which is not an with computer programs created in the framework of an agency or an organ of EU. It is an organ of the EPO, which has employment relationship, it does not regulate computer legal entity and it is an independent inter-governmental programs created under a contract for a work made for hire. organisation8 [16]. The status quo thus remains the same as in There are significant differences between instances when a Slovenia. Software that does not demonstrate a technical “classic” copyrighted work is created in an employment contribution can only be protected by copyright, which does not relationship, and when a computer program is created in an protect ideas. The appearance of a command line or graphical employment relationship. interface can be protected as a registered design, whereas a The ZASP also accounts for instances when an employee patent for computer or mobile applications can be granted if a creates a copyright work that is not a computer program, in the technical contribution is demonstrated. Under EPO rules, in the event of which it stipulates that economic and other rights of event of such, the software must be connected with the the author to this work are exclusively assigned to the employer hardware. for a period of ten years from the completion of the work (unless the parties agree otherwise in a contract). Upon the 3. COPYRIGHT AND COMPUTER expiration of the term, the rights revert to the employee. PROGRAMS IN SLOVENIA AND EU However, the employer can claim a new exclusive assignment of these rights, for adequate remuneration. A worker who 3.1 Copyright creates a computer program in the framework of an employment Computer programs are defined both in Directive 2009/24/EC relationship is therefore in a disadvantaged position compared of the European Parliament and of the Council of 23 April 2009 to workers who create other copyright work in the course of on the legal protection of computer programs (the Directive) their employment. [17] and the Slovenian Copyright and Related Rights Act (the ZASP) [18]. EU member states protect computer programs by Despite the copyright protection in place for computer copyright the same way literary works are protected under the programs, the Directive and the ZASP do not regulate the Bern Convention for the Protection of Literary and Artistic subject matter exclusively; they allow legal protection under Works [19]. While a computer program is defined by these other branches of law [21]. For computer programs, other legal instruments as a program in any form of expression and is branches include regulations on patent protection, trademarks, considered a written work, software does not enjoy copyright protection of competition, trade secrecy, etc. Due to this non- protection. Due to the requirement that copyright protection exclusivity, and the grey area between copyright and computer- applies to the expression of a computer program in any form, implemented inventions, computer programs are therefore often algorithms and programming languages that involve ideas and protected as trade secrets and as know-how. principles do not enjoy copyright protection. Preparatory design work leading to the development of a computer program is 4. CONCLUSION considered a computer program provided that the nature of the The status quo in the field of computer-implemented preparatory work is such that a computer program can result inventions, which are neither legally defined nor legally from it at a later stage. undefined in Slovenia and the EU, raises many open issues and When a computer program can be patent protected or when it provides opportunities for future work. In Slovenia it would can enjoy copyright protection depends on what kind of make sense to examine at which stage TTOs can problem it resolves. If a computer program resolves a business methodologically and substantively contribute to the problem, it is protected by copyright. In the event it resolves a examination and presentation of computer-implemented technical problem (and meets all other criteria for patent inventions at the level of the national patent office and to the protection) it can be protected with a patent. examination of non-obvious combinations that constitute computer-implemented inventions under the ZIL-1-UPB3. At the level of the EU and Europe as a whole, it is necessary to 7 The EPC is a multinational convention of which 38 member states examine how we may contribute to the creation of a legal basis participate in, including all 28 member states of the EU and other that would ensure uniform patenting of computer-implemented non EU member states [16]. inventions. 8 For the last 50 years, the EU's ambition to create a single, central court for the enforcement of European patents has been frustrated by TTOs are tightly integrated into the work of organisations that the EPO's existence as an autonomous, international organisation produce inventions. First and foremost, we use our know-how outside the EU [16]. to help researchers who create computer programs by verifying 333 what kind of problem their program addresses and how a Moed, U. Scmoch, and M. Thelwall, Eds. Springer Nature quality decision can consequently be made as to the protection Switzerland AG, Switzerland, Cham, 1007–1022. of intellectual property (a copyright or patent). [10] European Patent Office. ESPACENET. Patent Search. All things considered, we believe that TTOs should at a 2020. GB1039141 (A)–1966-08-17. minimum participate in public debates and present practical https://worldwide.espacenet.com/publicationDetails/biblio examples of researchers who develop computer programs at ?CC=GB&NR=1039141&KC=&FT=E&locale=en_EP public organisations, thereby contributing to a constructive [11] Glon, R. 2019. ABS Brakes helped Airlines make more decision-making process on the future of the protection of Money before they helped you stop. Digital Trends. computer programs. 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F. 334 Strategic intellectual property management system for universities and scientific organizations for efficient technology transfer Khvorostyanaya Anna Sergeevna, Ph. D. Lomonosov Moscow State University, Russia, Moscow Leading Researcher at the Center for Strategic Studies Institute of Mathematical Studies of Complex Systems +79151098661 Khvorostyanayaas@gmail.com researches’ results and being fairly treated. The question of ABSTRACT making the balance between scientists, universities and federal The technology transfer development is a strategic priority in parties is not only to appear within one organization. the economies of many countries. For a successful and efficient Universities and educational organizations are actively engaged technology transfer, a high-quality exchange process between in creating new products, but there is often no systematic work science and industry must be established. In this publication on commercialization - there are questions about attracting author review the specifics of Intellectual Property management industrial partners, setting up accounting for the result of systems in higher education institutions. Universities and intellectual activity and the amount of royalties pay out. scientific organizations should strive not only to create patents with public funds and publish in top-rated journals, but also 2. STRATEGIC INTELLECTUAL work efficiently with industrial partners to increase the commercialization level of their developments. For that PROPERTY MANAGEMENT SYSTEM purpose, it is necessary to create a specialized structure in the These problems of technology transfer can be solved by university – a technology transfer center – that could manage Strategic Intellectual Property Management System (SIPMS), Strategic Intellectual Property by using specific documents that which helps to build the commercialization stage step by step. form unique ecosystem. Speaking about the strategic priorities of such a system it should be working for the researches, university administration Keywords and industrial partners to make the mutually beneficial cooperation. This approach guarantees all the parties’ interests Technology transfer, strategic intellectual property to be considered and minimizes the risks to lose one’s management, universities and scientific organizations. intellectual property. It can also help to build the researches’ reputation, attract new employees, and, finally, meet the federal 1. INTRODUCTION demand for using the knowledge for the national economy In modern world and Russian practice, the main developers of benefit. innovative technologies and suppliers of developments with the There is a vital experience of such a system in Russia: National potential for commercialization are large universities, research Association of Technology Transfer has a Project Group that centres and laboratories. Universities and research organizes an intellectual property management system in higher organizations are increasingly responding to the needs of the education institutions [7]. The activities of this group are real sector of the economy for innovative developments by related both to the holding of events to popularize and involve making changes to R&D plans. Developing towards a larger- in the work of the vice-rectors of universities responsible for scale participation of universities / research institutes in innovations, as well as a wide range of experts in the field of economic processes, offices and technology transfer centres technology transfer and all interested market participants, and contribute to building communications with other participants to the implementation of a package of standard documents for in research activities and subjects of the real sector of the the IP management in universities and research centres. economy, contribute to improving the quality of fundamental and applied research, and intensify the cooperation and In preparing a set of National Association of Technology integration interaction development. Based on fundamental Transfer model documents, the Intellectual Property Policy for scientific research, the results of the development of these Universities and Research Organizations, adapted by WIPO and institutions, having an applied focus, allow the companies the Ministry of Education and Science of Russia, was used. acquiring them to form new strategic competitive advantages Pilot implementation of the IP management system to the based on significant technological superiority [1]. Today, there Lomonosov Moscow State University experience showed that is an aim on global and regional agenda to create the IP management rules in the local regulations should be first environment as well as the ways to make researches’ results consolidated. These regulations can be the Strategy and/or the commercial, to make it possible having an income from the Policy in the field of IP management. MSU version of such a intellectual property. The universities should become the document is the Provision on IP management, which latest reliable providers of the specific intellectual products to meet revision was approved in 2018 [8]. the federal and industrial demand. In many strategies of scientific and technological development of countries, this Speaking of key strategic principles of the efficient functioning aspect is qualitatively reflected – Russia [2], China [3], of the strategic system, implemented to the Lomonosov Germany [4], South Korea [5], USA [6]. It should also be Moscow State University, legal certainty, fair income considered the scientists’ interest for publishing their distribution, and stability could be mentioned. These principles are consolidated in the local regulations. The legal certainty 335 principle implies the right holder to have all the results of development and practical application of the Moscow intellectual activity certificated, all the rights transactions to be University developments in industry. confirmed by entering into a contract and fulfilling its Strategic IP management system implementation helped MSU conditions. get significant results in two important rankings: According to the fair income distribution principle, the - National University Ranking (Innovations unit). There were university pays costs to get and renew the patent, including the 849 scores (8th place) in 2017, 805 scores (5th place) in 2018, international ones. The income of the commercial using the and 774 scores (4th place) in 2019 [15]. intellectual property is shared as following: The authors receive 25%, the faculty – 40%, the university – 35% of the reward. - Invention Activity University Ranking (scores are summed). The amount of payments to the authors can be extended by the There were 57,9 scores (1st place) in 2017, 58,9 scores (1st head of faculty, using the funds which the faculty got in the place) in 2018, and 63,6 scores (1st place) in 2019 [17]. specified order [8]. There are about 900 items in the overall MSU IP portfolio. An important aspect of successful technology transfer on the There are also more than 30 valid license contracts made by part of the authors is associated with the motivational part. [1] MSU. At the same time, the income from RIA rights disposal For example, Higher School of Economics — National multiply.increased. As a result of successful SIPMS Research University pays 30% of net contractual income [9], implementation, the following information can be given: Saint Petersburg State University pays 50% of net contractual income for using intellectual property [10], Ural Federal 11 licenses were issued with fixed payments for the current University [11] named after the First President of Russia B. N. period and royalties for future periods; Yeltsin pays up to 50% of the royalty income. legal support of transactions with industrial partners were The stability principle means that authors should remain undertaken; confidential and report the university about the intellectual 119 notifications on disclosure of intellectual activity results activity result before there will be any information published. were processed; The university recourse usage makes intellectual activity result as the university’s property. Commission on university IP 42 applications for inventions/utility models were submitted to approves the key deal’s conditions, as well as the patenting Rospatent, 2 of them for international protection; geography. Earlier, the IP management process in MSU was 2 applications for industrial designs were submitted; decentralized and implied several departments’ parallel participation. Faculties were responsible for many matters in the 3 applications for University trademarks were submitted; field of IP management (including special legal, patent, 30 computer programs and databases submitted for registration; accounting matters). However, not all the faculties could afford employees from the field needed. That is why there came an received 55 patents for inventions/utility models; idea to reconstruct the IP management system. Moreover, it was necessary to do the rights inventory, analyse the demand for received 37 certificates for computer programs and databases; current intellectual activity result and prospective for the ones received 2 trademark certificates; at the application stage [8]. received 2 patents for breeding achievements [18]. The new IP management system is working in MSU since 2014 when the decision was taken on the pilot system There are also IP commission and Intangible Assets implementation. Russian Federal Service for Intellectual commission in the IP management architecture. The main chain Property (Rospatent) expertly supported the pilot of the system, NATT, is participating at all the stages of life implementation. The system is constantly developing, cycle. At the first stage of the research, the Association considering changing legislation, application practice, and approves the work conditions, announces the RIA creation, special ministries and departments’ recommendations. For forms a document on its legal protection, and participates in example, the Ministry of Economic Development of Russian making a request and applying for a patent. As all the actions Federation developed in 2014 [12] and finalized the mentioned above are made by one department, the amount of Recommendations on results of intellectual activity (RIA) patent applications has raised up to 100 a year. That is 80% management [13]. In 2018, WIPO and the Ministry of Science more that it was in 2014. After the grant of the patent, there is and Higher Education approved the Policy in the field of still commercial work to do. Be that we mean making additional intellectual property for universities and research centres [14]. research, communicating with appraisers, internal and external experts. As well as looking for partners, approving terms of the The main chain of a system implemented in MSU is Centre of deals on RIA rights disposal, and controlling over university Technology Transfer. The main goals of technology transfer and developers treatment [8]. centres are to promote the development of cooperation chains between science and business, attract investment for the In conclusion, it can be noted that MSU has successfully innovative projects implementation and the creation of implemented SIPMS, as evidenced by the results. It should be consortia, commercialize the results of scientific and technical noted that such a system is effective for establishing systemic activities, meet transfer innovative developments to industry interaction between main participants in technology transfer, and the market [16]. Centre of Technology Transfer of helps to set up a system work on commercialization and Lomonosov Moscow State University is a “one-step” facility consolidate innovative offers for industrial partners. The for both internal university work and processing external presence of such system in technology transfer centres helps to suggestions and external demand. It is staffed with employees work systematically even in the face of external challenges. The in the field of intellectual property management (patenting, main SIPMS value is to reduce uncertainty, regulate liability licensing, business development and legal issues) with various and establish a standard business process. The presence of the competencies that allow assistance in the promotion, same template for the industrial partner technological request makes it possible to create an innovative development catalog more effectively. Taking into account the professional 336 competence of each university and its structural organization, [10] Saint Petersburg State University (SPbU). Transitional SIPMS is easy to adapt and change. NATT specialists are provision on the procedure of paying the reward for using currently implementing SIPMS at Sechenov University and results of SPbU intellectual activity. [Electronic resource] D.Mendeleev University of Chemical Technology of Russia [8]. // URL: https://spbu.ru/ (date of the request – 17.05.2020). Using this experience, we can talk in the future about the [11] Ural Federal University. Policy in the field of intellectual possibility of scaling it in order to form the maturity of property. [Electronic resource] // URL: universities to introduce their developments into national and http://inno.urfu.ru/admin/ckfi nder/userfi les/fi global industry. les/doc20121120170643.pdf (date of request: 17.05.2020) 3. REFERENCES [12] The Ministry of Economic Development of the Russian [1] Khvorostyanaya A. S., Alimuradov M. K. The Value of Federation formed the recommendations for organizations the Participation of Actors in the Technology Transfer on results of intellectual activity rights disposal, and the Process: a Strategic Vector // Administrative consulting. Government of the Russian Federation approved these 2020. No. 5. P. 128–137. recommendations. [Electronic resource] // URL: http://old.economy.gov.ru/minec/activity/ [2] Presidential Decree No. 642 of 01.12.2016. On the sections/instdev/doc20140210_4 (date of request: Strategy for Scientific and Technological Development of 17.05.2020). the Russian Federation. President of the Russian Federation. [Electronic resource] // URL: President of [13] The Ministry of Economic Development of the Russian Russia//kremlin.ru/acts/bank/41449 (date of the request – Federation improved the recommendations on RIA rights 17.05.2020). disposal. [Electronic resource] // URL: http://old. economy.gov.ru/minec/about/structure/depIno/201703100 [3] China's Scientific Revolution. Scientific American. 1 (date of request: 17.05.2020). [Electronic resource] // URL: https://blogs.scientificamerican.com/observations/chinas- [14] The Ministry of Science and Higher Education of the scientific-revolution/ Russian Federation. Policy in the field of intellectual property for universities and research centers. [Electronic [4] Industry 4.0 - Germany's 4th industrial revolution. resource] // URL: Germany Trade and Invest. https://www.gtai.de/gtai- https://minobrnauki.gov.ru/common/upload/library/2018/1 en/meta/press/industry-4-0-germany-s-4th-industrial- 0/Politika_v_oblasti_IS_s_VOIS.pdf (date of request: revolution-78306 17.05.2020). [5] Yi, Sang. (2012). Kuhn's The Structure of Scientific [15] Interfax company. National university ranking. [Electronic Revolutions in South Korea. East Asian Science, resource] // URL: Technology and Society: an International Journal. 6. 533- https://academia.interfax.ru/ru/ratings/?rating=8&year=20 539. 10.1215/18752160-1905942. 19&page=1 (date of request 17.05.2020). [6] Shapin, Steven. (2018). The Scientific Revolution. [16] Khvorostyanaya A.S. (2020). Strategicheskaya rol tsentrov 10.7208/chicago/9780226398488.001.0001. transfera tekhnologii v razvitii kreativnyh industriy ekonomiki [Strategic role of the technology transfer [7] National Association of Technology Transfer. NATT. centers in the development of creative industries of the [Electronic resource] https://rusnatt.ru/napravleniya- economy]. Kreativnaya ekonomika. 14. deyatelnosti/rid/ (date of the request – 17.05.2020). (7).doi:10.18334/ce.14.7.110546 [8] Metlyaev D. Ragozin P. UNIVERSITY IP [17] Invention Activity University Ranking 2017. Expert MANAGEMENT SYSTEM BY EXAMPLE OF analytic center data. [Electronic resource] // URL: MOSCOW STATE UNIVERSITY// Intellectual property. http://www.acexpert.ru/ analytics/ratings/reyting- 2020. No 6. P. 17-22. izobretatelskoy-aktivnosti-vuzov.html (date of request: [9] Higher School of Economics — National Research 17.05.2020). University. Provision on the financial incentive in the field The activities of the Technology Transfer Center. of intellectual property in Higher School of Economics — Technology Transfer Center. [Electronic resource] // National Research University. [Electronic resource] // URL: http://www.ctt.msu.ru (date of request: 21.09.2020). URL: https://www.hse.ru/docs/86975404.html (date of the request – 17.05.2020). 337 Strategic research and innovation partnerships as enablers of technology transfer Maja Bučar Aleš Lipnik Faculty of Social Sciences Institute for economic research Kardeljeva ploščad 5 Kardeljeva ploščad 17 SI-1000 Ljubljana, Slovenia SI-1000 Ljubljana, Slovenia Phone: +386 1 5805-195 Phone: +386 1 5303 810 maja.bucar@fdv.uni-lj.si ales.lipnik@ier.si ABSTRACT human and material, with the objective to raise competitiveness Paper address the question of knowledge -transfer activities in and value added in selected sector. the case of two (business and research-led) SRIP. SRIP- One of the tasks of SRIPs, as specified in documentation Strategic research and innovation partnerships is the form of explaining the S4, is exchange of knowledge and experience as collaboration between business sector, public research well as knowledge transfer (SVRK, 2015b). SRIPs should organizations (PROs) and other stakeholders introduced by enable flow of knowledge among the members, from the PROs Slovenian Smart Specialization Strategy. In the paper, we try to to business sector as well as among the business partners find similarities and differences in their positions, perceptions themselves (for example, from large to small and medium size and approaches toward technology transfer, as well as enterprises). They should also enable the transfer of knowledge challenges of this process on the level of SRIP as an instrument among the same stakeholders. and on the level of Slovenian innovation system. The implementation of this expectation of the policy makers, which was spelled out in the public call for the establishment of Keywords SRIPs, is the subject matter of our short paper. SRIPs were Technology transfer, Smart Specialization Strategy of Slovenia, established in the fall of 2017 and their first mid- term SRIP Strateško razvojna inovacijska partnerstva- Strategic evaluation/ monitoring was performed in 2019 (FDV, 2019). development innovation partnership. The monitoring looked at the issues, specified in the public call: 1. INTRODUCTION • Implementation of the objectives in Action plans With adoption of Smart Specialization Strategy of Slovenia • (S4) in the end of 2015 (GODC, 2015a), a new form of Progress in promotion of joint development and services, collaboration between business sector, public research especially in cooperation and development of joint RRI organizations (PROs) and other stakeholders was introduced. initiatives to develop and market higher value-added So-called Strategic research and innovation partnerships integrated products and services; (known as SRIPs, GODC, 2015b) were established in all nine • Introduction of horizontal enabling technologies within priority areas of S4, following a public call, issued by the vertical value-added chains Ministry of Economic Development and Technology in December 2016 (MEDT, 2016). • Implemented market manifestations, resulting from joint activities. The 3 priority pillars of the Smart Specialisation (a) Digital, b) Circular and c. (S)Industry 4.0 have nine areas of application: Mid-term monitoring of the SRIPs resulted in the report to the funders, where the successes as well as some of the problems in (i.) Smart cities and communities; functioning of the SRIPs were identified. The main conclusion (ii.) Smart buildings and homes, including wood chain; of the monitoring phase was that the SRIPs are a good (iii.) Networks for transition into circular economy; instrument to support RIS3 implementation and that most of (iv.) Sustainable food production; them have achieved an impressive level of cooperation among (v.) Sustainable tourism; their members from different spheres (large and small (vi.) Factories of the future; companies, public research institutions and in some cases, also (vii.) Health-medicine; communities/ municipalities). (viii.) Mobility; (ix.) Development of materials as products. Since transfer of knowledge was not considered the primary task in the initial phase of working of SRIPs, the mid-term The idea of the policy makers was to support the formation of a monitoring had not focused on this issue. Still, we believe it is platform, similar to clusters, in each of the priority areas, based important to examine how they approach this topic, if at all. To as a long-term public –private partnership. The members of learn more about the position of SRIPs with regard to SRIPs are to identify value chains within selected priorities technology transfer, we designed a small questionnaire for two (deepen the relatively general priorities) through providing fora very different SRIPs: one is primarily business- dominated and for continuous entrepreneurial discovery process (EDP). SRIPs the other with more pronounced impact of the public research should provide an environment for cooperation in joint R&D organizations. Their views on the role of SRIPs as agents for projects of various type and enable innovation activity technology transfer are presented in the next segment. eventually leading to market penetration in S4 priority areas. The objective is to focus and coordinate both private and public investment in R&D and innovation, share capacities, both 338 2. INDUSTRY-LED SRIP AND condition for cooperation between PRO and business entities in such projects, explained by the fact that the business partners TECHNOLOGY TRANSFER contribute most of the co-financing. So far, research-led SRIP First, we wished to learn if the SRIP coordination office deals had no case of direct technology transfer, where the with the questions, relating to technology transfer, especially in coordinating office would be directly involved. view of relatively limited human resources. The answer revealed that the technology issues are mostly addressed at the As technology transfer is not recognized as a crucial level of Council of Experts, where new developments in their topic/activity of the SRIP, SRIP coordination office does not priority field are discussed, especially in the areas of interest to detect special needs or requests from the side of SRIP members. their members. The office itself has no capability to assist in the Therefore, activities of SRIP coordination office are oriented actual technology transfer deals; they do however monitor mainly toward awareness raising and trainings of members technology developments at global level and pass relevant through special events and thematic workshops. Research-led information to the members. They see their role mostly in SRIP coordination office sees the opportunity for a more active establishment of initial contacts between different members, role of SRIP in the technology transfer only if the main where the office identifies potential for cooperation. Beyond stakeholders would request such service, as SRIP itself at the this phase, they currently do not act. moment has no planned resources for technology transfer. The issue of transfer of technology is in the opinion of the Research-led SRIP coordination office also detects some office an important one for their members, but the SRIP can obstacles, which prevent transfer of knowledge and technology. only help in raising the awareness and the promotion of the In the first place, they point to a relatively complicated and long protection of intellectual property rights, sharing information on lasting procedures for knowledge transfer, which demand cases of successful transfer of knowledge to the market, but not specific and high professional knowledge in different areas. with the actual process of transfer. Secondly, as procedures are mainly focused on financial part of transfer (i.e. licenses or patents costs), this is not found as Explicitly, the members have not requested services or highly stimulating, especially for Spin-out companies. Third: assistance with transfer of knowledge. They do take part in the legally very complicated procedures for knowledge transfer in events, organized by the Office, where experience and most PRO, especially universities, requiring a long list of knowledge on the topic of various members is presented. The approvals, discourages the process. The SRIP sees solution in Office has also organized a set of workshops with one of the changing the current, very restrictive legislation. In order to leading Slovenian expert on intellectual property rights simplify and standardize these procedures, SRIP suggests protection. The workshops had sufficient attendance, but not preparing Toolbox for SME members in order to help and exceptional, suggesting that the topic is not the most support them in such procedures. problematic in their industry. The Office of SRIP sees itself primarily as an intermediary: 4. DISCUSSION AND CONCLUSION their role is to monitor the trends in global industry, be well With both types of SRIPs, we can find some similarities and informed of the development plans and needs of their members common issues: to the first question on the engagement of the and act as a matchmaker for the exchange of ideas and SRIP coordination offices in transfer of technology, both formation of joint R&D projects. Up to now, they have not pointed out the lack of human resources with specific identified specific barriers to transfer of knowledge or knowledge and competencies in the field of technology transfer. technology. They do, however, observe inactivity among PROs, This is the main reason why they cannot play the role of especially research institutes in searching the contacts with technology broker. However, this issue does not seem to industry. Here, researchers from the universities, especially represent significant problem as this role is also not expected younger ones, are more eager to cooperate with business. On from their members. From the side of SRIP members, the role the other hand, the research institutes wait to be approached by of SRIP office is not seen in the field of TTO. the industry and, often reluctantly, respond. Secondly, policy maker, at the time of establishing SRIPs, listed a long range of tasks for the SRIP offices, obviously with the 3. RESEARCH-LED SRIP AND expectations that the SRIP member will be prepared to finance TECHNOLOGY TRANSFER all these tasks. Common rule of 50% public co-financing of the The same set of questions as for industry- led SRIP, were SRIP office activities does not allow them to strengthen the directed to research-led SRIP. Regarding the question, related technology transfer activities. On the other side, there is no to technology transfer, we received an answer that coordinating specific need expressed by the members for SRIP offices to office of SRIP is not dealing with knowledge transfer activities. enter the field of technology transfer, which requires a very They don’t have sufficient human and financial resources for specific and high professional knowledge. Often, this this sort of services. However, PRO hosting the research-led knowledge and resources already exists at the PRO and SRIP has its own Technology transfer office (TTO), providing universities in the form of existing Technology transfer offices. the services connected with knowledge transfer for their Most business enterprises, with experience in joint R&D researchers. Yet, these services are available only for the PRO projects, have their in-house capabilities to address the issues of researchers and their customers. intellectual property rights. The question arises as to what is the situation in SMEs and whether in the case of their more active From the side of research-led SRIP members, technology involvement in joint projects they would benefit from the transfer is currently not recognized as a very important topic. assistance of the coordination office of SRIP. Here, we see the Currently main cooperation form between SRIP business opportunity for strengthening technology transfer service from members and research organization are joint R&D projects, the side of SRIP members, coming from the public research where intellectual property rights (foreground, background and community. They should invest more energy into informing side-ground) are agreed in advance and they are part of SRIP business partners regarding their own R&D work and cooperation agreement signed before the project starts. In these potentials, of course if they are motivated to more actively projects, in most cases, industrial property rights become transfer their knowledge and technologies. Also, the services in property of business partners. This is often the standard 339 the area of technology transfer, which were developed with [3] Bučar M, Jaklič A and Gonzalez Verdesoto, E, RIO public money within PROs, could be offered to SMEs as well. Country Report 2017: Slovenia, EUR 29163 EN, Publications Office of the European Union, Luxembourg, As we see, the issues identified in the previous studies (Bučar 2018, ISBN 978-92-79-81226-2, doi:10.2760/684842, and Rojec, 2019) on knowledge/ technology transfer have not JRC111274. been addressed by SRIPs either. These issues are actually long- term challenge for Slovenian innovation system, which cannot [4] GODC Government Office of development and Cohesion be solved by one, single, time-limited action. The issue requires Policy- Služba Vlade Republike Slovenije za razvoj in several systemic changes in different areas, from bridging the evropsko kohezijsko politiko. 2015a. Slovenian Strategy gap in understanding the objectives of R&D for PRO and those of Smart Specialisation. Slovenska Strategija Pametne of business entities. One of the solutions is a permanent long- Specializacije S4. https://www.gov.si/assets/vladne- term, sufficient and clear support of the government to the sluzbe/SVRK/S4-Slovenska-strategija-pametne- instruments like SRIP and TTO’s. specializacije/Slovenska-strategija-pametne- specializacije.pdf 5. REFERENCES [5] GODC Government Office of development and Cohesion [1] Bučar et al. 2019. Vmesno spremljanje in vrednotenje Policy- Služba Vlade Republike Slovenije za razvoj in delovanja SRIP- ov v obdobju 2017-2019. FDV, IER, UP evropsko kohezijsko politiko. 2015b. Strateška razvojna FM. https://www.fdv.uni- inovacijska partnerstva (Strategic development innovation lj.si/obremenitve/projektdokument.aspx?idp=251&id=167 partnerships). https://www.gov.si/assets/vladne- sluzbe/SVRK/S4-Slovenska-strategija-pametne- [2] Bučar, M. and Rojec, M. 2019. Determinants of Success specializacije/Podporni-dokumenti.pdf in Science – Industry Cooperation: Case of Slovenia; University-Industry Engagement Conference, Sydney. 340 The awareness on environmental protection issues as reflected through the inventions Levin Pal Center for Technology Transfer and Innovation Jožef Stefan Institute Jamova cesta 39 00 386 1 477 3303 levin.pal@ijs.si ABSTRACT from which further attempts are made to recover metals using The present study aimed to get the insight into specific "state of the art" methods in smelters and refineries. In environmental issues associated with key enabling technologies underdeveloped countries, equipment disassembly and and to identify the environmental protection related niche areas separation of materials is manual, and the recovery of metals is of the highest potential for growth to which the future made by heating, burning, and acid leaching of e-waste scrap in technology transfer activities should focus on. Analyses of small workshops causing additional damage to environment [2]. environmental related inventions in terms of absolute numbers Many batteries still contain heavy metals such as mercury, lead, and their shares within the technology fields of electronics, cadmium, and nickel, which can contaminate the environment materials, biotechnology and power sources were based on the and pose a potential threat to human health. Batteries represent annual data for the last decade. The shares of environmentally a complete waste of a potential and cheap raw material, when oriented inventions at the fields of electronics, materials, improperly disposed. In addition, battery recycling is not biotechnology and fusion power over the last decade remained feasible from economic point of view. However, as low as 1%, 5%, 9% and 2%, respectively, indicating low nanotechnologies could provide more economical battery market demand for environmental applications. On the contrary recycling in the future [3]. the shares of inventions related to green power sources increased from 54% to 60% over the last decade, most probably Nanotechnologies are also used in radioactive waste clean-up in due to intragovernmental actions on reduction of carbon water, direct seawater desalination and disinfection by using dioxide emissions that took place over the last decades. Similar nanochannels and nanopores, oil and water separation, actions should be implemented promptly in order to support the detection of pollutants, carbon dioxide fixation, artificial innovativeness and technology transfer related to management photosynthesis, photocatalytic degradation of organic pollutants of electronic and material waste in the following decades. in waste waters, superhydrophobic and intelligent construction materials etc. [3]. Keywords In biotechnology, biological treatment plants are well known Technology transfer, environmental protection, key enabling for removal of organic impurities in solid, liquid and gaseous technologies, electronic waste, recycling, recovery, metals, rare form and removal of heavy metals from waste materials. An earths, batteries, fossil fuel, fusion, nuclear, green power important application of environmental biotechnology are also generation. biosensors enabling biomonitoring, including monitoring of biodegradability, toxicity, mutagenicity, concentration of 1. INTRODUCTION hazardous substances, and monitoring of concentration and pathogenicity of microorganisms in wastes and in the Key Enabling Technologies (KETs) – a group of six environment [4]. technologies: micro and nanoelectronics, nanotechnology, industrial biotechnology, advanced materials, photonics, and Photonics have enormous potential of reducing the greenhouse advanced manufacturing technologies – increase industrial and non-greenhouse gas emissions by reducing the electricity innovation to address societal challenges and creating advanced consumption from traditional energy sources [5]. Photonics and sustainable economies [1]. In addition to having the highest have already significantly contributed to climate protection by potential for growth at the global markets the KETs have applications such as energy saving light bulbs and LED several applications related to the environmental protection, but lighting, photovoltaics and communication via fibre optic there are also certain environmental issues associated with networks. Other environment protection related applications of KETs at various fields. photonics are at the moment in the beginning of their growth trajectory and include early detection of forest fires, laser- Information technology is important for the growth of any supported metal recycling and optical communication in 5G country, but with the sudden development of new TV sets, mobile networks [5]. smartphones, computers and their relatively short lifespan, the accumulation of waste electronics is increasing. Waste electrical In best case scenario, the introduction of automation will have a and electronic equipment contains toxic substances that may positive impact on the environment: greenhouse and non- leach into the ground and emissions that may escape into the air greenhouse gas emissions will be reduced as well as the use of when disposed. Direct environmental impacts are the release of natural resources. However, automation will lead to increased acids, toxic substances and heavy metals and carcinogenic electricity consumption, so the impact of increased automation chemicals [2]. on the environment depends primarily on how society will cope with the replacement of "dirty" energy sources. In worst case In developed countries, formal sectors for e-waste management scenario, automation at the expense of increased electricity are being established, which take care of manual disassembly consumption would lead to increased greenhouse and toxic gas followed by semi-automated separation of various materials 341 emissions and increased consumption of natural resources, Various combinations of keywords referring to metals, rare increased consumption of rare materials for building electronic earths and batteries were selected rather than those referring to equipment and increased electronic waste [6]. advanced production and photonics. According to the literature the natural resources such as metals and rare earth elements and In addition to the growing need for recycling, recovery and magnets are often a limiting factor of advanced production, regeneration due to lack of natural resources there is also a electronics and photonics sectors. For the purpose of this study growing need associated with the electric power generation [7]. batteries were classified among the materials although in reality In particular, the source of electricity will determine the extent the field of batteries is rather interdisciplinary representing the of damage that power generation will cause to the environment. intersection between electronics, materials, chemistry, advanced Primary energy sources such as crude oils, coal and natural gas production, photonics and energy conservation. exhibit the highest amounts of greenhouse and toxic gases and should be reduced on behalf of the increased use of nuclear [8] Fusion as the potential new power source and traditional power and presumably fusion [9], hydro power and especially green sources such as nuclear and fossil fuel were compared to green power sources such as geothermal, wind, solar and bio energy power sources such as hydro, wind, solar, geothermal and [7]. bioenergy. Environmental protection related inventions will benefit the The analyses was performed using PatBase [10] in August society and benefiting the society should be the main and only 2020. The exact keywords and combinations with basic morally acceptable focus of public as well as private entities. Boolean operators and symbols are listed under the PatBase queries in Table 1. The PatBase search was set to search within In this study, we examined the emergence of patent documents titles, abstracts and claims (TAC) which are usually available in related to environmental protection at the fields of electronics, English language after publication by majority of national materials, biotechnology and power sources. We hypothesized: patent offices. Priority date (PRD) field was set to search within (i) that environmental applications should account for about a certain year. In Table 1 the PRD was set to year 2018 for all half of all innovations now days; (ii) that the share the queries and the results were further analysed by PatBase environmental applications had grown sharply over the past analyticsv2 providing the numbers of filed, granted and decade. published patent families, top five assignees and top five The aim of this study was to search for the guidelines for future jurisdictions. Ten separate searches for data on the number of technology transfer based on the occurrence of environmental patent families without further analysis with PatBase Analytics related inventions at the mentioned main fields of technologies v2 were performed for each of the priority years from 2008 to and identifying the environmental protection related niche areas 2018 and graphically presented on Figure 1 and Figure 2. The of the highest potential for growth to which the future calculations in Table 2 are based on the same dataset as Figures technology transfer activities should focus on. 1 and 2. Tables and Figures were prepared by Microsoft Excell software. Whenever average values were calculated the 2. METHODOLOGY corresponding standard deviations are presented next to the average values (e.g. average value ± standard deviation). The results of this study are based on comparison of the occurrence of patent documents between the general key There were 651.578 patent families for the query enabling technology (KET) areas and its sub-areas related to “TAC=(*material* and PRD=2018:2018)”. PatBase analyticsv2 environmental protection applications (e.g. area of “electronics” is capable of analysing up to 250.000 patent families at once. In compared to its subarea “electronic waste”) within the priority order to maintain the comparability of results and for the period from 2008 until 2018. Since the content of patent reasons described in the previous paragraphs of this section, applications is normally confidential for the first 18 months only the areas of metals, rare earths and batteries and their after the priority date, the priority period 2008-2018 is quite corresponding environmental protection related subareas were well reflecting the known prior art of the last decade (June/July included into the analysis. 2010 to June/July 2020). This paper was written in August 2020. 3. RESULTS Keywords denoting different areas and subareas within KETs The patent families (Table 1 and 2, Figures 1 and 2) having were selected based on the known literature considering the priority filing dates in 2018 were published in summer 2020 widest possible coverage of technology fields: The keyword and therefore represent the latest known prior art in the time (*electronic*) was selected to cover electronics, micro- and this paper was written. Approximately half of the patent nano-electronics; the keyword (*material*) was selected to families filed in 2018 were granted by at least one jurisdiction cover materials and advanced materials as well as micro- and and each of them was published by approximately five different nano- materials and consequently a certain range of jurisdictions. The term “invention(s)” will be used in the nanotechnologies; the keyword (*bio*) was used to cover following text referring to the filed, granted and published biotechnology. patent families at the fields of Electronics, Materials / Chemistry, Biotechnology and Power Sources. 342 Table 1: Number of filed, granted and published inventions (patent families) and top five assignees and jurisdictions based on the specific PatBase queries denoting wide areas (white background) and environment protection related sub-areas (shadowed background) within the technology fields.* Patent Patent Technology Areas and PatBase Patent Top five families families Top five assignees Fields Sub-Areas query families filed jurisdiction granted published Samsung Electronics Co. Ltd China P. Rep. GuangDong Oppo Mobile USPTO TAC=(*electronic*) Electronics 174.737 88.457 577.376 Lenovo Group Ltd WIPO and PRD=2018:2018 Qualcomm Inc Japan Apple Inc. EPO Electronics Ford global technologies China P. Rep. TAC=(*electronic* Alibaba Group holding Ltd. WIPO Electronic AND *waste*) and 2.332 1.170 12.229 Beijing Qihoo Tech Co. Ltd USPTO waste PRD=2018:2018 Netease Hangzhou Networl Co. Ltd EPO Univ. Shanghai 2ND Polytechnic Japan Taiwan Semiconductor MFG Co. Ltd China P. Rep. Samsung Electronics Co. Ltd USPTO TAC=(*metal*) and Metal 218.502 108.249 757.025 Intel Corp; WIPO PRD=2018:2018 LG Chemical Ltd. Japan BOE Technology Group Co. Ltd EPO Exxon Mobil Corp. China P. Rep. TAC=(*metal* AND Univ. Kunming Science and Tech WIPO Metal (recover* OR recycl*)) 9.587 4.285 54.242 Univ. Central South USPTO recycling and PRD=2018:2018 UOP LLC EPO BASF SE Japan LG Chemical China P. Rep. Ningde Contem… USPTO TAC=(batter*) and Battery 145.739 82.062 331.599 Sonoef Hefei Tech WIPO PRD=2018:2018 Hefei Guoxuan Japan Bosch Gmbh South Korea Materials Toshiba KK China P. Rep., TAC=(batter* and Bosch Gmbh USPTO Battery (recycl* or 2.484 1.087 9.221 Toyota Jidosha KK WIPO regenerat*)) and recycling PRD=2018:2018 Honda Motor Co. Ltd Japan Toyota Motor Corp. EPO TDK Corp. China P. Rep. TAC=(rare AND Nichia Corp USPTO earth* AND (magnet* Rare Earths 2.971 985 13.769 Hitachi Metals WIPO OR element*)) and PRD=2018:2018 China Petroleum Japan Univ Jiangxi Scientific EPO Sabic Global Technologies BV China P. Rep. TAC=(rare AND earth* AND (magnet* Exxon Mobil Corp. WIPO Rare Earths OR element*) AND 164 60 1.223 Univ Jiangxi SCI and Technology USPTO recovery recover*) and Inner Mongolia Jarud Banner Luan EPO PRD=2018:2018 Commissariat A Lenergie Atomique Canada IBM China P. Rep. Samsung Electronics Co. Ltd WIPO TAC=(bio*) and Biotechnology 99.862 37.244 497.744 Univ. California USPTO PRD=2018:2018 Univ. Jiangnan EPO Univ. South China Tech. Japan Biotechnology TAC=(biotreat* OR Univ. Jinan China P. Rep. Biodegrad* OR Univ. Tianjin WIPO Bio waste bioaugment* OR 7.208 2.566 42.793 Univ. California USPTO treatment biosens* OR Univ. South China Tech. EPO biomonitor*) and PRD=2018:2018 Univ. Zhejiang South Korea Tokyo Electron Ltd. China P. Rep. TAC=(power AND Applied Materials Inc. USPTO (crude* OR coal OR Fossil Fuel 27.824 15.535 110.970 Toyota Jidosha KK WIPO gas OR fossil)) and PRD=2018:2018 United Technologes Ltd. EPO Huaneng Clean Energy RES Inst. Japan China General Nuclear Power China P. Rep. TAC=(nuclear AND China General Nuclear Power ENG WIPO Nuclear power) and 3.214 1.739 11.245 Cnnc Nuclear Power MAN Co. Ltd. USPTO PRD=2018:2018 Jiangsu Nuclear Power Corp. South Korea Power China Nuclear Power Design Co. Ltd. Japan sources State Grid Corp. China China P. Rep. TAC=(fusion AND Hewlett Packard Development Co. WIPO Fusion power) and 1.512 708 17.226 Siemens AG USPTO PRD=2018:2018 Saint Gobain SA EPO Corning Inc. Japan State Grid Corp. China China P. Rep. TAC=(power AND (hydro* OR wind OR Beijing Hanergy Photovoltaic Invest WIPO Green solar OR geothermal 48.465 27.245 167.115 Beijing Boyang Dingrong PV Tech USPTO OR bio*)) and Beijing Goldwind Science and EPO PRD=2018:2018 Hanergy Mobile Energy Holding Japan * PatBase queries were based on the keywords to be searched in titles, abstracts and claims (TAC) across the patents and patent applications having priority date in 2018 (PRD=2018:2018). Analyses were performed using PatBase in August 2020. Priority patent applications are published after 18 months from the priority date. The represented data therefore reflects the present known state of the art. There is a correlation between number of filed, granted and Table 2 and Figures 1 and 2 are based on the filed patent family published patent families within the categories of Table 1. data. Average ratio of number of granted and filed patent families The queries referring to technology field of Materials have was 0,46 ± 0,08 and the average ratio of number of published jointly contributed the highest number of inventions filed in and filed patent families was 5 ± 2. The results in the following 2018 followed by the fields of Electronics, Biotechnology and 343 Power. The situation is different when comparing (a) Patent families - general environmental protection subareas within the general technology fields. The highest number of environmental related 250000 s inventions is the subarea Green followed by Metal recycling, 200000 Bio waste treatment, Battery recycling, Electronic Waste and amilief t Electronics Rare Earths recovery subareas representing the descending 150000 ent order of Power, Materials, Biotechnology and Electronics fields a Metal p 100000 in terms of the number of inventions (Table 1). A similar order of Battery in the number of inventions by field has been observed over the er 50000 Rare earths past decade (Figures 1 and 2) with the exception in the field of mbu Biotechnology Batteries and Biotechnology. In 2008 fewer Battery related N 0 2008 2010 2012 2014 2016 2018 priority patent applications were filed as compared to Year of priority Biotechnology, but from 2015 onwards the field of Batteries exceeded the field of Biotechnology by the number of inventions due to presumed exponential growth (R2 = 0,98) of b) Patent families - related to environment Battery related inventions (Figure 1). However, in general the protection number of inventions within all areas has been growing over the priority years 2008 – 2018 (Figures 1 and 2, Table 2). 10000 s Moreover, the number of inventions in general areas of 8000 technology as well as the number environmental related amilief Electronic waste t 6000 inventions were growing proportionally resulting in similar ent Metal recycling proportions of environmental related inventions within the a 4000 p Battery recycling general areas in 2008 and 2018 (Table 2). of 2000 er Rare earths recovery The proportion of environmental related inventions within the 0 mb Bio waste treatment u general fields of Electronics, Materials and Biotechnology was 2008 2010 2012 2014 2016 2018 N low, ranging from 1% up to 10%, throughout the whole priority Year of priority filing period 2008-2018. The said proportions have slightly increased over time except the proportions of Bio waste Figure 1: Number of inventions (patent families) with treatment related inventions, which dropped from 10% to 7% priority dates ranging from 2008 to 2018 referring to: (a) from 2008 to 2018, respectively. On the contrary, the general areas of Electronics, Materials - including metal, proportion of Green Power within the field of different Power rare earths and batteries - and Biotechnology; (b) sources was higher than 50% in 2008 and increased to 60% in environment protection related sub-areas of electronic 2018 (Table 2, Figure 2). waste, recycling or regeneration of materials - metal, rare Top five assignees are presented for each of the areas listed in earths and batteries - and bio waste treatment.* Table 1. Some of them are active in more than one area at the same time: Samsung Electronics in areas of Electronics, Metals Power sources: Patent families over years and Biotechnology; LG Chemical in areas of Metals and Rare 90000 Earths; Exxon Mobil Corp. and Univ. Jiangxi Scientific in area s 80000 ie of Rare Earths and Rare Earth recovery; Toyota Jidosha KK in il 70000 am area of Battery recycling and Fossil fuels; University of f 60000 t n California in Biotechnology and Bio waste treatment and State e 50000 Fusion at Grid Corp. China in areas of Fusion and Green Power Sources. p 40000 f Nuclear r o The top assignees listed under the general areas usually differ 30000 e Fossil fuel b from the ones listed under the environmental protection related 20000 mu Green N 10000 subareas (Table 1). 0 In general, based on the number of published inventions the top 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 five jurisdictions were China, America, Europe and Japan Priority appearing in descending order. South Korea is classified among top five jurisdictions in the areas of Batteries and Bio waste Figure 2: Number of inventions (patent families) with treatment and Nuclear Power sources displacing European, priority dates ranging from 2008 to 2018 referring to Japan and European jurisdictions from the top five jurisdictions different power sources: fusion; nuclear; fossil fuel at the said areas, respectively. Canada displaced Japan among including crude oil, coal and gas; and green including hydro, the top five jurisdictions at the field of Rare Earths recovery. wind, solar, geothermal and bioenergy sources. *Analyses were performed in August 2020 using PatBase [10] and PatBase queries listed in Table 1. 344 Table 2: Absolute numbers of general and environmental related inventions (patent families) filed in 2008, 2018 [Nr.] and the proportions [%] of environmental related inventions (patent families) filed in 2008 and 2018 and the 10-year average (Avrg) proportion with corresponding standard deviation (stdev).* Number and percentage of environmental related patent families in priority years Environmental related General 2008 2018 2008-2018 subareas areas [Nr.] [% ] [Nr.] [% ] Avrg Stdev Eletronic waste : Electronics = 928 : 81266 = 1,1% 2332 : 174737 = 1,3% 1,2% ± 0,1% Metal recycling : Metal = 5284 : 132352 = 4,0% 9587 : 218502 = 4,4% 4,1% ± 0,1% Battery recycling : Battery = 776 : 35109 = 2,2% 2484 : 145739 = 1,7% 1,8% ± 0,2% Rare Earths recovery : Rare Earths = 88 : 2123 = 4,1% 164 : 2971 = 5,5% 5,0% ± 1,0% Bio waste treatment : Biotechnology = 4850 : 49774 = 9,7% 7208 : 99862 = 7,2% 8,6% ± 0,9% Green Power : Power = 19023 : 35513 = 54% 48465 : 81015 = 60% 58% ± 2% *data on the number of patent families for individual filing years 2008-2018 are represented at the Figures 1 and 2. The PatBase queries referring to the keywords shown in Table 1 were combined with the priority dates (PRDs) ranging from 2008 to 2018 reflecting the known prior art from 2010 to 2020. Toshiba, Panasonic and Sharp funded an Electronic 4. DISCUSSION Manufacturers Recycling Management Company (MRM) in The results indicate that the shares of environmental 2007 and Toshiba as the top assignee in the field of batteries is applications account for less than 10% of all innovations in the also a partner of the Rechargeable Battery Recycling fields of electronics, materials and biotechnology now days and Corporation (RBRC) under the national U.S. Call2RecycleTM there was no sharp growth of the shares of environmental program dedicated to recycling of batteries [12]. applications observed over the past decade in these fields (Table 2 and Figure 1), which is not consistent with any of our Surprisingly, two large IT corporations Samsung and IBM introductory hypotheses. On the other hand, in the field of appeared in the general area of Biotechnology, most probably power sources the environmental applications account for more due to their activities in healthcare and life sciences, such as than half of all inventions, while their share grew from 54% to computational biology [13] and pharmaceuticals [14]. 60% over the past decade, which is consistent with the However, the Bio waste treatment subarea was dominated by hypotheses. universities. Universities of California and South China appeared among top five assignees in both, general A possible explanation for extremely low share (approximately Biotechnology area and Bio waste treatment subarea as well. In 1%) of inventions in the field of "electronic waste" within the addition to the absence of large corporations at the subarea of wider field of "electronics" could be due to inappropriate “Bio waste treatment”, the average proportion of “Bio waste methodological approach - choosing too secular keyword for treatment” related inventions has decreased from 10% to 7% the analysis (as explained latter this was not the case). over the last decade. Electronic waste is indeed a mix of different materials and its recycling is therefore closely linked to the recycling of various Technology transfer in the field of environmental solutions is materials including metals, rare earths and batteries [2]. often unsuccessful because, as evidenced by the low Interestingly, Samsung Electronics did not only appear among proportions of environmental inventions in this study, market the top five assignees in the field of its core business interest in environmental technologies is low. As a result, a (electronics), but also in the field of metals, which is not negative feedback loop arises: (i) Environmental solutions are surprising, since Samsung is investing in the development of not a priority to companies, since they present financial loss metals (e.g. semiconductors), which are an integral part of rather than profit to them. For example, the introduction of electronic devices they are producing [11]. recycling of products in parallel with the production would drastically affect the price of products and consequently the However, the proportions of inventions related to recycling, competitiveness; (ii) Public research organizations, which are recovery and regeneration of metals, rare earths and batteries supposed to be a driver of innovation and the well-being of were low as well, amounting approximately 4%, 5% and 2%, society are trying desperately with the commercialization, but respectively. And the top five assignees in the general areas of they sooner or later stop with patenting of environmental electronics, metals, rare earths and batteries were mostly solutions due to the low probability that these technologies will different to those associated to the subareas related to recycling, be licensed out to companies. Therefore, it would be illusory to regeneration and recovery of these products. expect that the corporations mentioned in this study - in other words the largest producers of waste and pollution - will begin With electrification of transport and growing demand for to change their attitude towards the environment on their own natural resources, the need for batteries and battery recycling is [15]. growing sharply, which explains the presumed exponential growth in terms of the number of inventions in this area. It is As mentioned in the introduction, photovoltaics and other not surprising that representatives of automotive industry and/or photonic applications will contribute to reduced electricity auto parts suppliers Toyota, Honda and Bosch are among the consumption and consequently lower greenhouse gas emission top five assignees in the subarea of battery recycling. It seems [5]. On the other hand, advanced production will increase the that national programs need to become involved to support the consumption of electricity and presumably increase the recycling of products, otherwise these activities would not be greenhouse gas emission [6]. Switch to green power sources is economically feasible for large corporations. For example, therefore extremely important [7]. However, it is necessary to 345 understand that the power generation from green sources is less Technology transfer within the innovation ecosystem is a part reliable due to low capacity potential and dependency of of the solution, but unfortunately it works well in case of clear momentary environmental parameters. Therefore, complete demand for breakthrough technologies at the market. In the transition to green sources is most probably not possible and field of alternative energy sources, intergovernmental the need for reliable power sources, such as fossil fuels and agreements have emerged over the decades, creating such a nuclear power will remain [8]. demand for technologies enabling the exploitation of alternative power sources. This can be observed by the high number and Fusion power will be able to replace environmentally harmful shares of inventions in the field of green power sources. energy production with fossil fuels in the future, if successful [9], but decades will pass by then. This is also evident from the However, the need in the market has yet to be created for number of inventions related to fossil and nuclear power technologies dealing with recycling of waste electronics and sources, wherein a number of inventions related to less waste materials. And it is illusory to expect that this demand environmentally friendly fossil fuel was approximately nine will arise on its own without adequate political support to put times higher as compared to cleaner nuclear and fusion power pressure on manufacturers globally. The task of the innovation sources. However, the major concept of the vast majority of ecosystem stakeholders is therefore to properly present these fossil fuel inventions was related to carbon dioxide according to problems to the interested public, through which the pressure to PatBase Analyticsv2 [10], indicating that research and the policy makers will be exerted. In fact, it would be great, if development in this area is mainly concerned with optimizing the solution in the field of electronic waste and waste materials fuel use towards lower carbon dioxide emissions, which is management would be even more efficient and implemented admirable. faster than in few decades. Even more favorable trends were observed in the field of green power at which the share of inventions was high and has grown 5. CONCLUSIONS from about 54% to 60% in the last decade. These data are Although the number of inventions has generally increased over encouraging in terms of reducing the global warming, the past decade, the share of environmentally oriented environmental pollution and health hazard originating from inventions has not changed at the fields of electronics, materials “dirty” power sources, which gives optimistic forecast for the and biotechnology, and has remained on average as low as 1%, future. 5% and 9%, respectively. A kind of “push” obviously exists at the energetics sector that Large corporations leading at the areas of electronics, materials forces states, governments and consequently all kinds of private and biotechnology are not as innovative and active at the and public entities including the players of innovation subareas related to the recycling of their own products, ecosystem to deal with environmental issues. This might be not therefore they should refocus and invest into the environmental only due to a lack of natural resources, but also due to clear protection. In order to do so, legal basis, programs and rules at international and intergovernmental level, which oblige incentives for non-profit recycling at national, international and countries to respect the environment globally. The 1997 Kyoto global levels are beneficial. Protocol, which has been in force since 2005 and replaced by On the contrary, the situation is more optimistic in the field of the Paris Agreement in 2015 [16] seems to play a key role electric power generation, wherein the share of inventions encouraging innovation towards the use of green energy sources related to green power sources grew from 54% to 60% in the by reducing the carbon dioxide emission [7]. last decade suggesting that technology transfer works well in Despite the fact that some countries do not respect the Kyoto case of clear demand at the market. In the field of alternative Protocol and later Paris Agreement, it still is a good practice as energy sources, intergovernmental agreements have emerged it has - by insisting on solving climate problems at the over the decades, creating such a demand for technologies international and intergovernmental level - created markets for related to exploitation of green power sources. green power sources around the world. Even China for The players of innovation ecosystem should therefore convince example, which has often been declared a non-Kyoto country, and support the interested public to exert the pressure to the is active producer of the equipment related to exploitation of policy makers in order to create a market demand for the green power sources – most probably due to the existence of technologies dealing with recycling of wastes, especially global market as well as due to its own awareness on the electronic and material waste through establishment of environmental issues in the last decades [17]. Environmental issues associated with the “dirty” power sources are decades old intergovernmental agreements on the global scale. and have been consequently addressed more in detail by the relevant authorities as compared to newer environmental threats 6. AKNOWLEDGEMENTS (e.g. electronic waste, batteries, rare earths, metals etc.). The inspiration for this paper was KET4CP – KET for clean production project to which Jožef Stefan Institute has The establishment of the UN E-Waste Coalition and the approached as the first and only Slovenian KET Technology introduction of the Platform for Accelerating the Circular Center at the time. I would like to thank the four independent Economy (PACE) [18] will hopefully lead to at least as reviewers that gave us further inspiration with their helpful and effective international protocols in the field of electronics and constructive comments. waste material recycling as were established in the field of power sources. Measures that would encourage companies to protect the environment should therefore apply to all companies 7. REFERENCES and all countries in order to maintain healthy competition [1] EUROPEAN COMMISSION. 2020. Key enabling between them. 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Why Nuclear Power Must Be Part of the tackle-challenge-e-waste Energy Solution. Yale Environment 360. 347 Transfer of knowledge and skills in STEM: Exploring and promoting digital analysis skills - Testing optimal conditions of X-ray irradiation Prenos znanja in veščin na področju STEM: Raziskovanje in promocija digitalnih veščin: Testiranje optimalnih pogojev rentgenskega obsevanja Svit Pestotnik Stres Gimnazija Bežigrad Peričeva 4, 1000 Ljubljana svit.pestotnik@gimb.org ABSTRACT information technology and science education to motivate young In this paper, we describe the transfer of knowledge and skills people to STEM content. In this context, digital skills are crucial between the High school and University system in establishing for establishing closer links between science and education. We of a digital environment for analytics in physics experiments. presented one of the options in our paper. ICT skills are essential in establishing the potential for automated In this paper, we describe an experiment done in collaboration or digital analysis in the observation of physics experiments. We between the International Baccalaureate at the Gimnazija have proven that this claim is valid in the case of X-ray detection Bežigrad and the Faculty of Physics and Mathematics of the on a imaging phantom. We photographed an irradiated imaging University of Ljubljana. The aim of this experiment was twofold: phantom under different initial conditions and tried to compare firstly, to explore how changing the voltage affects different results with each other in terms of different output parameters as image quality properties in X-ray Imaging phantom detection; optimal voltage used and signal to noise ratio. With the help of secondly, to explore how and to explore digital tools necessary independently created automated Python software for the RGB to execute the experiment as a regular study and collaboration analysis of the images and using analytical tools as Root and tool. The experiment and its data analysis allows for an Logger Pro programmes, we showed that collaboration between exploration of digital tools in STEM experiments and can the two educational systems is crucial for the transfer of represent a good basis for further collaboration between the knowledge and skills. institutions. Keywords The crucial element of this work was to establish a collaboration Digital technologies, digital skills, data analysis, STEM, X-ray that would enable the realization of the goal. The goal of this detection, imaging, observation research was to prove the correlation between the voltage applied to the X-ray apparatus and the image quality of the recorded POVZETEK picture. We were also exploring the impact of the distance V tem prispevku opisujemo prenos znanja in veščin med between the fluorescent screen and the phantom irradiated by the gimnazijo in univerzitetnim sistemom pri vzpostavitvi x-ray apparatus on the intensity of the light measured. digitalnega okolja za analitiko v fizikalnih eksperimentih. IKT The experiment conducted is based on the theory of X-rays. The spretnosti so bistvenega pomena pri ugotavljanju možnosti rays are produced by an apparatus, where a certain voltage is avtomatizirane ali digitalne analize pri opazovanju fizikalnih applied to a X-ray tube that accelerates the electrons towards the eksperimentov. Dokazali smo, da ta trditev velja v primeru molybdenum’s anode. The x-ray beams are the result of the rentgenskega zaznavanja na slikovnem fantomu. Fotografirali interaction of electrons with matter. They are shielded by a smo obsevan fantom za slikanje v različnih začetnih pogojih in poskušali med seboj primerjati rezultate glede na različne collimator so that can only exit the sources at a certain spatial angle. izhodne parametre kot sta optimalna uporabljena napetost in razmerje signal / šum. S pomočjo neodvisno ustvarjene The detection of X-rays was achieved by taking a picture of a avtomatizirane programske opreme Pyton za RGB analizo slik in fluorescent screen [1], which emitted fluorescent green light z uporabo analitičnih orodij kot sta programa Root in Logger Pro when hit by x-rays, with a camera. The acquisitions had to be smo pokazali ključno soodvisnost med obema sistemoma taken in complete darkness with a long exposure time to enable izobraževanja za namen prenosa znanja in spretnosti. enough light to accumulate on the sensor. Ključne besede After the data was converted to numerical form, a double error Digitalna technologija, digitalne veščine, analiza podatkov, function was fitted on the 2D response image. The parameters, STEM, rentgensko zaznavanje, slikanje, opazovanje which I received as an output, were then used in the analysis. 1. INTRODUCTION 2. METHODS In today's world, knowing digital approaches is increasingly The experiment was performed at the University of Ljubljana, crucial. On the other hand, the relationship between the various Faculty of Mathematics and Physics. I used the experimental branches of science - chemistry, physics, computer science - even equipment for the X-ray exercise of the subject Laboratory in the education system itself is still in its infancy. experiments V [2]. Interdisciplinarity and cross-curricular integration depend on individual initiatives. Particularly noteworthy is the link between 348 The detection of the x-ray particles was double-phased. The is significant, that the researchers involved take part in the apparatus used to produce x-rays was “Didaktiksysteme 554811” initiative SKOZ. [3]. The first part of the experiment was acquiring data in the The project itself will end at the end of 2020, during which time, form of captured photos, whereas the processes and techniques together with schools from the Western Cohesion Region, employed further on my research are analytical and systematical. research partners and business partners, established a solid and However, there is a second segment of activities embedded in functioning network of organizations that encourage the most this paper. It presents a proposal for technology transfer between talented students with projects. Jožef Stefan Institute took part in different parts/sectors of the educational system. In particular, the initiative, supporting more than 40 students so far. the paper proposes to enhance the capabilities of high schools by The purpose of SKOZ was to connect students with mentors and giving them access to digital tools that can only be found on the experts for the transfer of knowledge, in order to allow specific university level, but which could potentially be utilized by high subjects from a supportive environment to deal with the field of school students. work in specific research of the students. 2.1 Transfer of knowledge from one to the Gimnazija Bežigrad was not the recipients of the funds of the other educational environment tender announced in August 2017 by the Ministry of Education, It has soon become clear that without digital tools the observation Science and Sport. Even though it was not actively involved, it of the processes taking place in the imaging phantom and the still aimed at supporting and encouraging collaboration of the setup as a whole would be impossible on the level of accuracy experts with talented students. requested to draw reliable conclusions. In line with the idea of the project, in which the experts of the Thus the second aim of the study was to use existing and to Jožef Stefan Institute actively collaborated and understood its develop missing digital tools to enable RGB analysis of the purpose, also other more personal initiatives as this one were images taken. absorbed. These tools were developed with the assistance of the experts Thus on the point where digital skills transfer of knowledge was from the University of Ljubljana, Faculty of Mathematics and established as a break through element, which will enable this Physics and Jožef Stefan Institute. study to be carried out, although via personal contacts, the collaboration has been established between the IB Gimnazija The main purpose of the collaboration was to enable quick, Bežigrad student and the experts from Jožef Stefan Institute and accurate and reliable analysis. Faculty of Mathematics and Physics. On the other hand, the process at hand demanded that a The transfer of knowledge resulted in the setup of the processes knowledge transfer in terms of technologies used and skills that required for the data analysis, as described below. enable analysis, to be transferred from one educational environment to the other, to enable analysis of the data 2.2 Analysis of data themselves. 2.2.1 Python script- image color processing 2.1.1 Transfer of knowledge and skills in STEM The photos taken by the camera were then transferred to a During the measurements it soon became obvious that the scope computer, where further analysis was carried out. The captures of analysis is too broad and too extensive to allow for a usual were analyzed using a Python script that determines a specific approach of analysing single data sets with simple analytics tools RGB light composure of a certain pixel on a straight line, whose as Excel or Logger Pro analysis, which are usually used in the direction and extremes are provided by the user. The result of the high school environment. image color processing is a graph of light intensity in the correlation with coordinate of the pixel explored. The base code Thus in a constructive dialogue with my IB Physics teacher it was found on the internet [5] and was then changed so that it was decided to seek for further assistance with the experts at the suited my experiment’s needs. Faculty of Matematics and Physics and Jožef Stefan Institute. 2.2.2 Root script- intensity analysis and image They proposed to collaborate on creating suitable analytics tools splitting that would be useful for the concrete analysis, but would also be ROOT [6] was in this experiment used in two parts of analysis. further used in the IB process, if necessary. The digital skills in Firstly, the picture of the phantom had to be split up in several question included in particular: smaller pictures, which were only showing one hole in the - Python script-image color processing, phantom at a time. This step was required to enable easier - Root script-intensity analysis and management with the original data. Other processes in the - image splitting. analysis were then run on large amount of very similarly structured photos, which enabled the code to be less complicated. The relevant digital skills to be transferred from a University to a High School environment proved to be crucial for the execution of the research at hand. To understand how the process of knowledge transfer happens from a University to a High School environment, we need to start with more background information on how collaboration between high school and faculty commenced and where in the process the knowledge transfer occurred. 2.1.2 Process of transfer Figure 1. Irradiated phantom Figure 2. Image splitting Since 2017 in Slovenia there is a systematic approach, the project Secondly, the color analysis done in ROOT analysis framework SKOZ [4], trying to connect students from high schools to is similar to the one in Python. However, in this case the options mentors at the Public research organizations. Although this for the analysis are much wider. A light composition analysis particular connection has been established via personal means, it investigation can be done over the x-, y- axis and over the whole 349 picture. To achieve the highest accuracy of the outputting values That is why I decided to perform the research only on the the analysis over the whole picture was done. The program tried remaining 6 different sizes of gaps (0.8mm, 1mm, 1.4mm, to fit an error function [7] on the 2D response. Borders of such a 1.6mm and 2mm). signal is usually treated as a Gaussian function [8], so when a number of signals are treated together as one signal, convolution of the point response with the image shape makes the borders take form of an error function. The fitting of an error function was in my case used all around the given circular 2D signal (Fig.6). green Color gree gr n En E t n r t ie r s ie 6 4 6 0 4 0 0 Me M a e n a n x 0 - . 0 4 . 7 4 8 7 7 8 Me M a e n a n y 0 - . 0 5 . 7 5 5 7 3 5 St S d t d De v De x v 2 2 2 . 2 6 . 9 6 St S d t d De v De y v 2 2 2 . 2 7 . 1 7 2 c / /n d n f d f 4 . 4 7 . 4 7 1 4 1 / / 6 3 6 9 3 4 9 A A 0 . 0 4 . 0 4 4 0 3 4 3 ± 0 . 0 1 . 6 1 6 6 4 6 m_x _ x 0 . 0 0 . 0 0 4 0 3 4 5 3 7 5 7 ± 1 . 1 1 . 5 1 6 5 m_y _ y 0 - . 0 9 . 6 9 1 6 3 1 3 ± 1 . 1 1 . 5 1 4 5 W W 1 4 1 . 4 7 . 4 7 4 ± 3 . 3 9 . 8 9 3 8 0.7 s 2 . 2 7 . 5 7 4 5 4 ± 1 . 1 9 . 1 9 6 1 B B 0 . 0 3 . 5 3 6 5 8 6 8 ± 0 . 0 0 . 0 0 7 0 8 7 7 8 5 7 Figure 4. Example of analyzed material (left) 0.6 0.5 Figure 5. Python color intensity test (right) 0.4 The voltages used in this experiment are displayed in the table 0.3 below: 0.2 Table 1. Accelerating voltages used on the X-ray apparatus 0.1 0 Trial no. 1 2 3 4 5 6 y 30 Voltage [kV] 35 32 29 26 23 20 2010 0 30 x -10 20 10 -20 The aim of this experiment was to explore how changing the - 0 -30 - - 10 20 voltage affects different image quality properties. -40 - 30 40 3.1 Resolution dependence on the voltage Figure 3. 2D histogram of a captured photo  is a parameter of the error function that essentially tells us how The outputs that determined the double error function were: steep the border between the peak of the signal and background of the measurement is. It represents the width of a derivative -A, the height of the signal, function of the error function. The width of the derivative is a -W, the width of the signal, statistical value that tells us how well the border of the picture -B, the height of the background, was captured, the quality of the image can be described. -∂, the width on the half of the height of the graph od derivative of the error function 2.2.3 LoggerPro analysis The data acquired from the analysis by the code in Python and ROOT can be transferred to LoggerPro by importing the data as a text file with different columns. After the data is appropriately represented, we can identify the average height of the signal and the average width of the border by using cursor coordinates displayed by LoggerPro. The data gathered was then presented in the table to show the correlation. Graphs were drawn to Figure 6. Error function (left) explore different dependences. Figure 7. Average width of the derivative function of the 3. RESULTS error function (right) The images captured using the phantom with holes and the above The data that was processed with the mentioned codes resulted described setup (Fig.3), were analyzed using the described digital in the graph, where the sigma-value does not increase or decrease tools. with the variation of voltage. There was no found correlation Our goal was to determine the sharpness of the holes’ images. since the changes in the values with different voltages are The results acquired from the exploration were firstly in the form probably a result of a statistical error. The data gathered and of pictures (see example in Fig.7). After the analysis using the averaged is collected in the table and the graph below. developed Python programming tools the results had a numerical Table 2. 's average values for different gap diameters and form, since they represented an average width of the signal and voltages the average height. Both obtained values are an important test of the sharpness of the picture border and the quality of the photo. Diameter of the 2 1.6 1.4 1 0.8 0.5 hole [mm] / After the ROOT script was run on a set of little pictures, as Voltage [kV] presented above, the code tried to find the best fit for the 35 3.07 3.43 3.47 3.38 3.63 3.72 mentioned double error function. The parameters that root used 32 3.03 3.45 3.46 3.46 3.60 6.04 to find the best correlation, were then exported to a .txt file, 29 3.00 3.44 3.47 3.41 3.11 3.54 where they could be used for further analysis. 26 3.21 3.66 3.70 3.49 3.68 2.97 On the pictures captured with the lower input voltage the smallest 23 2.92 3.33 3.48 3.17 3.28 3.55 holes of the size of 0.5mm were really hard to see and the analysis 20 3.93 4.39 4.46 8.93 10.17 4.01 of light intensity on those was not returning consistent results. 350 pertinent that the transfer of knowledge is supported between the educational systems to allow for an optimal human resources development for the future industrial needs. 5. CONCLUSION Ultimately, the results could not have been obtained without using digital skills. STEM collaboration between high school and experts with highly developed digital skills is of utmost importance in order to firstly promote digital skills at a relatively early age of students, and secondly, to enable the students to learn them and use them in real-experimental setups, measurements and analysis. The conclusion is, that transfer of knowledge is very important in the STEM field and that young people can obtain many options Graph 1.  's correlation with voltage and opportunities with such transfer of knowledge, which would otherwise would not be achievable for them – and is not time financially or consuming for the university system at all. Only We can clearly see that the differences between the values are not through transfer of knowledge and skills between the two the consequence of the variation of voltage. educational systems optimal solutions can be found. 4. DISCUSSION 6. ACKNOWLEDGMENTS 4.1 Usefulness of the Transfer of knowledge My thanks to University of Ljubljana, Faculty of Mathematics As the baseline, I need to reconfirm the thesis that none of this and Physics for letting me use their x-ray apparatus, used for the work would be possible without the collaboration between subject Laboratory experiments 5, and for all advice on how to Gimnazija Bežigrad and Jožef Stefan Institute alongside with the approach the analysis of data and the knowledge transferred Faculty of Mathematics and Physics. The knowledge transferred about how to do so. in the field of digital skills and analysis were of the utmost 7. REFERENCES importance for the design and execution of the experiment. [1] Fluorescence. Wikipedia. [internet]. [cited on September The role of the project SKOZ was previously explained and can 05, 2020]. Available from: https://en.wikipedia.org/wiki/X- here be reconfirmed that it has created, at least for this particular ray_fluorescence. setup of people, technologies and skills needed, an awareness of a need for collaboration and transfer of knowledge between the [2] Fizikalni praktikum 3. Poskusi z žarki. [internet]. [cited on different educational systems. September 05, 2020]. Available from: http://predmeti.fmf.uni- The creation of digital skills in a different environment and a lj.si/fizprak3?action=AttachFile&do=get&target=Xzarki.p transfer of knowledge and promotion of digital analytics has been df. subject to personal experience and efforts, which I am thankful for. This, however, also sheds a ray of light onto the future [3] Instruction sheet 554 811. X-ray Apparatus. [internet]. possible transfer of knowledge and skills between the two [cited on September 05, 2020]. Available from: educational systems. https://www.ld-didactic.de/documents/en- US/GA/GA/5/554/554811e.pdf?__hstc=98968833.1bb630 4.2 Accuracy of the established digital tools f9cde2cb5f07430159d50a3c91.1530662400075.15306624 The ROOT and Python analysis scripts I ran on captured photos 00076.1530662400077.1&__hssc=98968833.1.153066240 often did not give very accurate output, because the starting 0078&__hsfp=1773666937. parameters were not set correctly. Even though I worked on [4] Project SKOZ [internet]. [cited on April 23, 2020] improving the code to the point, where the efficiency and Available from: https://www.gimvic.org/dejavnosti/skoz/ reliability was relatively high, there were still some cases where the code using the described models did not converge with the [5] Python Math: Convert RGB color to HSV color. [internet]. initial parameters provided. Especially the part of the [cited on March 30, 2020]. Available from: experiment, where the Root script was finding optimum double https://www.w3resource.com/python- error function to fit on the given data, was problematic, since a exercises/math/python-math-exercise-77.php. small difference in the way function was structured had major [6] ROOT analysis programme. [internet]. [cited on impact on the output parameters. September 05, 2020]. Available from: http://root.cern.ch. To conclude, the experiment could of course be performed more [7] Derivative of an error function. [internet]. [cited on efficiently, professionally, accurately, the errors could be September 05, 2020]. Available from: minimized. However, I believe that with given time, resources https://www.numberempire.com/graphingcalculator.php?f and my non-existing previous experience with such machinery, unctions=erf%28x%29%2C%282%2A%25e%5E- the experiment was performed optimally, and the results are quite x%5E2%29%2Fsqrt%28%25pi%29. relevant as they show how and to what degree digital skills are important in analysis of data obtained in physics experiments. [8] Error function. Wikipedia. [internet]. [cited on September 05, 2020]. Available from: Moreover, not only is the transfer of knowledge important https://en.wikipedia.org/wiki/Error_function. between the industry and public research organizations. It is 351 352 DODATEK / APPENDIX 353 INTRODUCTION AND AIM OF THE CONFERENCE Conference topic: How to maximize the impact of technology transfer funnel at TTOs? Subtopics: Assisting enterprises in order to better use the RTD results from public research organizations How to approach enterprises? The perspectives of TTOs, researchers and enterprises. The value proposition of early stage technologies for enterprises. Creation of an efficient national Proof-of-Concept (PoC) funding system. Helping spin-offs to succeed. Improving the knowledge base of technology transfer experts. Objectives of the Conference The main aim of the Conference is to promote knowledge exchange between academia and industry, in order to strengthen the cooperation and transfer of innovations from research labs into industrial exploitation. The Conference goal is also further strengthening the knowledge base and experiences of technology transfer professionals at public research organisations. In the past events, we hosted more than 2500 participants, including investors, inventors, researchers, students, technology commercialization and intellectual property experts, start-up funders, industrial development experts etc. We have successfully organized eleven competitions to award the team with their technology and business proposition with the biggest commercial potential, which led to successful start-ups and licensing contracts. Biannually we organise Research2Business (R2B) pre-scheduled meetings in order to give the participants additional opportunity to meet and discuss possible cooperation. Researchers presenting their work being financed by Slovenian Research Agency (ARRS) is another channel for enterprises to get familiar with recent discoveries and development opportunities. Conference prize for the best innovations in 2020 The main objective of the special prize for innovation is to encourage commercialization of inventive/innovative technologies developed at public research organizations and to promote cooperation between research organizations and industry. One of the main objectives is also promoting the entrepreneurship possibilities and good practices in the public research organizations. Researchers are preparing business models for their technologies and present them to an international panel of experts in a pitch competition. They need support in many aspects of their path from research to industrial application. The researchers and their team need assistance, knowledge and tools to develop business models, find appropriate partners, form a team, and secure financial resources to bridge the gap from publicly funded research to the market, either in their own start-up (spin-out) company or by licensing out their technology. How shall they do it and how can we help them? The Conference pitch competitions in the last eleven years resulted in spin-out company creation or licensing case development in at least one case per competition each year. In many cases, young researchers that participated in pitch competition in the past years, have been involved for the first time in an organized and structured process of development business model around their technology and preparation of the targeted (pitch) presentation about their planned venture to investors and technology commercialization experts. 354 WIPO IP Enterprise Trophy The aim of the WIPO IP Enterprise Trophy is to stimulate Slovenian enterprises to intensify their cooperation with public research organisations. We wish to expose as a good practice those enterprises that are constantly and methodologically using the IP system in their business activities. WIPO Medal for Inventors The goal of the WIPO Medal for Inventors is to award inventive and innovative activity of Slovenian public researchers and to recognize their contribution to national wealth and development. Research2Business meetings In the course of the conference, pre-scheduled Research2Business (R2B) meetings will take place, allowing the representatives of companies and research institutions to discuss possible development solutions, inventions and commercially interesting technologies. Such meetings present an excellent basis for possible future research cooperation and business synergies. Opportunities arising from publicly funded research projects / presentations of successful scientific projects Researchers will be presenting their work that is being financed by Slovenian Research Agency. Key stakeholders The conference involves different key stakeholders in the process, public research organizations as knowledge providers, technology parks as infrastructure providers, business accelerators, intellectual property offices, IP attorneys, agencies, consultants, capital (venture capital companies, agencies, business angels), SMEs, international enterprises, private innovators, and others. Target audience and benefits Target audience of the conference are researchers, students and post-graduate students with entrepreneurial ambitions, representatives of industry, established and future entrepreneurs, innovators and also representatives from governmental institutions and policy-making organizations. 355 Introduction to the International Technology Transfer Conference The International Technology Transfer Conference (ITTC) is organized by the Jožef Stefan Institute (Center for Technology Transfer and Innovation) for the 13th year in a row. The first ITTC was organized in 2008. The ITTC has, through the years, been presented in different formats and it is currently organized as part of the International multiconference Information Society (IS2020), organized by the Jožef Stefan Institute. The Center for Technology Transfer and Innovation at the Jožef Stefan Institute is the coordinator of the project KTT (2017-2022), coordinator of Enterprise Europe Network Slovenia, and is a financially independent unit. The CTT is presently involved in 4 projects, having recently been involved in three additional ones. The Conference has been organized with the support of partners from the KTT project (2017-2022). The previous project KTT, from 2013 through 2014, was the first project within which technology transfer in Slovenia was systematically funded from national funds. There were 6 partners involved, but the project only lasted for 17 months. The current KTT project, 2017-2022, comprises 8 partners, all public research organizations (PROs), represented by their respective technology transfer offices (TTOs), namely, 4 leading institutes and 4 renowned universities. The project's mission is twofold: the strengthening of links and increasing the cooperation of PROs and industry and the strengthening the competences of TTOs, researchers and enterprises. Most (80%+) of the finances go to human resource financing. Support of Slovenian Industry The goal of the KTT project is to support the industry in Slovenia, rather than an outflow of knowledge abroad or great profit for PROs. Collaboration between PROs and SMEs in Slovenia should be strengthened. However, Slovenian companies prefer contract and collaborative cooperation to buying licenses and patent rights. Also, a relatively low added value per employee and a low profit margin are not stimulating the research-industry collaboration. Investing into Intellectual Property Rights Despite the above stated it is important to invest in patents and other forms of intellectual property (IP). Investments in intellectual property increase licensing opportunities and the IP position of the Slovenian knowledge worldwide. Research2Business meetings One-to-one research-to-business pre-scheduled (virtual) meetings allow the representatives of companies and research institutions to discuss possible development solutions, inventions and commercially interesting technologies. Such meetings present an excellent basis for possible future research cooperation and business synergies. The meetings focus on applications, solutions and expertise in natural sciences like electronics, IT, robotics, new materials, environment, physics, chemistry and biochemistry. Companies and researchers book meetings also with technology transfer experts from the Center of technology transfer and innovation. The meetings are held virtually through b2match platform. The Research-to-business meetings at the Conference were co-organized in collaboration with the Enterprise Europe Network partners. 356 Strengthening the Competences of TTOs The goal of the KTT project is to establish technology transfer centers in Slovenia as integral parts of PROs, which shall, first and foremost, strive to serve the interests of the researcher and the PRO. The TTOs shall assist the researcher throughout the entire procedure of the industry- research cooperation, by raising competences and educating, taking care of legal and administrative issues, and promote research achievements among the industry. Lastly, TTOs shall support the cooperation already established by research groups. 357 ACKNOWLEDGEMENTS The editors and organizing committee of the Conference would like to express cordial thanks to all who helped make the 13th International Technology Transfer Conference a success. We would like to acknowledge the valuable contributions to the members of the SCIENTIFIC PROGRAMME COMMITTEE: Dr. Jeff Skinner, Executive Director of Institute of Innovation and Entrepreneurship, London Business School, Dr. Jon Wulff Petersen, director, Technology Transfer, Plougmann Vingtoft, Niko Schlamberger, President of Slovenian Society INFORMATIKA, Doc. Dr. Tamara Besednjak Valič, Faculty of Information Studies in Novo Mesto, for their contribution to the scientific programme and review of the scientific contributions and selection for publication in this Conference proceedings. Our special thanks go to the EVALUATION COMMISSION MEMBERS: Andreja Satran, Managing Director, ABC Accelerator, Dr. Jeff Skinner, Executive Director, Institute of Innovation and Entrepreneurship, London Business School, Dr. Jon Wulff Petersen, Director, Technology Transfer, Plougmann Vingtoft, Robert Al, Head of Business development, TU/e Innovation lab, Eindhoven University of Technology, and proxy member, Mark Cox, Knowledge Valorisation Officer, TU/e Innovation lab, Eindhoven University of Technology, for their evaluation of written technology commercialization proposals and selection of winning teams, authors of inventive technologies with the best potential for commercialization of the technologies, developed at Public Research Organizations. We are particularly grateful to the members of the EVALUATION COMMISSION: Jeff Skinner, London School of Business, Jon Wulff Petersen, TTO Ltd., Denmark, Alojz Barlič, Slovenian Intellectual Property Office (SIPO), for their evaluation and selection of the awardees of the WIPO IP ENTERPRISE TROPHY and WIPO MEDAL FOR INVENTORS. 358 Day 1 359 OVERVIEW OF THE PROGRAMME 8 October 2020 (virtual teleconference) 08.30 – 09.00 Registration Welcome address Dr. Simona Kustec, Minister, Ministry of Education, Science and Sport 09.00 – 09.15 Prof. Dr. Jadran Lenarčič, Director, Jožef Stefan Institute Dr. Špela Stres, MBA, LLM, Head of the Center for Technology Transfer and Innovation, Jožef Stefan Institute Keynote speech: Does the relation between the technology transfer and business education system influence the transfer efficiency? Dr. Jeff Skinner, Executive Director, Institute of Innovation and Entrepreneurship, 09.15 – 10.00 London Business School, UK Keynote speech: How to maximize the impact of technology transfer funnel at TTOs? Dr. Jon Wulff Petersen, Director, Technology Transfer, Plougmann Vingtoft, Denmark 10.00 – 12.00 Best innovation with commercial potential: Pitch competition 12.00 – 13.00 Lunch break 13.00 – 13.20 Award announcement: Best innovation with commercial potential Award announcement: WIPO IP Enterprise Trophy Paper presentations: scientific papers on technology transfer and intellectual property Round table on IPR management in industry: Mag. Mladen Vukmir, Vukmir and Associates, Zagreb, expert in IPR management, 13.20 – 15.20 patent attorney Mr. Gverino Ratoša, innovation in automotive industry, Hidria d. o. o. Mr. Drago Lemut, Director, company Le-Tehnika d. o. o. Prof. Dr. Alexsandre Marin, Director TTO, University POLITEHNICA of Bucharest; EEN member, EU IPR Helpdesk Ambassador 15:20 – 16.50 Opportunities arising from publicly funded research projects / presentations of successful scientific projects Award announcement: WIPO Medal for Inventors 16.50- Closing Parallel session: Besearch2Business meetings (B2R meetings) 9:00 – 13:00 360 WELCOME ADDRESSES From 9:00 to 09:15 Honorable Speakers: Dr. Simona Kustec, Minister Ministry of Education, Science and Sport Prof. Dr. Jadran Lenarčič, Director Jožef Stefan Institute Dr. Špela Stres, MBA, LMM, Head of the Center for Technology Transfer and Innovation, Jožef Stefan Institute 361 KEYNOTE SPEECHES From 09:15 to 10:00 Honorable Speakers: Dr. Jeff Skinner, Executive Director, Institute of Innovation and Entrepreneurship, London Business School, UK Does the relation between the technology transfer and business education system influence the transfer efficiency? Dr. Jon Wulff Petersen, Director, Technology Transfer, Plougmann Vingtoft, Denmark How to maximize the impact of technology transfer funnel at TTOs? 362 Does the relation between the technology transfer and business education system influence the transfer efficiency? Keynote speech by Dr Jeff Skinner, Executive Director, Institute of Innovation and Entrepreneurship, London Business School, UK The summary written by: Tomaž Justin, Miha Pitako, Robert Blatnik, Center for technology transfer and innovation, Jožef Stefan Institute Dr Jeff Skinner shared the business and research practice of how multiple relations between the technology transfer and business education system can influence the transfer efficiency. The question of “Can the relationship between the technical universities improve and benefit technology transfer from connecting with business schools and how?” arose as a focal point of where and how technology and business meet and evolve together seeing that technology transfer should be complemented with a great business strategy. People from science, technology, engineering and mathematics (STEM) usually have useful tech knowledge and ideas but those ideas lack support by people who could and would want to commercialize the idea. The efficiency of technology transfer can be improved if we help researchers to learn how to sell their knowledge and how to combine their talents with the entrepreneurs’ ones both exploiting existing business education systems and opportunities. Researchers have to go on a business and commercial journey from their laboratories to the world. They have to be empowered to effectively and efficiently search for the right application, with the right team and business model around the technology they invented. This is where business schools can complement the journey of the invention or innovation to the market as they can provide people with knowledge and skills of entrepreneurial methodology, offer existing business courses accessible to researchers, provide access to MBA students who love to work on cool stuff and have already established “entrepreneurial clubs” for networking and exchange of ideas. How can we combine these talents effectively? Researchers should mix and form teams with those who have business know-how and entrepreneurial spirit. In trying to combine these talents effectively we tried different approaches in order to form teams out of mixing people with different technical talents and people with business know-how. Researchers may join existing MBA courses to understand how business “think” and enable them to form teams with MBA students that may last beyond the course. As it turns out the sooner an idea can generate a critical mass of people supporting it the more likely it is to have market success. With bringing new venture ideas to the MBAs, they may be able to test different business models for technology commercialisation regardless, none of them is tailored to technology transfer exclusively. Business people should understand the business aspect of the technology transfer. By bringing people together into a single space to share ideas we are trying to establish a “cohort feel” to enable ideas support with people helping each other in different areas of expertise in order to enable freedom over scheduling and duration of the project as technology transfer projects may take months if not years to come to fruition. The other option is to inject technology transfer projects into MBA courses that may bring useful ideas on how to commercialize the innovations or inventions. Technology Transfer 363 Offices (TTOs) select promising projects that are elaborated almost as a consultancy project. We can argue if we do like that technology transfer opportunities are written up as teaching cases. We may want to venture out of the classroom with enabling co-curricular activities organized by the school’s staff. It is even better that students form semi-structured opportunities to mingle. At London Business School we are organizing hackathons, launchpads, team-forming workshops, competitions and challenges in order to achieve inter-sectoral mingling. By doing so we established several effective semi-structured educational opportunities for researchers to become better sellers. On one hand, after joining some forms of business education, some of the researchers may be even more curious about the efficient process of commercialization. On the other hand, Business Schools have assets that TTOs can use. For example, entrepreneurship courses to learn and team-build or MBA students who crave tech opportunities with some social capital in the business world that can enable the technology project to reach the market. But business education for researchers to become better sellers will always be a bit ad hoc and focused on the individual rather than project development. As it turns out the technology transfer projects are often about personal skills training. This is making it much more difficult to demonstrate the impact of the business education system on the transfer efficiency in short term. There is no steady state for technology transfer offices. This is why one should not overthink things but just do something, act on them. TTOs have to constantly think of new ways of engaging. To conclude: TTOs at STEM and business schools should enable and support mingling and networking within formal or informal mixing of different student’s ‘clubs. Be it medical clubs, media clubs, management clubs and others that can provide an environment in order to enable team formation of differently skilled people to gather around an idea as quickly as possible. The quicker an idea gathers a team the more likely it is to succeed. 364 How to maximize the impact of technology transfer funnel at TTOs? Keynote speech by Dr Jon Wulff Petersen, Director, Technology Transfer, Plougmann Vingtoft, Denmark The summary written by: Tomaž Justin, Miha Pitako, Robert Blatnik, Center for technology transfer and innovation, Jožef Stefan Institute Dr Jon Wulff Petersen, pointed out that technology transfer is a contact sport demanding a team effort with work that has to be organized systematically by clear concepts and rules whilst working with academia. This leads to the need of combining individual and team approaches. Technology transfer offices (TTOs) connect academic, scientific and research institutions with the industry and interact with various groups of people with different competences and roles, ranging from researchers, patent specialists, external project pilots, external mentors, seed investors and so on. The key is to form a team very early on, even around immature ideas. Since technology transfer is not an individual challenge, technology transfer requires a system thinking where organizational knowledge build-up is a key. Acknowledging the fact that we will always be short on resources, early funding such as proof of concept and seed capital has to be spent wisely. It is very important for technology transfer offices, apart from the skilled individuals, to have systems, processes and tools in the TTOs to overcome eventual lack of resources. This lack of resources is a challenge that requires clever systems and embedded processes such as the “Triangle method”, project and decision-making questionnaires, templates and other tools. The technology transfer system with a technology transfer office has to be robust enough to tackle good staff members leaving the successful TTO and joining the industry. On the other hand, when a TTO is on the rise one has to think of how to plug new people into TTOs as the TTO gets successful. The “Triangle method” is an important vehicle system that follows the case of technology evaluation for technology transfer all the way through the process. It is a way of organizing questions for which you want answers to when you have new technology. Some questions are more important than others and some are showstoppers. The TTO triangle method links six segments where specific value is added to them for the technology evaluation. The segments we observe in the TTO Triangle are: Application, Market, Competition, Human resources, Development time and cost and Intellectual property rights and regulatory. The TTO Triangle method is also an effective communication tool towards the team, to be used in explaining to the team, researchers and other colleagues or the outside world about the new technology. It can be used as well as a portfolio management system and as a tool for introducing new staff members into the system. An additional tool is the NABC - Needs, Approach, Benefits, Competition - which was developed at Stanford University and is broadly used in Scandinavia along grading and comparing inventions. The NABC is preferably using a simple system, like 10-point scale, which can also be used to provide new insights. It helps us understand what are we missing or what do we have to improve. The TTO Triangle method and NABC can be useful communication tools for creating team spirit and energy in the process. Communication assures progress, creates transparency, commitment and back up for the technology transfer system and the TTO. 365 A lot of work in technology transfer offices runs in circles – from analysing ideas to business development where we can be successful or the idea goes bad. Transparency in communication with participants within the process of technology transfer is imperative for when or if the invention is given back to the researchers at a certain stage of the evaluation or transfer process. The “giving-back” should be a positive learning process for the whole team, in particular for the researchers who should know the criteria and the decision-making foundation in advance. It is helpful for the TTO staff to be outgoing, to understand technology and have great social skills. The TTOs staff should be mindful not to get too far ahead of the research team they are trying to help. The feeling of ownership should remain with the R&D team. The R&D team should be encouraged and not frontrunner by the TTO stuff. To maximize the impact of technology transfer funnel at TTOs, stakeholders have to build a local technology transfer ecosystem that will work with local, near-by resources. Early stage technology transfer does not work well on long distances. Inventors have to connect with management professionals and do bottom-up market analysis rather than top-down one. 366 BEST INNOVATION WITH COMMERCIAL POTENTIAL: PITCH COMPETITION From 10:00 to 12:00 Moderator: Robert Blatnik, Senior Technology Manager | Spinnovator, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Evaluation commission: Andreja Satran, Managing Director, ABC Accelerator Dr. Jeff Skinner, Executive Director, Institute of Innovation and Entrepreneurship, London Business School Dr. Jon Wulff Petersen, Director, Technology Transfer, Plougmann Vingtoft Robert Al, Head of Business development, TU/e Innovation lab, Eindhoven University of Technology (proxy member: Mark Cox, Knowledge Valorisation Officer, TU/e Innovation lab, Eindhoven University of Technology) Presentation of six (6) selected business model proposals from public research labs to the technology transfer experts. 367 Course of the competition Robert Blatnik, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) The 12th annual competition for the best innovation in 2020 at public research organizations (PROs) aims at stimulating the researchers from public research organizations to develop business models for commercialization of their inventions. The competition was initiated with a public call, which was open to authors of inventive technologies with a proposed business model for commercialization. Eligible applicants for the call are individuals, employed at PROs, which are developing innovative scientific-research ideas into a viable business model. Possible business models are either licensing the technology to industrial partners or commercialization in a spinout company. The teams have prepared their application and pitch presentation following the guidelines, which were introduced by the Organizer of the Conference at the dedicated preparatory webinar which was organized for the teams. The webinar consisted of three one-hour parts. The researchers learned the guidelines on how to prepare their pitch presentation. In a series of three webinars we went through the process of preparing a pitch of their invention and business model to a potential investor or a partner in a future venture; either licensing the technology to an industrial partner or via commercializing of the technology in their own spin-out company. We have discussed which are the stronger points in the specific business model of participants and how to prepare an effective and appealing presentation for the intended audience of their pitch. The guidelines for preparing a pitch included the following elements: Cover / Introduction slide (name & compelling tagline); Deal (what you are selling, to whom, for what price); Market & segmentation (target customer, market size, trends); Customer value proposition and why now; Product (the solution); Financials; Impact; Competitive advantage; Team & founder’s/inventor’s dream; Summary / three key points to remember. The written description of the proposed invention/innovation included the following chapters: Title of the idea with a brief commercial tagline; Summary; The Science; The Opportunity (problem and solution); The Plan (Development stage and Business model); The Team; Impact. The teams and their applications with the proposed business models were evaluated by an international panel of experts which constituted the evaluation commission. The members of the evaluation commission are the following experts: Andreja Satran, Managing Director, ABC Accelerator, Dr. Jeff Skinner, Executive Director, Institute of Innovation and Entrepreneurship, London Business School, Dr. Jon Wulff Petersen, Director, Technology Transfer, Plougmann Vingtoft, and Robert Al, Head of Business development, TU/e Innovation lab, Eindhoven University of Technology and his proxy member: Mark Cox, Knowledge Valorisation Officer, TU/e Innovation lab, Eindhoven University of Technology. The experts evaluated the proposals in two phases. The 1st phase was the evaluation of written descriptions and the 2nd phase was the evaluation of the five-minute pitch at the Conference. The evaluation experts used the predetermined evaluation criteria which were already defined in the public call. The Criteria for evaluation are divided into six lots, which together account for total of 19 criteria. The criteria are presented in the table 1; each of the 19 criteria brings at the most 10 points. After the pitch the experts exchanged their views and opinions and selected the winner(s). The Criteria is presented in the Table 1. The traditional pitch competition, which this year had its 12th anniversary, stimulated six innovative and entrepreneurial research teams to prepare their pitch and apply for competition. Members of the teams have participated in three preparatory workshops to develop their pitch 368 and receive comments for improvements of their presentations. The workshop was organized by Center for Technology Transfer and Innovation as part of the KTT project, financed by Slovenian Ministry of education, science and sport. The teams are entirely or partly employed at the Slovenian PROs, Jožef Stefan Institute, National Institute of Chemistry, National Institute of Biology and University of Ljubljana. Criteria lots Criteria 1. Overall Degree to which project aligns with market need Project’s IPR situation 2. Product/application advantage Unique benefits Meets customer needs better Value for money 3. Market attractiveness Market size Market growth Favourable trends 4. Competitive situation Degree of entry barriers Level of competitiveness Manufacturing / processing synergies 5. Technology maturity Technical gap Complexity Technical uncertainty 6. Risk versus return Expected profitability (e.g. NPV) Return (e.g. IRR) Payback period Certainty of return / profit estimates Low cost & fast to do Table 1: Criteria for evaluating the applications (source: Jon Wulff Petersen, TTO A/S, Denmark) 369 Abstracts of the Competing Teams and their Technologies 370 Contact-based, leaching-free antimicrobial textile Authors/inventors: Marija Vukomanović, Srečo Škapin, Danilo Suvorov PRO: Jožef Stefan Institute, Ljubljana, Slovenia Abstract: Antimicrobial textile market is currently valued at around 10.48 billion USD with predicted growth rate close to 9.8% for the period from 2020 to 2026. The development of new fabrics is promoting the market growth. Further up-scaling of the production is particularly expected to support the healthcare industry’s requirement for masks and other medical textiles amid the spread of the COVID-19 pandemic. Besides being efficient against microbes, antimicrobial component inside textile has to meet important additional criteria regarding: (i) toxicity, (ii) allergenicity, (iii) irritation and (iii) sensitization. These are the most challenging criteria in selecting adequate antimicrobial component. Silver is frequently used antimicrobial present in many products (i.e. AlphaSan®, Silpure®, Silvadur™, SmartSilver®, Silvérion 2400). Integrated inside textile in form of ions or (nano)particles it is leached to provide antimicrobial activity. Lately there have been a lot of concerns about safety of this technology. Sweden’s national agency for chemical inspection has ruled silver as health risk (for human genetic material, reproduction, and embryonic development). Regulations in USA and Australia limit application of antimicrobial silver, particular in healing procedures. Still there is a high demand for discovery and implementation of the novel strategies able to replace existing, potentially toxic antimicrobial technologies. The last opens wide highways for innovation and progress in this area. Our team is designing innovative antimicrobial technologies for more than 10 years. We are holding EU patent on contact-based, non-leaching gold-based technology with proven efficacy in replacing antimicrobial silver (illustrated in Fig.1). Our next challenge is to formulate product prototype that will place our technology closer to the market. Figure 1: Current state of the invention: gold powder its efficacy and cytotoxicity in direct comparison to nano-silver. Doctoral dissertation, M. Vukomanovic, 2012. 371 DiTeR: Dynamic thermal line rating software Authors/inventors: Gregor Kosec, Jure Slak PRO: Jožef Stefan Institute, Ljubljana, Slovenia Abstract: One of the important aspects of transmission lines is overheating and thus the transmission capacity of the transmission network is often limited by the maximum allowed temperature of the conductor. Traditionally, the static capacity of the line is conservatively set for unfavourable weather conditions, i.e. hot sunny windless days. A more sophisticated approach is to dynamically determine the capacity considering the weather conditions or the weather forecast, which results in a considerable increase of the transmission capacity of the line. Based on experiences from theoretical studies and technology transfers, we developed a software package DiTeR that enables forecasting of thermal rating of power lines. The implemented software package has achieved high reliability and industrial level of use (TRL 9), thus representing a product that can be marketed on an international level. With DiTeR, any transmission system operator can much better utilize its power transmission network. Additionally, DiTeR increases the reliability of the transmission network and offers support for decision making in forecasts of extreme events. Currently, it is in operational use by the Slovenian transmission operator ELES that monitors 27 transmission lines with it. Figure 1: The image shows an overhead powerline that collapsed due to extreme icing. This event triggered the creation of software for thermal management which evolved into DiTeR. Eles d.o.o., February 2014. 372 Single step production of Bio-based methacrylic acid for plastic and coating industries Authors/inventors: Ashish Bohre, Miha Grilc, Blaž Likozar, Peter Venturini, Martin Ocepek and Miha Steinbücher. PRO: National Institute of Chemistry, Ljubljana, Slovenia Industrial partner: Helios Tblus d. o. o., Slovenia Abstract: Methacrylic acid (MAA) is an industrially important monomer, widely used to produce organic glass (poly-methyl methacrylate), acrylic fibres, plastics, and paints. Currently, the majority of MAA in the industries are produced through acetone-cyanohydrin process. This unsustainable method relies on expensive and extremely toxic feedstocks and corrosive concentrated acids. Besides the use of harmful substrates, low atom economy, poor product selectivity and the net emission of greenhouse gases are other drawbacks, associated with the industrial process, while the production is based exclusively on a non-renewable fossil-based resource. We have invented an efficient and sustainable catalytic route for the production of MAA. MAA is sourced from inexpensive and abundant lignocellulosic biomass derived feedstocks thus addressing one of the major issues associated with the utilization of depleting fossil fuel based feedstocks. Our technology provides industrially-relevant yield and selectivity, with more than 90 % of purity of MAA in a single step process. The archived MAA yield is higher compared to the previously reported method that utilized noble metal catalyst and alkaline base as a co- catalyst. Our catalytic process enables to replace the current multiple-step and energy-intensive industrial process of the MAA production in a single step from petroleum-based chemicals with the bio-based feedstock under relatively mild operating conditions. Figure 1: Single step production of Bio-based methacrylic acid for plastic and coating industries. Ashish Bohre, Miha Grilc, Blaž Likozar, Peter Venturini, Martin Ocepek and Miha Steinbücher, 2020. 373 A scalable method for eco-benign destruction of waterborne microorganisms Authors/inventors: Gregor Primc, Arijana Filipić, Rok Zaplotnik, David Dobnik, Ion Gutierrez Aguirre, Matevž Dular, Martin Petkovšek, Miran Mozetič PRO: Jožef Stefan Institute, Ljubljana, Slovenia; National Institute of Biology, Ljubljana, Slovenia; University of Ljubljana, Slovenia, Faculty of Mechanical Engineering, Ljubljana, Slovenia Abstract: Water scarcity is one of the biggest problems we are facing today so there is a global need for a stable supply of safe, pathogen-free water. Contaminated waters come from various sources including hospitals, farms and irrigation systems. These waters are guided through water- treatment systems; however, they usually do not inactivate viruses. Currently, chlorination, or similar chemical methods, are used for water disinfection, what represents potential environmental hazard. Chlorinated water released to the environment can cause adverse changes to many useful, but chlorine susceptible microbes. Treatment by ultraviolet radiation or ozone is only feasible for the disinfection of small quantities of contaminated water and efficient decontamination is limited by water turbidity. Our innovative technology presents an eco-friendly way for inactivation of waterborne microorganisms, particularly viruses, with low operation costs. The first phase is penetrating the market of small irrigation systems, such as hydroponics, second phase is a device for cleaning the heavily virus-contaminated water from clinics and the third phase, if successful with previous two phases, are large users, such as wastewater treatment plants and urban water systems with a large purification device. Globally, there are roughly one million potential small users and several thousand large users. Our technology exploits synergistic effects of two technologies (plasma and cavitation). The efficiency of its decontamination potential has been proved in laboratories, and the patent application to EPO has been submitted in October 2020. Figure 1: Abstract illustration on cleaning virus-contaminated water with synergistic effect of plasma and cavitation. Author: Gregor Primc (2020). 374 Enhanced cross-differential dynamic microscopy. A DLS- like particle characterization technique for cost-effective and accurate analysis of complex systems Authors/inventors: Andrej Petelin, Natan Osterman, Luka Cmok PROs: Jožef Stefan Institute, Ljubljana, Slovenia; University of Ljubljana, Slovenia Abstract: Enhanced cross-differential dynamic microscopy (C-DDM) is a cost-effective tool for the analysis of the soft matter dynamics in biosciences and biopharmaceuticals, paints, inks and coatings, nanomaterials, foods and drinks, pharmaceuticals and drug delivery, and academic research. The sensitivity of the method promises to be comparable to current commercial tools, like Dynamic Light Scattering (DLS), with added benefits of the multi-angle characterization for the analysis of complex systems, so it covers a broader range of use compared to DLS. The market size for DLS devices in European academic research is estimated to 15000 potential customers and 100 devices sold per year. C-DDM will be marketed as a complementary tool for studying the more complex system, or replacing more standard DLS applications. So, all current customers of DLS are potential buyers of C-DDM. Globally, in the long term, adding industrial customers into play, an estimated 1M revenue is viable, which is enough for a small- size sustainable business. We are a team of three, capable of completing the first phase of the development plan, that is, bringing the first device to the market in a year or two, and raising funds for further development. Team members have a good track record in applied research and have plans to improve the device in the future and to apply the technology for liquid crystal characterization and particle characterization tools for industrial research. For this, we will have to be successful in drafting the research projects and obtaining human resources (students). After finishing the research and development stage within three to five years, the team will assess the market and technology state and decide on future directives (licensing, spin-off). 375 A New Paradigm on Plastic Waste »PLASTICS - the Problem or the Solution« Authors/inventors: Andrej Trkov, Luka Snoj, Stane Merše, Blaž Likozar, Johannes T. van Elteren PRO: Jožef Stefan Institute, Ljubljana, Slovenia; National Institute of Chemistry, Ljubljana, Slovenia Abstract: Plastic waste is a big problem for the environment. Significant reduction of plastic use by replacement with more sustainable materials, circular economy and change of our behaviour is the key priority. However, plastics are hard to replace for some specific purposes, but eventually all plastic products become waste. The objective is planet-friendly production of essential Eco-plastics and final disposal of unrecyclable plastic by burial as a form of long-term carbon storage. Current practice of dealing with waste plastic is recycling (not all plastic is recyclable), disposal by incineration (CO2 emissions, hazardous combustion by-products), chemical reforming (e.g. synthetic fuels, etc.) and bio-degradation (possible micro-plastic residuals). A new paradigm is proposed, promoting the synthesis of Eco-plastics from CO2 from the air and hydrogen from water by electrolysis (or otherwise), polymerization into plastic resins for industrial use, collecting and compacting plastic products when they become waste, and disposing them as a way of long-term carbon storage, thus returning some of the carbon from fossil sources back into the ground. The key point is the availability of cheap electricity. Renewable sources of energy like the sun or the wind are strongly fluctuating. They result in surplus energy at peak hours and must have backup at production minima, which can be provided by the nuclear without a CO2 burden on the environment. Plastic production from electricity production peaks would make good use of this energy and help to stabilise the energy grids. Based on the experience of the team, our role in the scheme is to develop and optimize the system for the synthesis of plastic resins on a small scale. The know-how would be offered to external partners for application on industrial scale. Likewise, we would seek partners for the back-end of the process on super-compacting, canning and disposal of waste plastic. 376 Award announcement: Best innovation with commercial potential From 13:00 to 13:10 Moderator: Robert Blatnik, Senior Technology Manager | Spinnovator, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Evaluation commission: Andreja Satran, Managing Director, ABC Accelerator Dr. Jeff Skinner, Executive Director, Institute of Innovation and Entrepreneurship, London Business School Dr. Jon Wulff Petersen, Director, Technology Transfer, Plougmann Vingtoft Robert Al, Head of Business development, TU/e Innovation lab, Eindhoven University of Technology (proxy member: Mark Cox, Knowledge Valorisation Officer, TU/e Innovation lab, Eindhoven University of Technology) ANNOUNCEMENT OF THE WINNER The evaluation commission weighed all the criteria in the evaluation process and selected the winning teams. The second award of 500 Euro goes to the team members: Marija Vukomanovič, Srečo Škapin and Danilo Suvorov, coming from the Jožef Stefan Institute, for their technology: Contact-based, leaching-free antimicrobial textile »Silver-free, wearable germ protection«. The first award of 2000 Euro goes to the team members: Gregor Primc, Arijana Filipić, Rok Zaplotnik, Miran Mozetič, Ion Gutierrez-Aguirre, David Dobnik, Matevž Dular and Martin Petkovšek coming from Jožef Stefan Institute, National Institute of Biology and University of Ljubljana. In the opinion of the experts, the presented technologies of both teams bring value to society, have great potential to be brought to first customers and to be industrially scaled up. The qualified and passionate teams have key skills and knowledge for successful further development of the application which will bring value to the customers. Congratulations! 377 Award announcement: WIPO IP Enterprise Trophy From 13:10 to 13:20 Moderator: Marjeta Trobec, Spinout and Promotion Specialist, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Evaluation commission members: Jeff Skinner, London School of Business Jon Wulff Petersen, TTO Ltd., Denmark Alojz Barlič, Slovenian intellectual property office (SIPO) ANNOUNCEMENT OF THE WINNER WIPO IP Enterprise Trophy By celebrating the achievements of inventors, creators and innovative companies around the world, the World Intellectual Property Organisation Awards aim to help foster a culture in which innovation and creativity are encouraged and appreciated at every level of society. The WIPO IP Enterprise Trophy is awarding enterprises for their good practice to constantly and methodologically using the IP system in their business activities. Among the applications, the jury has decided to award Razvojni center eNeM Novi Materiali d. o. o. . Justification: Razvojni center eNeM Novi Materiali is actively cooperating with several public- research organisations. In the last ten years they have been developing new products based on public-research transfer. Those products also have suitable IP protection. The applicant has persuaded with the outstanding use of the IP system and activities to build public respect for IP via different public campaigns, mostly environment oriented and based on the newly developed products. And finally, they constantly and methodologically encourage the creativity and innovativeness among their staff. Congratulations! 378 Award announcement: WIPO Medal for Inventors From 15:20 to 15:30 Moderator: Marjeta Trobec, Spinout and Promotion Specialist, Jožef Stefan Institute, Center for Technology Transfer and Innovation (CTT) Evaluation commission members: Jeff Skinner, London School of Business Jon Wulff Petersen, TTO Ltd., Denmark Alojz Barlič, Slovenian intellectual property office (SIPO) ANNOUNCEMENT OF THE WINNER WIPO IP Enterprise Trophy The WIPO Medal for Inventors is awarding Slovenian public researchers for their contribution to national wealth and development. The "WIPO Medal for Inventors" goes to Prof. Dr. Alenka Vesel. In the last decade she has gained several international patents, she is a cofounder of company Plasmadis and her IP has resulted in different products and services being brought to the market. Congratulations! 379 Research2Business meetings (R2B meetings) Parallel session from 9:00 – 13:00 Robert Premk, Center for Technology Transfer and Innovation, Jožef Stefan Institute About Traditional biannual Research2Business (R2B) meetings promote and encourage cooperation among researchers and/or representatives from research institutions and companies on the international level. Main focus is transfer of developed or in development technologies and techniques from research institutions in business processes of the companies, while searching for opportunities to develop new solutions for challenges the companies are facing in the business-as-usual activities, or to look for partners for different topics and calls. Course of event Distinguishing feature of Research2Business meetings in the frame of 13th International Technology Transfer Conference was the completely virtual form of the meetings through the b2match platform. In the registration period between May and October 2020, 134 participants from universities, R&D institutions, companies, start-ups, associations submitted their interest to participate at the meetings. They were from 14 different countries: Austria, Bulgaria, Croatia, Ireland, Italy, Lithuania, North Macedonia, Morocco, Romania, Serbia, Slovenia, Spain, Turkey and United Kingdom. Two sessions of meetings were organized between 9 AM and 1 PM (CEST), where scheduled duration of each meetings was 20 minutes. In total 51 meetings were held, where registered participants could attend the meetings from their office with their computer, laptop or other devices with camera, microphone and connection to the internet. In both sessions more than 13 hours of conversations were held, with average length of each meeting at around 15 minutes. The meeting with the longest duration lasted for 23 minutes and 39 seconds. Although the format of this year edition of meetings was virtual instead of physical one, the participation exceeded expectations and attendance from previous years, while statistics and feedback already confirms that this type of meetings can provide excellent opportunity for individualized and thorough conversation between representatives of research and/or business community. 380 Day 2 381 CONFERENCE CEREMONY 382 Overview of the Conference Ceremony 9 October 2020 Jožef Stefan Institute, Ljubljana, Slovenia Location: Main Lecture room at the Jožef Stefan Institute (A-building) 11:30 – 11:35 Musical performance 11:35 – 11:40 Welcome speech Prof. Dr. Jadran Lenarčič Director of Jožef Stefan Institute 11:40 – 11:50 Opening speech Dr. Jure Gašparič, State Secretary of Ministry of Education, Science and Sport 11:50 – 11:55 Greetings Prof. Dr. Mojca Ciglarič Chair of the Programme Committee of IS2020 Dean of Faculty of Computer and Information Science 11:55 – 12:10 Awards of IS2020 Prof. Dr. Mojca Ciglarič, IS Programme Chair Prof. Dr. Matjaž Gams, IS Organization Chair Prof. Dr. Stane Pejovnik, Slovenia Academy of Engineering Prof. Dr. Nikolaj Zimic, AMC Slovenia President Prof. Dr. Sašo Džeroski, SLAIS President Dr. Mark Pleško , President of Slovenian Academy of Engineering Niko Schlamberger, President of Slovenian Society Informatika Robert Blatnik, M. Sc., Member of 13. ITTC Organizing Committee: - Award for the best innovation with commercial potential in 2020 - WIPO IP Enterprise Trophy - WIPO Medal for Inventors 12:10 – 12:15 Musical performance 383 13. ITTC Award Speech Robert Blatnik, Center for Technology Transfer and Innovation, Jožef Stefan Institute Marjeta Trobec, Center for Technology Transfer and Innovation, Jožef Stefan Institute The award for “The best Innovation with commercial potential from a public research organisation in 2020 with the award fund of 2.500 Euro goes to two teams: 500 Euro award goes to the team members: Marija Vukomanovič, Srečo Škapin and Danilo Suvorov, coming from the Jožef Stefan Institute, for their technology: Contact-based, leaching-free antimicrobial textile »Silver-free, wearable germ protection«. 2000 Euro award goes to the team members: Gregor Primc, Arijana Filipić, Rok Zaplotnik, Miran Mozetič, Ion Gutierrez-Aguirre, David Dobnik, Matevž Dular and Martin Petkovšek coming from Jožef Stefan Institute, National Institute of Biology and University of Ljubljana. The presented technologies of both teams bring value to society, have a great potential to be brought to first customers and to be industrially scaled up. The qualified and passionate teams have key skills and knowledge for successful further development of the application which will bring value to the customers. We congratulate the awarded team and invite the team representatives to accept the award. By celebrating the achievements of inventors, creators and innovative companies around the world, the WIPO Awards aim to help foster a culture in which innovation and creativity are encouraged and appreciated at every level of society. The evaluation committee for the WIPO Awards consisted of Dr. Jeff Skinner, Dr. Jon Wulff Petersen and Mr. Alojz Barlič from the Slovenian Intellectual Property Office. The WIPO Medal for Inventors is awarding Slovenian public researchers for their contribution to national wealth and development. The "WIPO Medal for Inventors" goes to Prof. Dr. Alenka Vesel. In the last decade she has gained several international patents, she is a cofounder of company Plasmadis and her IP has resulted in different products and services being brought to the market. The WIPO IP Enterprise Trophy is awarding enterprises for their good practice to constantly and methodologically using the IP system in their business activities. Among the applications, the jury has decided to award Razvojni center eNeM Novi Materiali d. o. o. . Razvojni center eNeM Novi Materiali is actively cooperating with more than 5 public-research organisations. In the last ten years they have developed several new products that have IP protection and are based on public-research transfer. They have persuaded also with the outstanding use of the IP system and activities to build public respect for IP. Congratulations to all of the awardees! 384 Zbornik 23. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2020 Zvezek F Proceedings of the 23rd International Multiconference INFORMATION SOCIETY – IS 2020 Volume F Ljudje in okolje People and Environment Uredili / Edited by Janez Malačič, Tomaž Ogrin, Matjaž Gams http://is.ijs.si 7. oktober 2020 / 7 October 2020 Ljubljana, Slovenia 385 386 PREDGOVOR Konferenca je sestavljena iz dveh: • demografske, predsednik prof. dr. Janez Malačič, letos trinajstič • okoljske, predsednik mag. Tomaž Ogrin, letos drugič. V letu pandemije se je zaostrila tako zdravstvena kot demografska scena. V 2020 bo umrlo nekaj nad milijon ljudi zaradi kovida, zbolelo jih bo nekajkrat več. V primerjavi s 130 milijoni rojenimi in 60 milijoni umrlimi se en milijon zdi zanemarljiv. Hkrati je razlika med rojenimi in umrlimi vsako leto manjša, a se bo zaradi časovnega zamika rast svetovnega prebivalstva nadaljevala še dolgo po izenačenju rojstev in smrti. Za Slovenijo sta med najbolj perečimi tematikami begunska problematika in skoraj pol stoletja premajhna rodnost Slovenije, ki preti z dolgoročnimi uničujočimi posledicami. Demografske odločitve bodo pomembno krojile kakovost življenja ljudi v prihodnjih desetletjih tako v Sloveniji kot Evropi. Če Japoncev s sedanjo rodnostjo po napovedih leta 3000 ne bo več, bodo Slovenci s sedanjo rodnostjo izumrli čez nekaj 100 let. Podobno travmatične so napovedi glede okolja. Medtem ko zavedanje o pomenu okolja narašča, mirno gradimo nova in nova veletrgovska središča na najboljši kmetijski zemlji, pa smo jo v letih od osamosvojitve izgubili 70.000 ha, tako da je ostalo še cca 180.000 ha obdelovalnih (njivskih) zemljišč, v občinskih prostorskih načrtih je predvidenih za pozidavo še 57.000 ha. Ni čudno, da imamo le 30 odstotno samozadostnost. Od leta 2000 smo izgubili 10 odstotkov zemljiških površin. Slovenija je majhna država z malim vplivom na svet, a narava je naša prednost v Evropi in mora biti prioriteta. Ima tudi gospodarski turistični pomen z delovnimi mesti za veliko prebivalcev in generacij. Ena od prioritet so prosto tekoče reke in potoki, za nas in za zanamce. Modrost je v izreku: ''Ne uničujmo narave, da bi reševali okolje. '' Poznan v tujini kot ''Do Not Destroy the Nature to Save the Environment.'' Želimo podati usmeritev Slovenije v varno, prijazno, zdravo in kakovostno okolje za vse državljane in državljanke Slovenije. Opozarjamo na prehitro uničevanje okolja, kmetijskih površin, nepotrebno gradnjo novih in novih trgovskih centrov, avtocest in energijskih objektov na najboljših zemljiških površinah. Je mogoče hkrati spodbujati tehnološki razvoj, uporabo obnovljivih virov in preprečevati negativne vplive na okolje? Smo sposobni preusmeriti antropocentrični razvoj v ekocentričnega? Potrebujemo strožji nadzor varstva na ožjih, širših in vplivnih vodnih območjih za zaščito podtalnice in pitne vode, vključno z ekonomskimi in lastniškimi načeli? Imajo mesta dovolj zelenih površin v mestih, imajo podjetja in inštitucije vse pozidano, v asfaltu in betonu? Kdaj bomo sanirali degradirana območja, na primer Celjsko kotlino? V letu 2020 smo pripravili Belo knjigo strokovnega varovanja okolja http://library.ijs.si/Stacks/Literature/Bela%20knjiga%20znanost%20o%20okolju%202020.pdf in s tem postavili pomemben mejnik pri izboljševanju slovenskega okolja. Janez Malačič in Tomaž Ogrin 387 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Janez Malačič, predsednik Matjaž Gams, organizator Drago Čepar Christian Gostečnik Majda Černič Istenič Boštjan Kerbler Karin Kasesnik Dušan Kidrič Marko Krevs Tomaž Merše, Mari Osredkar Janja Pečar Janja Povhe Jože Ramovš Jože Sambt Milivoja Šircelj Petronela Vertot Božidar Voljč 388 The Shrinking of Human Population and Causes for it – is Women Education and Empowerment among them? Zmanjševanje človeške populacije in razlogi – ali sta žensko izobraževanje in emancipacija med njimi? Matjaz Gams† Department of intelligent systems Jozef Stefan Institute Ljubljana, Slovenia Matjaz.gams@ijs.si ABSTRACT / POVZETEK current estimate of the world population. The current projection estimates that the world population will reach 10 billion persons The bulk of the paper examines the 2020 Lancet paper about in the year 2057. Table 1 presents basic demographic data. fertility and human demographic projections [1] in particular in relation to the causes of the fertility decline. Also, throughout the Table 1: World population - basic demographic data paper, comparisons to the previous publication of the author of (https://www.worldometers.info/world-population) the paper are presented, again with the relation to the women empowerment, education and implementation. The conclusion is that the best world-wide scientific literature is aligned with the Year conclusions obtained by the AI methods and presented at the (July Yearly Median Fertility Urban demographic conferences in Slovenia. Therefore, the 2018 1) Population Change Age Rate Pop % national protests regarding exactly the same issues do not hold any scientific merit in light of the recent publications. 2020 7,794,798,739 1.05 % 30.9 2.47 56.2 % KEYWORDS / KLJUČNE BESEDE 2019 7,713,468,100 1.08 % 29.8 2.51 55.7 % Demographic trends, birthrate, fertility, emancipation, women 2018 7,631,091,040 1.10 % 29.8 2.51 55.3 % empowerment / demografski trendi, stopnja rodnosti, rodnost, emancipacija, ženske opolnomočenje 2017 7,547,858,925 1.12 % 29.8 2.51 54.9 % 2016 7,464,022,049 1.14 % 29.8 2.51 54.4 % 1 INTRODUCTION 2015 7,379,797,139 1.19 % 30 2.52 54.0 % Demographic projects are primarily based on birthrate, i.e. fertility rate and are commonly measured in terms of children 2010 6,956,823,603 1.24 % 28 2.58 51.7 % born by a woman in her lifespan on average (in this paper 2005 6,541,907,027 1.26 % 27 2.65 49.2 % “fertility rate” or “birth rate” denotes the Total Fertility Rate – TFR). There are several other parameters that influence the 2000 6,143,493,823 1.35 % 26 2.78 46.7 % number of citizens in a particular country, such as emigration, wars and natural disasters, average life span and similar. The 1995 5,744,212,979 1.52 % 25 3.01 44.8 % projections are in recent years performed by several individual research teams and several official services such as UN, Eurostat 1990 5,327,231,061 1.81 % 24 3.44 43.0 % https://ec.europa.eu/eurostat/web/population-demography- 1985 4,870,921,740 1.79 % 23 3.59 41.2 % migration-projections/data or American institutions such as CIA. Through Web it is also possible to observe basic data and 1980 4,458,003,514 1.79 % 23 3.86 39.3 % projections, e.g. a world population counter https://www.worldometers.info/world-population/ showing 1975 4,079,480,606 1.97 % 22 4.47 37.7 % 1970 3,700,437,046 2.07 % 22 4.93 36.6 % Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed 1965 3,339,583,597 1.93 % 22 5.02 N.A. for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must 1960 3,034,949,748 1.82 % 23 4.90 33.7 % be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 1955 2,773,019,936 1.80 % 23 4.97 N.A. 389 Several studies are concerned with the question what will healthy lifestyles are strongly recommendations for Europe. accompany the slowing of demographic fertility rate and where Higher education levels are accompanied by decreases in fertility will it end, and also what influences the decrease of the fertility and mortality. Prof. Emma Galli, Scientific Director, rate [2,3,4,5,6]. Slovenian studies culminated in the White book Fondazione Luigi Einaudi, Italy, Andrea Virág, researcher of the of Slovenian demography [7]. Republikon Institute, Hungary and Prof. Anna The demographic changes are strongly affecting social and Rotkirch, Director of the Population Research Institute at the economic development [6] and will potentially cause lots of Family Federation of Finland provided development in southern problems unless resolved. Even in Slovenia, the presentation of Europe, eastern Europe (V4 countries) and Scandinavia/Finland. the studies at the National Council, e.g. [8], published later in the Amongst these, Finland stands out with its total fertility rate for White book [7], caused lots of discussion in public, Web and 2019 at alarming 1.33 children per woman. Prof. Rotkirch gave among political parties. The focus of the criticism was that it is three possible explanations for this: 1) Lower fertility ideals & not the case that the Slovenians or native Europeans will more uncertain intentions: there seems to be a greater focus on diminish with current birthrates, as claimed by the White book, work as the meaning of life (author remark: neoliberal globalism and that relating the level of emancipation and education to lower aims at producing work and capital oriented individual fertility is both not supported by scientific data, since for example consumers instead of society and family members). The number empowerment relates to the improved standard and vice versa, of women aged 20–39 not wishing children at all has was 1 % in and therefore this relation is not of essence, but collateral as is 1977 and 11 % in 2018 in Finland. 2) High previous proportions for example the number of cars to the standard. To explain it with of childlessness might make not having children more ‘normal’ an example: if a country imports a large number of cars, it will (highlighted by the author). Ms. Virág presented the Hungarian not be any richer. The final argument was that the proclaimed orientation towards more children: families receive support for relation between education and empowerment on one side and buying a new home (levels depending on the amount of children), the fertility rate on the other side was not only unscientific, it was a mortgage reduction if the number of children are two or more, also based on ideology – the authors were alleged trying to support for buying a car if the number of children are three or reverse the women powers back to a patriarchal family, even more, and mothers with four children or more do not have to pay though fiercely denied by the authors [9]. Due to the ideological income tax. The roundtable also pointed out the strong relation polarization of the research question, even some research between politics and demography. communities either joined the protests or accepted an indifferent Even though this is just one event, the conclusions from it are stance [10]. so general and supported even by the basic data in Table 1, that However, that is not the way science works, be it there is little doubt that if the current fertility rate in Europe vaccination/anti-vaccination or claims that the world is flat – it is continues, the native European peoples will sooner or later perish on scientists to provide either evidence on their own or provide unless new solutions are found. quality citations. In this paper we will reexamine the basic causes for lower fertility consequences primarily to the recent Lancet paper [1], and the causes for the polarization of the utterly a 3 THE LANCET DEMOGRAPHIC PAPER scientific question. In the Lancet, one of the three major scientific journals (Science, Nature) with more medical orientation, published a paper on the issue of fertility, causes for lowering worldwide birthrates, and 2 RECENT SCIENTIFIC CONFERENCES consequences [1]. The study was performed at the University of AND PAPERS Washington, Seattle, USA, and was funded by the Melinda and In the Ralf Dahrendorf Roundtable on “Population Decline Bill Gates foundation. While majority of studies currently project and its Effects in Europe” [11], organized by EU, on 19 continuing global population growth, the Lancet models November 2019 in Helsinki (Magma 2019), one of the central highlight the huge challenges to economic growth of a shrinking comments by Nils Erik Forsgård, Director of Magma, was: “At workforce, the high burden of an ageing population, and the current fertility rates, we Europeans are basically breeding impact on global power. The uniqueness compared to the ourselves out of existence.” Europe as a whole is facing a severe previous projections is that the Lancet study considers dynamic demographic challenge. With fertility 1.59, as was the rate in the and simultaneous interchange of the parameters and predictions. EU in 2017, and the rapidly growing amount of people older than The data obtained from the Global Burden of Disease Study 80 years will provide a surge for emigration. 2017, given to the prediction algorithms developed by the Dr Daniela Vono de Vilhena from the Max Planck Institute researchers from the Institute for Health Metrics and Evaluation for Demographic Research, observed that Africa and Asia (IHME) at the University of Washington's School of Medicine, remain the continents of the children of the future. Few changes projects that in 2100, 183 of 195 countries will have fertility rates in fertility levels are expected to occur for the rest of the world: below replacement level of 2.1 births per woman. World in Europe, demographers are not expecting fertility trends to population is forecasted to peak in 2064 at around 9.7 billion drastically change in the upcoming decades. Pragmatic migration people and fall to 8.8 billion by century's end. policies, therefore, are and will be essential to maintain a healthy Here is a quote from the Interpretation of the paper (bolded population structure in Europe. According to the Centre of by the author): Expertise on Population and Migration, half of the population of “Our findings suggest that continued trends in female EU-28 was at least 43 years old (median age) in 2015. By 2060, educational attainment and access to contraception will hasten however, 50 % of the population is expected to be at an age above declines in fertility and slow population growth. A sustained TFR 50 years old. Encouraging longer working life and promoting lower than the replacement level in many countries, including 390 China and India, would have economic, social, environmental, not just economically bypass the USA and continue extending and geopolitical consequences. Policy options to adapt to the lead, but rather will in the forthcoming decades hamper the continued low fertility, while sustaining and enhancing female new superpowers and again lead to shifts in global powers. reproductive health, will be crucial in the years to come.” Among the core reasons for the birthrate decrease and Demographic projections, models and studies of relations subsequent shifts in demographic and economic powers are indicate that the world population will likely shrink after mid- widespread access to modern contraception and the education of century, forecasting major shifts in global population and women. The new study also predicts huge shifts in the global age economic power. All countries worldwide will continue structure, with an estimated 2.37 billion individuals over 65 years decreasing their fertility rate with a delayed shrinking of their globally in 2100, compared with 1.7 billion under 20 years, populations. For example, the USA is projected to have underscoring the need for either increased immigration of population growth until mid-century (364 million in 2062), advanced IT solutions to help elderly. followed by a moderate decline of less than 10% to 336 million In terms of economic relevance, the demographic by 2100. The USA's total fertility rate is predicted to steadily changes will result in major power shifts. For example, although decline from 1.8 in 2017 to 1.5 in 2100 (close to the current numbers of working-age adults in India are projected to fall from Slovenian birth rate). However, the projections are reasonable 762 million in 2017 to around 578 million in 2100, it is expected favorable for the USA (at least compared to Europe and to maintain its working-age population over the century. Without Slovenia) - in 2100, the USA is forecasted to have the fourth COVID-19 interference it is expected to surpass China's largest working-age population in the world (around 181 million), workforce population in the mid-2020s, while the number of after India, Nigeria, and China. In terms of economic projections, Chinese workers will decline from 950 million in 2017 to 357 the projections are eve better – while the USA with the largest million in 2100 unless China again reintroduces demographic economy currently will be replaced by China in 2035, the USA obligatory ruling as the prescript of the number of children. Thus, is forecasted to once again become the largest economy around India will substantially progress in terms of GDP. 2100. A sufficient number of workers will have a major impact on The new projections anticipate major fertility decline in the economic progress also in Sub-Saharan Africa which will current high-fertility countries, e.g., in sub-Saharan Africa where become significantly more powerful. Due to the high fertility rate, rates are expected to fall from an average 4.6 births per woman Nigeria will see its working-age population grow from 86 million in 2017 to just 1.7 by 2100. Currently in Niger, where the fertility in 2017 to 458 million in 2100, and will rise its GDP rankings rate is the highest in the world with 6-7 children per woman, the from 23rd place in 2017 to 9th place in 2100. rate is projected to decline to around 1.8 by 2100. But due to the Big European countries with reasonable fertility like the UK, delayed effect of fertility change on the overall population, the Germany, and France are expected to remain in the top 10 for population of sub-Saharan Africa is forecast to triple in this largest GDP worldwide at the turn of the century, but those with century, from an estimated 1.03 billion in 2017 to 3.07 billion in particularly low fertility will decrease a lot – e.g., Italy will drop 2100. According to the projections, North Africa and the Middle from rank 9th in 2017 to 25th in 2100 while Spain from 13th to East are the only other regions predicted to have a larger 28th. population in 2100 (978 million) than in 2017 (600 million). The population decline could be softened by an increased Asia, Central and Eastern Europe will also face further fast immigration. Countries like the USA, Australia, and Canada, will population shrinking. 23 countries will sustain more than 50% probably maintain their working-age populations in this way. decrease, including Japan (from around 128 million people in 2017 to 60 million in 2100), Thailand (71 to 35 million), Spain (46 to 23 million), Italy (61 to 31 million), Portugal (11 to 5 4 DISCUSSIONS BASED AND RELATED TO million), and South Korea (53 to 27 million). 34 countries are THE LANCET DEMOGRAPHIC PAPER expected to have population declines of 25 to 50%, including The Lancet projections are highlighting the importance of China (1.4 billion in 2017 to 732 million in 2100). demographic movements on the quality of life and the progress Birthrates will fall to around 1.2 in Italy and Spain, and to of countries. In the words of IHME Director Dr Christopher 1.17 in Poland. The number of children under 5 years old is Murray, who led the research: "This study provides governments forecasted to decline by 41% from 681 million in 2017 to 401 of all countries an opportunity to start rethinking their policies on million in 2100, whereas the number of more than 80 years old migration, workforces and economic development to address the is projected to increase six fold, from 141 million to 866 million. challenges presented by demographic change." and In other viewpoint, the global ratio of adults over 80 years to each "For high-income countries with below-replacement fertility person aged 15 years or younger is projected to rise from 0.16 in rates, the best solutions for sustaining current population levels, 2017 to 1.50 in 2100 in countries with a population decline of economic growth, and geopolitical security are open immigration more than 25%. policies and social policies supportive of families having their This is the source for the changes in predictions - even slight desired number of children. However, a very real danger exists changes in TFR translate into large differences in population size that, in the face of declining population, some countries might during decades. For example, increasing TFR by as little as 0.1 consider policies that restrict access to reproductive health births per woman is equivalent to around 500 million more services, with potentially devastating consequences. It is individuals on the planet in 2100. imperative that women's freedom and rights are at the top of Surprisingly, the working age-populations decline will hit every government's development agenda." countries not considered before, e.g. India and China, which will 391 IHME Professor Stein Emil Vollset, the first author of the decline. The author of this paper is studying the longevity of the paper, similarly claims that "The societal, economic, and human technological civilization and the most likely outcomes geopolitical power implications of our predictions are substantial. are between 1000 and 10.000 years [12]. Unless we change our In particular, our findings suggest that the decline in the numbers behavior and values, i.e. unless we do not conquer the space and of working-age adults alone will reduce GDP growth rates that become aware of the silent major dangers like the globalization, could result in major shifts in global economic power by the which the Melinda and Gates Foundation scientists are totally century's end. Responding to population decline is likely to unaware of, we are in indeed a grave danger. become an overriding policy concern in many nations." Nevertheless, the theses proposed in [8] and White book [7] And adds: "While population decline is potentially good news are consistent with the Lancet paper, being the most relevant and for reducing carbon emissions and stress on food systems, with novel recent demographic publication with an addition that the more old people and fewer young people, economic challenges Lancet paper [1] provides significant modifications of the current will arise as societies struggle to grow with fewer workers and projections and revelations about demographic relations. taxpayers, and countries' abilities to generate the wealth needed to fund social support and health care for the elderly are reduced". Dr Richard Horton, Editor-in-Chief of The Lancet, agrees: REFERENCES "This important research charts a future we need to be planning [1] Stein Emil Vollset, Emily Goren, Chun-Wei Yuan, Jackie Cao, Amanda for urgently. It offers a vision for radical shifts in geopolitical E Smith, Thomas Hsiao, Catherine Bisignano, Gulrez S Azhar, Emma Castro, Julian Chalek, Andrew J Dolgert, Tahvi Frank, Kai Fukutaki, power, challenges myths about immigration, and underlines the Simon I Hay, Rafael Lozano, Ali H Mokdad, Vishnu Nandakumar, importance of protecting and strengthening the sexual and Maxwell Pierce, Martin Pletcher, Toshana Robalik, Krista M Steuben, reproductive rights of women. " Han Yong Wunrow, Bianca S Zlavog, Christopher J L Murray, 2020. World population likely to shrink after mid-century, forecasting major As a Commentator, Professor Ibrahim Abubakar, University shifts in global population and economic power, The Lancet, College London (UCL), UK, and Chair of Lancet Migration says: https://doi.org/10.1016/S0140-6736(20)30677-2 [2] D. Bricker, J. Ibbitson. Empty Planet. 2019. Robintson, UK. "Migration can be a potential solution to the predicted shortage [3] Gams. M., Krivec. J. 2008. Demographic analysis of fertility using data of working-age populations. While demographers continue to mining tools . Informatica : an international journal of computing and debate the long-term implications of migration as a remedy for informatic s, vol. 32, no. 2, str. 147-156. [4] Vidulin, V., Gams, M. 2012. Slovenske demografske projekcije in analize. declining TFR, for it to be successful, we need a fundamental V: MALAČIČ, Janez (ur.), GAMS, Matjaž (ur.). Soočanje z rethink of global politics. Greater multilateralism and a new demografskimi izzivi : zbornik 15. mednarodne multikonference Informacijska družba - IS 2012, str. 14-18. global leadership should enable both migrant sending and [5] Gams, M., Krivec, J. 2011. Slovenske demografske projekcije in analize. migrant-receiving countries to benefit, while protecting the rights V: MALAČIČ, Janez (ur.), GAMS, Matjaž (ur.). Soočanje z demografskimi izzivi v Evropi : zbornik 14. mednarodne multikonference of individuals. Nations would need to cooperate at levels that Informacijska družba - IS 2011, str. 14-18. have eluded us to date to strategically support and fund the [6] Lee, R., Mason, A., Sambt, J., et al. Is low fertility really a problem?: development of excess skilled human capital in countries that are population aging, dependency, and consumption. Science, ISSN 0036- 8075, 10. Oct. 2014, vol. 346, iss. 6206, str. 229-234, a source of migrants. An equitable change in global migration doi: 10.1126/science.1250542. policy will need the voice of rich and poor countries. The [7] M. Gams, J. Malačič (ur.). Bela knjiga slovenske demografije. 2019. http://library.ijs.si/Stacks/Literature/Bela%20knjiga%20demografije%20 projected changes in the sizes of national economies and the DS%202018.pdf consequent change in military power might force these [8] M. Gams. Predstavitev na posvetu v Državnem svetu o demografiji. 2018, discussions." and https://www.youtube.com/watch?v=A4rai9zoNg0 [9] Reporter 2018, M. Gams: We must eliminate ideology from science, In "Ultimately, if Murray and colleagues' predictions are even Slovene half accurate, migration will become a necessity for all nations https://reporter.si/clanek/slovenija/intervju-z-dr-matjazem-gamsom- samooklicanim-cenzorjem-se-moramo-upreti-643326 and not an option. The positive impacts of migration on health [10] Delo 2018, Jozef Stefan Institute does not support scientific theses of and economies are known globally. The choice that we face is Matjaz Gams, in Slovene, whether we improve health and wealth by allowing planned https://www.delo.si/novice/slovenija/institut-jozef-stefan-ne-podpira- stalisc-matjaza-gamsa-55676.html population movement or if we end up with an underclass of [11] Magma 2019 https://magma.fi/population-decline-and-its-effects-in- imported labor and unstable societies. The Anthropocene has europe/ [12] Šircelj, Beno, Blatnik Guzelj, Laura, Zavrtanik Drglin, Ajda, Gams, created many challenges such as climate change and greater Matjaž. Expected human longevity. V: STRLE, Toma (ur.), KOLENIK, global migration. The distribution of working-age populations Tine (ur.), MARKIČ, Olga (ur.). Kognitivna znanost : zbornik 22. Mednarodne multikonference Informacijska družba - IS 2019, 10. oktober will be crucial to whether humanity prospers or withers." 2019 : zvezek B = Cognitive Science : proceedings of the 22nd The 21st century will see a revolution in the story of our International Multiconference Information Society - IS 2019, 10 October, human civilization. Africa and the Arab World will shape our 2019, Ljubljana, Slovenia : volume B, (Informacijska družba, ISSN 2630- 371X). future, while Europe and Asia will recede in their influence. By the end of the century, the world will be multipolar, with India, Nigeria, China, and the US the dominant powers. The solutions proposed in the paper, however, bare certain amount of ideology as well since there is no influence of IT solutions for taking care of elderly and no mention that increased globalization might not only provide additional stress on our planet, it also possesses one of the existential dangers for the progress of the human civilization. Namely, the neoliberal globalism, be it as successful as it is in terms of providing progress to the rest of the world, it also puts the human civilization in grave danger of stalling and 392 Standardi kakovosti storitev zdravja na daljavo za starejše odrasle - njihov poudarjen pomen v času epidemije Covid-19 Standards of quality for telehealth services for older adults - their augmented significance in Covid-19 pandemics Neja Samar Brenčič† Drago Rudel IZRIIS Institute MKS Electronic Systems Ltd Ljubljana, Slovenia Ljubljana, Slovenia neja.samar-brencic@izriis.si drago.rudel@mks.si POVZETEK group of end users, as they need a greater degree of trust and guidance in choosing and deciding on a particular service. The Zaradi trenutne pandemije COVID-19 se je tudi na področju issues are as relevant at this time as we put out the fire of the zdravja pomembno povečalo zanimanje za storitve na daljavo pandemic, as they will be in the future, when we will increasingly (telehealth services). V poplavi informacij in novih rešitev se use remote services building on our current experiences. The potencialni naročniki, dobavitelji in končni uporabniki current crisis situation predicts long-term changes in the way of sprašujejo, katere od teh so uporabne, nujne in preizkušene. Kako providing health care at a distance. The standards on which these je z njihovo kakovostjo in ustreznostjo? Posebej občutljiva services are based play an important role in ensuring the quality skupina končnih uporabnikov so starejši odrasli, saj potrebujejo of services. There are few standards of services in this area, so večjo mero zaupanja in vodenja pri izbiri in odločanju za standardization institutions and user associations call on določeno storitev. Vprašanja so relevantna tako v tem trenutku, stakeholders to co-create in their development. In this paper we ko gasimo ogenj pandemije, kot bodo v prihodnosti, ko bomo s will present the importance of standards in the field of remote sedanjo izkušnjo vse bolj uporabljali storitve na daljavo.Trenutne health services. We will present some practical examples of krizne razmere napoveduje dolgoročne spremembe v načinu standards applied to the remote health services used by older zagotavljanja zdravstvenih storitev na daljavo. Pri zagotavljanju adults, namely CEN standard on the 'Quality of Care for Older kakovosti storitev imajo pomembno vlogo standardi, na katerih People', ETSI standard for the 'Digital Citizen' and ISO / TS temeljijo te storitve. Standardov storitev na tem področju je malo, 13131 Health informatics - Telehealth services - Quality zato standardizacijske ustanove in združenja uporabnikov planning guidelines. As a case study, we will look at the pozivajo zainteresirane strani k soustvarjanju pri njihovem “standard” International Code of Practice for Telehealth razvoju. V prispevku bomo predstavili pomen standardov na Services, for which we, in cooperation with international področju storitev zdravja na daljavo. Predstavili bomo nekaj partners, have developed a convenient tool for self-evaluation of praktičnih primerov aplikacije standardov za storitve zdravja na our own planned or implemented remote health services. daljavo, ki so v uporabi pri starejših odraslih in sicer CEN standard on the ‘Quality of Care for Older People’, ETSI KEYWORDS standard for the ‘Digital Citizen’ ter ISO/TS 13131 Health health, elderly adults, distance services, standardization, service informatics — Telehealth services — Quality planning self - evaluation. guidelines. Kot vzorčni primer bomo pogledali “standard” International Code of Practice for Telehealth Services, za katerega smo v sodelovanju z mednarodnimi partnerji izdelali 1 POMEN STANDARDOV NA PODROČJU priročno orodje za samoevalvacijo lastne načrtovane ali izvajane STORITEV ZDRAVJA NA DALJAVO storitve za zagotavljanje zdravja na daljavo. Zdravje na daljavo (telehealth) je tehnološka storitev ali sredstvo, KLJUČNE BESEDE katerega ljudje uporabljamo za dostop ali zagotavljanje storitev zdravje, starejši odrasli, storitve na daljavo, standardizacija, povezanih z zdravjem in dobrim počutjem, ne glede na svojo samoevalvacija storitve. lokacijo. Da bi bile storitve zdravja na daljavo uspešne, morajo pridobiti zaupanje tako zdravnikov; izvajalcev zdravstvene in ABSTRACT socialne oskrbe ter podpore; kot tudi formalnih in neformalnih The current COVID-19 pandemic has also significantly negovalcev. increased interest in telehealth services in the field of Woolham et al. predlaga [1], da je morda način uporabe telemedicine. In the flood of information and new solutions, zdravja in oskrbe na daljavo prav tako pomemben kot sama potential customers, suppliers and end users are wondering tehnološka rešitev oziroma podpora tej oskrbi. Prav tako meni, which of these are useful, necessary and tested. What about their da so „ne-optimalne“ rešitve verjetno povezane bolj s quality and relevance? Older adults are a particularly vulnerable sprejemljivostjo, usposabljanjem, razpoložljivostjo in s tem 393 posledično, uporabnostjo, kot pa s samo tehnološko komponento 1.3 ETSI standard for the 'Digital Citizen' ali morebitno “zapletenostjo” tehničnega dela protokola. ETSI svojim članom ponuja odprto in vključujoče okolje za Tehnološke rešitve zdravja na daljavo tako pridejo do podporo razvoju, ratifikaciji in preizkušanju globalno veljavnih realizacije le ob doseganju določenih standardov storitve, katerih standardov za sisteme in storitve IKT v vseh industrijskih in uveljavitev v konkretnih strategijah je še v razvoju. družbenih sektorjih. ETSI je neprofitna organizacija z več kot Že v bližnji prihodnosti bo večja pozornost potrebna 900 članskimi organizacijami po vsem svetu iz 65 držav in petih vzpostavitvi operativnih postopkov, ki lahko zagotavljajo celin. Člani sestavljajo raznolik nabor velikih in majhnih ustrezne standarde kakovosti tako za tehnološki del kot za same zasebnih podjetij, raziskovalnih organizacij, akademskih krogov, storitve. Le tako se bo lahko stroka kot tudi družba ustrezno vladnih in javnih organizacij. EU je ETSI uradno priznala kot odzvala na povečanje potreb in povpraševanja. Evropsko organizacijo za standardizacijo (ESO). ETSI razvija standardizacijo pametnih mest in skupnosti za 1.1 CEN standard on the 'Quality of Care for državljane in potrošnike. Cilj pobude ETSI je pripraviti in razviti Older People' tehnično poročilo ETSI leta 2020, v katerem bodo opredeljene CEN je ena od treh evropskih organizacij za standardizacijo zahteve za standardizacijo, povezano z državljani, na področju (poleg s CENELEC in ETSI), ki sta jih Evropska unija in pametnih mest. Tehnično poročilo ETSI bo v celoti upoštevalo Evropsko združenje za prosto trgovino (EFTA) uradno priznali širok spekter standardnih dejavnosti, ki trenutno potekajo, kot odgovorne za razvoj in opredelitev prostovoljnih standardov pojasnilo bo, ali je potrebna nadaljnja standardizacija vprašanj na na evropski ravni. Področje CEN / TC 449 je razvijanje državnih nivojih, povezanih s pametnimi mesti in bo podprlo standardov za oskrbo starejših, ne glede na to, kje živijo, glede priporočila, ki se že izvajajo na ravni politike. na posameznikove potrebe in izbire starejših oseb. Pametna mesta so zapletena in vključujejo raznoliko paleto Poudarek je na spodbujanju varnosti in varne oskrbe za starost storitev, težave pa vplivajo na zelo širok krog zainteresiranih s samoodločanjem in udeležbo starejše osebe ter njene družine strani, ne glede na to, ali so ta dejavna v standardizaciji ali so ter bližnjih prijateljev. Prav tako je pomembno tudi zagotavljanje potencialni uporabniki standardov, ki jih je treba obravnavati. podpore strokovnih delavcev pri ustvarjanju dostopnega in Cilj predlagane dejavnosti je pripraviti in razviti tehnično podpornega fizičnega in psihosocialnega okolja, ki zagotavlja poročilo ETSI, ki opredeljuje zahteve za standardizacijo, priložnost za ohranjanje funkcije in pomembnih dejavnosti za povezano z državljani, na področju razvoja pametnega mesta, z starejše ter zagotavljanje dobrega delovnega okolja za osebje. naslednjo vsebino: splošne potrebe državljanov, državljani in Oskrba v starosti je zapleten pojem in dejavnost, ki zahteva njihovi lokalni organi, državljani in njihovi lokalne službe, vzajemno razumevanje in sodelovanje med vsemi sodelujočimi kazalniki državljanov, priporočila za standardizacijo. akterji za spodbujanje in razvoj kakovosti storitev. Oskrba predstavlja celovit pojem, ki vključuje socialno in zdravstveno nego, rehabilitacijo, preventivne ukrepe, storitve in druga 2 ŠTUDIJA PRIMERA - INTERNATIONAL sorodna področja. CODE OF PRACTICE FOR TELEHEALTH Področje uporabe ne vključuje standardizacije izdelkov SERVICES (medicinskih pripomočkov in pripadajoče programske opreme), Mednarodni kodeks ravnanja za storitve zdravja na daljavo kliničnih in poklicnih kvalifikacij ter grajenega okolja. Vključuje (International code of practice for telehealth services - naprej pa vse storitve ne glede na njihovo financiranje. ICPTS) je razvila skupina za kakovost zdravja na daljavo - TQG (Telehealth Quality Group), ki je Evropska gospodarska 1.2 ISO / TS 13131 Health informatics - interesna skupina - EEIG. Njen predhodni Evropski kodeks je bil Telehealth services - Quality planning razvit v okviru projekta TeleSCoPE, ki ga je financirala guidelines Evropska komisija in se je končal leta 2013 (EAHC 2009 11 11). ISO / TS 13131: 2014 vsebuje nasvete in priporočila o tem, kako TQG deluje v partnerstvu z Global Community Resourcing razviti cilje kakovosti in smernice za storitve zdravja na daljavo, (Avstralija). ki uporabljajo informacijske in komunikacijske tehnologije ICPTS zagotavlja merilo kakovosti, na podlagi katerega je (IKT) za zagotavljanje zdravstvenega varstva na dolgih in mogoče oceniti in certificirati storitve zdravja na daljavo kratkih razdaljah s pomočjo postopka obvladovanja tveganj. Pri (vključno z oskrbo na daljavo). Kodeks obravnava zdravje tako razvoju ciljev in smernic za kakovost storitev zdravja na daljavo v kliničnem vidiku kot tudi v smislu splošnega dobrega počutju. se upoštevajo naslednje ključne zahteve: Umeščen je predvsem v preventivni in javnozdravstveni prostor, • upravljanje postopkov za kakovost zdravja na zato povdarja koristi za uporabnike storitev in način izvajanja daljavo s strani zdravstvene organizacije; storitev. • upravljanje finančnih virov za podporo storitvam Kodeks lahko v strateškem položaju deluje kot „dežnik“, ki zdravja na daljavo; se lahko poveže s številnimi operativnimi kodeksi, povezanimi s • procesi, povezani z ljudmi, kot so načrtovanje posebnimi nalogami, ki jih opravljajo službe zdravja na daljavo delovne sile, načrtovanje zdravstvenega varstva in (ZD). Zagotavlja visoko merilo kakovosti za storitve ZD. odgovornosti; Uporablja se lahko v vseh državah in ustreza smernicam • nudenje virov infrastrukture in zmogljivosti za določenim v resolucijah Svetovne zdravstvene organizacije storitve zdravja na daljavo; EB101.R3 (1998), WHA58.28 (2005) in WHA 66.24 (2013); ter • akcijskemu načrtu Evropske komisije za e-zdravje za obdobje upravljanje informacijskih in tehnoloških virov, ki se uporabljajo v storitvah zdravja na daljavo. 2012–2020. V Kodeksu so navedeni tudi drugi standardi ISO. 394 Pomembno je, da kodeks vključuje smernice za načrtovanje akreditacij in predpisov vključiti v nacionalne prioritete. S tem kakovosti, določene v ISO / TS 13131 (2014). To pomeni, da se bo zagotovila ne samo tehnološka kakovost, temveč enako storitev ZD, ki je certificirana v skladu s Kodeksom, izpolnjuje pomembna kakovost storitve. tudi zahteve tehničnih specifikacij ISO 13131 (Zdravstvena informatika - Telehealth Services - smernice za načrtovanje REFERENCE kakovosti). [1] John Woolham, Nicole Steils, Malcolm Fisk, Jeremy Porteus, Kirsty Forsyth, 2019. Outcomes for older telecare recipients: The importance of assessments. Journal of Social Work 0(0) 1–26 ! The Author(s) 2019 Article reuse guidelines: sagepub.com/journals- permissions DOI: 10.1177/1468017319883499 journals.sagepub.com/home/jsw [2] Malcolm Fisk, Anne Livingstone, Sabrina Winona Pit, 2020. Telehealth in the Context of COVID-19: Changing Perspectives in Australia, the United Kingdom, and the United States Med Internet Res 2020 (Jun 09); 22(6):e19264 [3] Drago Rudel, Malcolm Fisk, 2012. Telescope – telehealth services code of practice for Europe. Inform Med Slov; 17(1):38-44. [4] Drago Rudel, Malcolm Fisk, 2011. Definitions of Terms in Telehealth, Infor Med Slov; 16(1): 28-46. http://ims.mf.uni- lj.si/archive/16%281%29/21.pdf (Accessible 2011-10-12). [5] Lohan, Elena-Simona ; Cramariuc, Oana ; Malicki, Lukasz ; Samar Brencic, Neja ; Cramariuc, Bogdan. / Analytic Hierarchy Process for assessing e-health technologies for elderly indoor mobility analysis. In: EAI Endorsed Transactions on Smart Cities. 2015 ; Vol. 16, No. 3. [6] Samar Brenčič et al., Intuitive and intelligent solutions for elderly care, 2020. In Advances in Predictive, Preventive and Personalised Medicine, Proceedings of the 2nd International Conference on Digital Health technologies, Springer. Slika 1: International Code of Practice for Telehealth Services: Okvir delovanja Kodeks vsebuje devet področji, kot je prikazano na zgornji sliki. V središču je oseba, ki uporablja storitve ZD - ta položaj simbolizira pomen posameznika in svobodo odločanja glede storitev in možnosti storitev. Ključno je sodelovanje, soglašanje k načinu zbiranja, shranjevanja in uporabe njihovih osebnih (vključno z zdravstvenimi podatki); poslušanje in upoštevanje njihova stališča in mnenja ter zaščita njihovih človekovih pravic in dostojanstva. ZAKLJUČEK V maju 2020 je bila v okviru Mednarodne organizacije za zdravje na daljavo (International Society for Telehealth - IsfTeh) ustanovljena delovna skupina za standarde in akreditacijo v storitvah zdravja na daljavo (SATS). Vzpostavitev delovne skupine je spodbujalo kontinuirano delo TQG in raziskovalcev v podjetji IZRIIS in MKS, z močno podporo mednarodnih strokovnjakov medicinskih in tehnoloških področij. Razume se, da se storitve zdravja na daljavo zdaj razvijajo v izrednih razmerah. Vendar pa je ključno, da so standardi, v okviru katerih storitve delujejo stvar skupnih interesov, ciljev in stopnje pomembnosti za vse deležnike vključene v razvoj kot rudi uporabo zdravja na daljavo. Fisk navaja [2], da je treba vzpostaviti in vzdrževati vsaj osnovne standarde kakovosti v teh razmerah. Nadalje bo tudi po pandemiji potreba po vključitvi zdravja na daljavo v okvire zdravstvenih in socialnih storitev ostala prioriteta. Rudel poudarja, da bomo poleg že uveljavljenih potrebovali tudi povsem nove storitve, ki jih bomo usmerili na posameznika, denimo telemedicinske storitve za podporo bolnikom na domu, ki bodo omogočili obstoječe rešitve na področju IKT. Menimo, da zdravje na daljavo ni več le alternativna oblika zdravstvenega varstva, zato se mora tudi razvoj standardov, 395 Delitvena ekonomija za starejše Sharing Economy for Seniors Alenka Ogrin Ajda Svetelšek† Inštitut Antona Trstenjaka za gerontologijo in Inštitut Antona Trstenjaka za gerontologijo in medgeneracijsko sožitje medgeneracijsko sožitje Ljubljana, Slovenija Ljubljana, Slovenija alenka.ogrin@inst-antonatrstenjaka.si ajda.svetelsek@inst-antonatrstenjaka.si POVZETEK blaga; vloga posrednikov odpade in je zato dobrina ali storitev dostopnejša. Poglavitni cilj je učinkovitejša uporaba Zaradi populacijskega staranja gerontologija išče rešitve, ki razpoložljivih sredstev in naravnih ter človeških virov. izboljšujejo kakovost bivanja starejših oseb in jim omogočajo čimbolj samostojno življenje tudi v pozno starost. Tovrstne rešitve so vedno bolj povezane tudi z uporabo sodobne 2 DELITVENA EKONOMIJA IN STAREJŠI tehnologije. Ena takih rešitev je delitvena ekonomija. V članku V Sloveniji upokojitvene reforme generaciji, ki se upokojuje v predstavimo koncept delitvene ekonomije in preverimo teh letih, z mnogimi omejitvami prinašajo negotovo prihodnost, uporabnost le-tega za starejše osebe. saj je njihova pokojnina v povprečju za 40 % nižja od plač v KLJUČNE BESEDE aktivnem obdobju. Izziv za starejše odrasle ob upokojitvi je torej Delitvena ekonomija, IKT, starejše osebe kako se s precej manjšimi dohodki prilagoditi spremenjenim okoliščinam in ohraniti dosedanji življenjski slog. Delitvena ekonomija sicer prinaša koristi vsem generacijam. 1 UVOD Preko platform delitvene ekonomije uporabniki lahko nabavijo, V časih, ko zaradi demografske situacije, v kateri se delež si izposodijo ali najamejo določene dobrine, blago in storitve po starejših oseb v populaciji vztrajno viša, se v gerontologiji ugodni ceni ali ponudijo svoje storitve, znanja in veščine, kot tudi meddrugim usmerjamo tudi v iskanje za starejše osebe primernih svojo lastnino, tisto česar ne potrebujejo več ali pa je večino časa inovacij, ki jih omogoča sodobna tehnologija. Ena tovrstnih neizkoriščeno. S tem se zmanjšuje potrošništvo, povečuje pa rešitev, ki veliko obeta, je t.i. delitvena ekonomija. V zadnjem odgovornost do okolja in socialna vključenost, saj se na tak način desetletju se je delitvena ekonomija ( ang. sharing economy) spoznavajo ljudje zunaj svojih socialnih mrež. Priložnosti je precej razširila in postala inovativen ekonomski model, v veliko, potrebno pa jih je starejšim dobro predstaviti in katerem več oseb skupaj uporablja dobrine, na primer avto, kolo, promovirati, da prepoznajo prednosti in koristi. Šele tako se bo stanovanje ali hišo, hišne pripomočke. Pri tem je bolj pomembna ustvarila potreba in povečalo zanimanje za uporabo njenih dostopnost do dobrin kot pa lastnina dobrin. Na ta način se bolje pestrih pobud in oblik. izkorišča vrednost premalo uporabljenih nepremičnin, naprav in Negotovost, ki jo občutijo številni starejši glede uporabe IKT predmetov ter posledično vsem uporabnikom privarčuje čas, in ekonomije delitve, je še vedno prisotna. Precej starejših sicer energijo in denar. To je tudi priložnost za posameznike, ki zaradi uporablja pametne telefone, vendar večinoma pretežno osnovne zmanjšanja prihodkov - izgube službe, prekarne zaposlitve, funkcije, ne pa tudi široke palete ostalih razpoložljivih funkcij in upokojitve ali drugih vzrokov, dajo drugim v začasno uporabo aplikacij. Zato je koristno in priporočljivo razviti izobraževalne svojo lastnino, vikend, avto, pripomočke ali svoje storitve in s programe za napredno uporabo IKT naprav in programov. tem poskrbijo za dodaten vir za preživljanje. Razvoj informacijskih tehnologij, predvsem mobilnih naprav in različnih aplikacij je razvoj teh pobud še okrepil, souporaba je s 3 NAPREDNA UPORABA IKT KOT NUJEN pomočjo tehnologije postala še bolj dostopna, priročna in POGOJ ZA UPORABO DELITVENE preprosta. EKONOMIJE Če poskusimo konceptualno opredeliti pojem delitvene Po definiciji OECD “digitalni razkorak” pomeni razlike med ekonomije lahko rečemo, da gre za sistem, osnovan na delitvi oz. posamezniki, gospodinjstvi, gospodarskimi in geografskimi souporabi neizkoriščenih ali slabo izkoriščenih dobrin ali storitev, področji z različno stopnjo socialno ekonomskega razvoja v brezplačno ali proti plačilu, neposredno od ponudnikov. Ta povezavi z njihovim dostopom do priložnosti, ki jih ponuja IKT pojem se je razširil po vsem svetu, a razumevanje je različno, kot oz. internet (Organisation for Economic Co-operation and so različne tudi aktivnosti, ki jih izraz pokriva. Odvisno od pogleda in ciljev različnih uporabnikov, ta izraz lahko opisuje Development, 2001). Usposobljenost za uporabo IKT starejšim pomaga izboljšati različne koncepte. Skupna vsem je uporaba spletnih platform za komunikacijo z družinskimi člani in prijatelji, povečajo si neposredno povezovanje uporabnikov in ponudnikov storitev in 396 možnosti za vseživljenjsko učenje, razširijo socialno mrežo, upoštevali različne sektorje: prevoz, nastanitev, finance, učenje obogatijo osebne interese, dobijo pa tudi hitrejši dostop do znanj in veščin on-line itd. Ocenjujejo, da je skupna vrednost zdravstvenih in drugih uporabnih informacij. Uporaba interneta delitvene ekonomije v EU-28 državah 26,5 milijard EUR (0,17 lahko opolnomoči starejše ljudi, znatno prispeva h kakovosti % GDP-ja držav EU-28). Največje tržišče je v Franciji (6,5603 njihovega življenja in jim pomaga pri soočanju z duševnimi in milijard EUR), v Združenem kraljestvu (4.6377 milijard EUR), telesnimi težavami, ki jih lahko prinaša starost. Današnji starejši na Poljskem (2.7366 milijard EUR) in v Španiji (2.5243 milijard so se rodili precej pred tehnološko dobo, zato se niso privadili na EUR). Sedem največjih tržišč delitvene ekonomije v EU – uporabo IKT v dnevni rutini in jo v vsakdanjem življenju ne Francija, Združeno kraljestvo, Poljska, Španija, Nemčija, Italija pogrešajo; zato jih precej, predvsem starejših nad 70 let, po in Danska je v letu 2016 prispevalo približno 80 % vseh uporabi IKT niti ne čuti potrebe (Mitzner idr., 2010). prihodkov iz delitvene ekonomije v državah EU-28. Za uporabo IKT so za starejše največje ovire: Poznavanje in odnos prebivalcev Evrope do delitvene Fizične omejitve - vid, sluh, motorične in taktilne sposobnosti ekonomije se po različnih državah razlikuje: po podatkih rokovanja z manjšimi napravami, kot je npr. miška ali pametni Evropskega barometra (European Commission, 2016) je delež telefon (Charness & Boot, 2009). Teh omejitev pri rokovanju z tistih, ki še nikoli niso slišali za delitveno ekonomijo, najmanjši napravami pa nimajo samo starejši, zato je pomembno naprave v Franciji s 14 %, v drugih državah pa je bil delež višji: v Španiji prilagoditi čim širšemu krogu uporabnikov z različnimi 42 %, v Italiji 52 %, v Grčiji 64 % in Sloveniji 68 %. Delež oseb, potrebami in omejitvami. ki še nikoli niso slišali za delitveno ekonomijo, je med starejšimi Mnogo starejših poroča o tesnobi pri uporabi IKT (Hill, Betts od 55 let 55 %, med mlajšimi od 25 do 39 let pa le 38 %. 42 % & Gardner, 2015); gre za neke vrste strah in nesigurnost, ki pa sodelujočih v raziskavi, je menilo, da je dostop do dobrin oz. izvira predvsem iz nepoznavanja uporabe tehnologije kot tudi iz blaga in storitev bolje organiziran na sodelovalnih platformah, neinformiranosti kako bi jim lahko olajšala vsakdanje življenje. 33 % da so storitve tam cenejše oz. ponekod tudi brezplačne. Odpor nekaterih izvira iz predsodka, da je za obvladovanje IKT naprav potrebno veliko znanja in spretnosti, čemur se niso več sposobni prilagoditi in se naučiti novih stvari, kar bi še povečalo 5 OBLIKE DELITVENE EKONOMIJE njihove frustracije. A posledično se na ta način izolirajo, ostanejo izven družbenih dogajanj, digitalni razkorak pa se še povečuje. Obstaja več pobud in dobro delujočih praks delitvene ekonomije, Dandanes sta digitalna in socialna izključenost medsebojno tesno ki so se v različnih državah različno razvile in prijele: povezana (Delello & McWhater, 2015). Transport in mobilnost: Pomanjkljiva izobrazba in slab ekonomski položaj prav tako Javni potniški prevoz je tradicionalna in že dobo vpeljana vplivata na uporabo IKT naprav in platform med starejšimi oblika skupnega prevoza, saj potniki souporabljajo isto prevozno (Elliot, Mooney, Douthit & Lynch, 2014). Nekateri si pametnega sredstvo. Razvoj IKT in delitvene ekonomije pa je v zadnjih letih telefona ali računalnika ne morejo privoščiti; v nekaterih državah omogočil nove oblike. v ta namen obstajajo različne ugodnosti in spodbude. Sopotništvo omogoča povezavo med voznikom prevoznega Pomembno je, da navedene ovire in težave rešujemo in sredstva - ponudnikom prevoza - in potniki, ki imajo skupni cilj, starejše še naprej spodbujamo, saj se bodo le tako lahko počutili se peljejo skupaj in si delijo stroške. Javni prevoz je ponekod del družbe in imeli od IKT koristi. Zato je potrebno še naprej slabo organiziran, vozni redi pa ne ustrezajo potrebam razvijati IKT naprave in programe ter jih prilagajati različnim prebivalcem. Pri nas sopotništvo omogoča platforma prevoz.org: fizičnim in drugim oviram in zmanjšanim sposobnostim starejših. voznik objavi relacijo vožnje, čas odhoda, ceno prevoza in Ker uporaba IKT starejšim lahko prinese precej koristi in olajša kontaktne podatke, potem pa se za prevoz zainteresirani sopotnik vsakdanje življenje, se je vredno in potrebno potruditi, da jim dogovori direktno z voznikom, določita tudi mesto odhoda. Ta uporabo IKT približamo in olajšamo. način sopotnikom omogoča cenejši prevoz, spoznavanje sopotnikov različnih starosti, po drugi strani pa vsi prispevajo k ohranjanju okolja. Ker več oseb uporablja en avtomobil, se 4 UGOTOVITVE ŠTUDIJE EVROPSKE zmanjšajo potni stroški za vsakega potnika, posledično se KOMISIJE O DELITVENI EKONOMIJI znižujejo tudi ogljični odtis, zastoji na cestah, potrebe po parkirnih mestih in stres zaradi vožnje. S fenomenom delitvene ekonomije se ukvarja tudi Evropska V tujini je zelo razširjena platforma Blablacar. Ta platforma je komisija: raziskuje ga in pripravlja ukrepe za ustrezen odziv na bila ustvarjena v Franciji, vendar je svojo dejavnost razširila še v mnoge pojavne oblike (Evropska komisija, 2016). enaindvajset držav in ima 80 milijonov uporabnikov. Deluje Komisija definira sodelovalno ali delitveno ekonomijo kot malce drugače kot naši prevoz.org, francoski partnerji so jo poslovni model z naslednjimi kriteriji: opisali takole: »…Ko voznik objavi svoj prevoz, platforma - v transakciji so udeležene tri stranke: ponudnik storitev, on-line priporoča ceno na potnika glede na prevoženo razdaljo. Voznik platforma in uporabnik - stranka lahko nato zniža ali poviša ceno. Med vožnjo se navadno - ponudnik omogoči dostop do storitev ali blaga za omejeni čas sopotniki spoznajo in tako se navežejo stiki med osebami, ki se - blago, storitve ali sredstva, ki jih ponuja v uporabo ponudnik, verjetno drugače ne bi nikoli srečale, ne glede na starost in bi bile sicer neizkoriščene socialno ali drugo pripadnost. Dobra praksa je torej v tem, da - blago, storitve ali sredstva so dostopne brezplačno ali proti povezuje različne ljudi, znižuje prevozne stroške in zmanjšuje plačilu onesnaževanje okolja.« V študiji Evropske komisije (Evropska komisija, 2018) so Souporaba prevoznih sredstev: raziskovali obseg sodelovalne ekonomije v EU-28 državah in 397 Že dobro stoletje je znana oblika »rent-a-car«, kjer si Homeforexchange: https://www.homeforexchange.com posamezniki za nekaj dni ali dlje časa najamejo avto ali drugo Gre za ekonomičen in udoben način nastanitve za čas počitnic oz. prevozno sredstvo. V zadnjem desetletju pa se je pojavilo precej na potovanjih. Preko te mednarodne platforme, ki je v angleškem novih oblik trajnostne mobilnosti, ki omogočajo kratkoročni jeziku, uporabnika navežeta stik in se dogovorita za izmenjavo najem oz. souporabo prevoznih sredstev – osebnih avtomobilov, domovanja za izmenjavo - stanovanja, apartmaja ali počitniške električnih skirojev itd. hiše; izmenjava je lahko simultana, ob istem času ali po dogovoru V Sloveniji se je uveljavil Avant2Go. Gre za model najema v različnem obdobju. Na tak način je nastanitev brezplačna, avtomobilov, pri katerem jih vozniki najemajo za kratek čas, za potrebno je le plačilo pristojbine ob registraciji na spletni strani. razdaljo od točke A do točke B in plačujejo le glede na čas Potrebna pa je tudi visoka stopnja medsebojnega zaupanja, da bo uporabe in prevoženo razdaljo. Avtomobili so električni in na vsak ravnal z izmenjanim domovanjem kot s svojim. voljo v posebej določenih parkirnih mestih, celoten proces Affitto Giardino: https://affittogiardino.it/ rezervacije in uporabe avtomobila poteka preko posebne Deluje podobno kot druge platforme, ki omogočajo souporabo aplikacije na pametnem telefonu. Souporaba avtomobilov je del zasebnih nepremičnin z začasnimi uporabniki, ki so pripravljeni večjega trenda skupne mobilnosti, ki uporabniku omogoča za to plačati. Osredotoča se izključno na uporabo zasebnih zniževanje stroškov svoje mobilnosti, saj finančnega bremena zunanjih površin – večjih vrtov, atrijev in dvorišč, zato je lastništva vozila ni več, prav tako ne stroškov vzdrževanja, zanimiv za tiste, ki potrebujejo prostor za izvedbo prireditev oz. parkiranja, goriva, cestnin itd. Starejši lahko sodelujejo kot kateri manjših dogodkov – praznovanje rojstnih dnevov, obletnic, koli drugi uporabniki, potreben je pametni telefon in napredno porok ipd. Na drugi strani so ponudniki - lastniki hiš z večjim znanje IKT. S tem ostanejo neodvisni, mobilni, aktivni in vrtom, ponekod z bazenom, letno kuhinjo ali zunanjim žarom itd., vključeni v družbo. ki želijo z oddajo teh površin na prostem povečati svoje prihodke. Za starejše osebe uporaben primer na področju prevoza je tudi Wallapop: https://es.wallapop.com platforma Drivy oz. po novem Getaround, preko katere lahko Ta platforma omogoča nakup in prodajo rabljenih predmetov, lastnik avta drugim odda svoj avto za čas, ko ga ne potrebuje oz. oblačil itd. V Španiji ima 20 milijonov uporabnikov (skoraj stoji avto neizkoriščen. Še posebej starejši svojih prevoznih polovica prebivalstva) in 70.000 dnevnih transakcij. Med dobre sredstev ne uporabljajo toliko kot prej, ker ni več potrebe, a avto prakse smo ta primer uvrstili, ker lahko pripomore k socialni še vedno obdržijo kljub rednim stroškov vzdrževanja, registracije vključenosti starejših, ponuja možnost ponovne uporabe za itd. Ta pobuda je na voljo v mnogih zahodnoevropskih državah. predmete, ki jih ne potrebujemo več in možnost povezovanja ComParko je spletna platforma, ki posreduje med lastniki ljudi s podobnimi potrebami in hobiji. Ta platforma je parkirnih mest oz. garaž in vozniki, ki jih potrebujejo. S pomočjo primerljiva je s slovensko bolha.com. platforme je mogoče poiskati, najeti ali si deliti parkirno mesto Storitve za pomoč starejšim za mesece, tedne, dneve ali celo ure. Ta pobuda se je začela v Ugo: https://hellougo.com Španiji in zdaj deluje po vsej Evropi. Italijanska platforma, ki starejšim in njihovim družinam Bivanje, nastanitve – souporaba neizkoriščenih kapacitet omogoča iskanje oskrbovalcev in spremljevalcev pomoči Skupnostno bivanje ali sobivanje je alternativa tradicionalnim potrebnim v njihovem lokalnem okolju. Koordinatorji te oblikam bivanja starejših; pri tem platforma nudi možnost platforme izvajalce predhodno preverijo in odobrijo. Gre za navezovanja stikov med ljudmi podobne starosti, ki jih zanimajo različne oblike pomoči starejšim ali invalidnim osebam, od tovrstne oblike sobivanja, s čimer se izognejo osamljenosti, osnovnih vsakodnevnih opravil do spremstva v trgovino, k spodbuja pa se vključenost in socialni stiki. V Španiji je več zdravniku, družabništvo, hišna opravila, vrtnarjenje ipd. Starejši tovrstnih iniciativ – stanovanjskih skupnosti starejših, večina je so večinoma uporabniki storitev, ki jih ponuja platforma, saj jim organiziranih kot zadruge. Najbolj znan primer je stanovanjska pomoč ali družba oskrbovalcev omogoči varno življenje doma zadruga Trabensol blizu Madrida https://trabensol.org. ali pa jim pomagajo pri dejavnostih, ki bi jo sicer težko izvedli Un toit 2 Générations: http://untoit2generations.fr sami ali brez pomoči družinskega člana. Po drugi strani pa lahko Gre za medgeneracijsko sobivanje. Platforma omogoča še aktivni starejši prek platforme Ugo ponudijo svoj čas in povezovanje starejših – ponudnikov nastanitve - in mladih, storitve drugim ljudem, s čimer ostanejo aktivni, tako fizično kot največkrat študentov, ki potrebujejo sobo oz. začasno nastanitev. socialno ter vključeni v družbo. Deluje v Metzu in Nancyju. S tem, ko starejši gosti študenta na Village Care: https://www.villagecare.it svojem domu, dobi družbo in pomoč, lahko deli svoja znanja in Deluje kot platforma, kjer se srečujejo potrebe (starejši ljudje in hobije ter se uči novih stvari. Družba v hiši je lahko za starejšega družine) in ponudba (ponudniki storitev). Uporabniki lahko človeka poživljajoča in spodbudna. Cilji platforme so brskajo po ponudbi domov za ostarele, dnevnem varstvu in spodbujanje medgeneracijske komunikacije in borba proti vse Alzheimerjevih centrov, oskrbovanih bivalnih enotah, ter večji socialni izolaciji starejše populacije. poiščejo formalne ali neformalne oskrbovalce in druge možnosti Turistične nastanitve za krajši čas: oskrbe na domu. Platforma omogoča starejšim, družinam in Platforme - najbolj poznana Airbnb - omogočajo lastnikom oskrbovalcem celovit vpogled in informacije o storitvah za stanovanj ali hiš, da za krajši čas oddajo sobe ali stanovanja, ki družine in starejše občane, ki iščejo storitve oskrbe, zdravstvene so sicer neizkoriščena. Med ponudniki je precej starejših oseb, ki podpore in možnosti bivanja, ki so na voljo v njihovem lokalnem si z dodatnim zaslužkom izboljšajo ekonomski položaj. okolju. Široka ponudba priložnosti olajša iskanje pomoči pri Na platformi Freebirdclub, specializirani le na starejše od 60 let, aktivnem življenjskem slogu in preprečuje socialno izključenost. ponudniki svoje neizkoriščene nepremičnine – sobe, stanovanja Platforma ponuja tudi strokovno svetovanje in orientacijo tako ali vikend hiše – oddajajo izključno starejšim osebam, za za uporabnike kot za strokovno osebje. počitnice, na potovanjih itd. 398 Druga področja: 6 ZAKLJUČEK L'Accorderie: http://www.accorderie.fr Koncept delitvene ekonomije lahko doprinese veliko koristi v Časovna banka, ki se je dobro ustalila v Franciji: platforma življenja starejših oseb. Ker starejše generacije nimajo toliko omogoča ljudem vseh starosti posredovanje veščin, znanja in izkušenj z uporabo sodobne tehnologije, na kateri je delitvena hobijev drugim ali jih sprejemajo sami. Menjalna valuta je čas, ekonomija dandanes utemeljena, je potrebno povečati na eni ovrednoten po kreditnem principu. Koncept so razvili v strani fokus stroke v prilagajanje tehnologije za potrebe starejših kanadskem Quebecu in je zdaj dosegel veliko francoskih mest, ter na drugi strani fokus stroke v oblikovanje učinkovitih vključenih je več kot 4.000 ljudi. Glavni rezultat je medčloveška usposabljanj za učenje napredne rabe tehnologije za starejše. solidarnost, saj spodbuja socialno angažiranost, medgeneracijsko sodelovanje, lokalno izvajanje in krepitev skupnosti. REFERENCE Zelemenjava: http://www.zelemenjava.si Gre za slovensko samoorganizirano civilno iniciativo za [1] Charness, N. & Boot, W. R. (2009). Aging and Information Technology Use: Potential and Barriers. Current Directions in Psychological Science, izmenjavo presežnih semen, sadik in pridelkov z domačih vrtov, 18/5, str. 253-258. ki udeležencem omogoča samooskrbo in boljše prehranjevanje, [2] Delello, J. A. & McWharter, R. R. (2015). Reducing the Digital Divide: Connecting Older Adults to iPad Technology. Journal of Applied prihranek, zmanjšanje živilskih odpadkov in srečevanje z Gerontology, 36/1, str. 3-28. drugimi vrtičkarji in sosedi. Udeleženci so ljudje različnih [3] Elliot, A. J., Mooney, C. J., Douthit, K. Z. & Lynch, M. F. (2013). Predictors of Older Adults' Technology Use and Its Relationship to generacij, ki gojijo zelenjavo za lastno uporabo, ne glede na Depressive Symptoms and Well-being. The Journals of Gerontology: izobrazbo, starost ali socialni status. Edino pravilo je, da se denar Series B, 69/5, str. 667-677. ne uporablja kot menjalno sredstvo, s čimer se spodbuja [4] European Commision (2016). Flash Eurobarometer 438 Report: The use of collaborative platforms. Brussels: European Commision. samozadostnost in solidarnost med člani lokalne skupnosti. Po [5] European Commision (2018). Study to Monitor the Economic besedah pobudnic je več kot polovico sodelujočih starejših oseb. Development of the Collaborative Economy in the EU: Final Report. Brussels: European Commision. Delitvena ekonomija in koncepti souporabe ob podpori IKT [6] Hill, R., Betts, L. R. & Gardner, S. E. (2015). Older adults' experiences so lahko eden od odgovorov na vprašanje kako lahko starejši and perceptions of digital technology: (Dis)empowerment, wellbeing, and ostanejo aktivni, vključeni, neodvisni, varni in mobilni. S tem si inclusion. Computers in Human Behavior, 48, str. 415-423. [7] Mitzner, T. L., Boron, J. B., Bailey Fausset, C., Adams, A. E., Charness, izboljšajo svoje življenje in hkrati prispevajo tudi za dobro N. idr. (2010). Older adults talk technology usage and attitudes. drugih ljudi, družbe in okolja. Computers in Human Behavior, 26, str. 1710-1721. [8] OECD – Organisation for Economic Co-operation and Development (2001). Understanding the Digital Divide. OECD Publications 399 Razlike med spoloma v ekonomski odvisnosti v obdobju 2000–2012 The gender gap in economic dependency in the period 2000–2012 Tanja Istenič Irena Ograjenšek Jože Sambt Ekonomska fakulteta, Univerza v Ekonomska fakulteta, Univerza v Ekonomska fakulteta, Univerza v Ljubljani Ljubljani Ljubljani Kardeljeva ploščad 17, 1000 Kardeljeva ploščad 17, 1000 Kardeljeva ploščad 17, 1000 Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija Tel: +386 1 5892778; fax: +386 1 Tel: +386 1 5892505; fax: +386 1 Tel: +386 1 5892515; fax: +386 1 5892698 5892698 5892698 e-pošta: tanja.istenic@ef.uni-lj.si e-pošta: irena.ograjensek@ef.uni-lj.si e-pošta: joze.sambt@ef.uni-lj.si POVZETEK KEYWORDS V ekonomski analizi je obdobje ekonomske odvisnosti običajno National Transfer Accounts, economic dependency, gender opredeljeno z uporabo fiksnih starostnih mej, neodvisnih od države, dimension, Slovenia. leta analize, spola itd. Poleg tega običajno predpostavljamo enak obseg ekonomske odvisnosti, ne glede na starost odvisnih posameznikov. Metodološki okvir računov nacionalnih transferjev 1 UVOD (angl. National Transfer Accounts – NTA) nam s pomočjo koncepta V času trajanja svojega življenja se posamezniki soočajo z dvema primanjkljaja življenjskega cikla omogoča natančno merjenje obdobjema ekonomske odvisnosti, v času otroštva in v času starosti. obdobja in obsega ekonomske odvisnosti. V članku predstavljamo V obdobju ekonomske odvisnosti posamezniki porabijo več, kot rezultate retrospektivne analize NTA po spolu za Slovenijo v zaslužijo, in se na ta način soočajo s t. i. primanjkljajem obdobju 2000–2012. Rezultati kažejo, da so bile ženske v letu 2012 življenjskega cikla. Ekonomska odvisnost mladih in starih je sposobne financirati svojo potrošnjo za obdobje 29,0 let, medtem ko financirana s strani delovno aktivne populacije, katere delovni moški 35,9 let. Vendar pa se v času razlika med spoloma v dolžini dohodek presega potrošnjo. Delovno aktivna populacija se sooča s t. i. presežkom življenjskega cikla, ki jim omogoča financiranje ekonomske neodvisnosti skrajšuje, s 7,9 let v letu 2000 na 6,9 let v odvisnosti mladih in starih v obliki javnih in zasebnih transferjev letu 2012. ter javne in zasebne prerazdelitve iz naslova sredstev (angl. asset-based reallocations) [2]. KLJUČNE BESEDE V ekonomski analizi je obdobje ekonomske odvisnosti običajno računi nacionalnih transferjev, ekonomska odvisnost, vidik spola, opredeljeno z uporabo fiksnih starostnih mej, neodvisnih od države, Slovenija. leta analize, spola itd. Poleg tega običajno predpostavljamo enak obseg ekonomske odvisnosti, ne glede na starost odvisnih posameznikov. Metodološki okvir računov nacionalnih transferjev ABSTRACT (angl. National Transfer Accounts – NTA) nam s pomočjo koncepta In the economic analysis, the period of economic dependency is primanjkljaja življenjskega cikla omogoča natančno merjenje usually defined using fixed age limits, independently of country, obdobja in obsega ekonomske odvisnosti. Z vpeljavo vidika starosti v Sistem nacionalnih računov (SNA) nam NTA omogoča year of analysis, gender, etc. Moreover, the same size of economic ocenjevanje starostnospecifičnih vrednosti ekonomskih kategorij, dependency is usually assumed, independently of the age of kot so delovni dohodek, dohodek iz premoženja, transferji, dependent individuals. However, by using the concept of the life potrošnja in varčevanje. Ker so starostnospecifične vrednosti cycle deficit, the National Transfer Accounts (NTA) framework ekonomskih kategorij močno odvisne tudi od časa in spola, v članku enables us to precisely measure the period and size of economic v običajno analizo NTA dodajamo še dimenzijo časa in spola. V dependency. This paper presents the results of a retrospective NTA članku tako predstavljamo rezultate retrospektivnih NTA po spolu by gender for Slovenia in the period 2000–2012. Our results show v Sloveniji v obdobju 2000–2012, ki nam pomagajo odgovoriti na that in 2012, women were able to finance their consumption with naslednja raziskovalna vprašanja: their labour income for 29.0 years, whereas men financed their (1) Kako velike so razlike med spoloma v delovnem dohodku, consumption for 35.9 years. However, the significant gender gap in potrošnji in primanjkljaju življenjskega cikla? the length of economic independence decreased over time, from 7.9 (2) Kako se vzorci delovnega dohodka, potrošnje in primanjkljaja years in 2000 to 6.9 years in 2012. življenjskega cikla obeh spolov spreminjajo skozi čas? (3) Ima ekonomska kriza vpliv na razlike v dolžini in velikosti primanjkljaja življenjskega cikla med spoloma? 400 2 METODOLOGIJA IN PODATKI 3 REZULTATI Metodologija NTA temelji na proračunski omejitvi posameznika, Slika 1 prikazuje dohodek iz dela in (javno ter zasebno) potrošnjo kjer se morajo prilivi izenačiti z odlivi. Med prilive štejemo delovni obeh spolov. Iz slike je razvidno, da ima delovni dohodek moških dohodek (𝑌𝑙), dohodek iz premoženja (𝑌𝐴) in prilive transferjev in žensk v celotnem obdobju med letoma 2000 in 2012 v Sloveniji (𝜏+); med odlive pa potrošnjo (𝐶), odlive transferjev (𝜏−) in tipično obliko obrnjene U-krivulje, vendar med spoloma obstajajo varčevanje (𝑆). S preureditvijo členov dobimo naslednjo velike razlike v vrednosti delovnega dohodka pri vseh starostih. računovodsko identiteto [2]: Delovni dohodek žensk začne naraščati kasneje kot delovni dohodek moških predvsem zaradi višje stopnje vpisa žensk v 𝐶( ⏟ 𝑥 ) − 𝑌𝑙 (𝑥 ) = 𝜏+ ⏟ ( 𝑥 ) − 𝜏− ( 𝑥 ) + (1) terciarno izobraževanje. Tudi v delovni starosti je dohodek žensk 𝑃𝑟𝑖𝑚𝑎𝑛𝑘𝑙𝑗𝑎𝑗 ž𝑖𝑣𝑙𝑗𝑒𝑛𝑗𝑠𝑘𝑒𝑔𝑎 𝑐𝑖𝑘𝑙𝑎 𝑁𝑒𝑡𝑜 𝑡𝑟𝑎𝑛𝑠𝑓𝑒𝑟𝑗𝑖 nižji od dohodka moških, in sicer predvsem zaradi njihove nižje + 𝑌𝐴 ⏟ ( 𝑥 ) − 𝑆 ( 𝑥 ). stopnje vključenosti na trg dela in rahlo nižjih plač žensk v 𝑃𝑟𝑒𝑟𝑎𝑧𝑑𝑒𝑙𝑖𝑡𝑒𝑣 𝑖𝑧 𝑛𝑎𝑠𝑙𝑜𝑣𝑎 𝑠𝑟𝑒𝑑𝑠𝑡𝑒𝑣 primerjavi z moškimi v primeru zaposlitve za polni delovni čas. V Otroci in starejši se soočajo s pozitivnim primanjkljajem višji starosti začne delovni dohodek žensk padati hitreje kot delovni življenjskega cikla (ki je opredeljen kot razlika med javno in dohodek moških, saj se v povprečju ženske upokojujejo hitreje zasebno potrošnjo ter delovnim dohodkom). Primanjkljaj kakor moški. Ne glede na to, da ženske vseh starosti zaslužijo manj življenjskega cikla določa njihovo ekonomsko odvisnost. Na drugi kot moški, je pri praktično vseh starostih njihova potrošnja višja od strani, v času delovne aktivnosti, delovni dohodek presega potrošnje moških. Razlika med spoloma v ravni potrošnje v nižjih potrošnjo, kar vodi v negativen primanjkljaj življenjskega cikla, tj. starostnih razredih je predvsem rezultat relativno višje stopnje vpisa presežek življenjskega cikla. Presežek življenjskega cikla omogoča žensk v formalno izobraževanje. Razlika med spoloma v potrošnji zaposlenim financiranje primanjkljaja življenjskega cikla je še bolj očitna v času aktivne delovne dobe, ko imajo v času ekonomsko odvisnega prebivalstva. Ekonomska odvisnost se materinstva ženske višjo predvsem javno in zasebno zdravstveno financira z različnimi oblikami medgeneracijskih tokov: javni neto potrošnjo. transferji (prilivi minus odlivi transferjev), zasebni neto transferji in V času se starostni profil delovnega dohodka obeh spolov prerazdeljevanjem iz naslova sredstev (dohodek iz premoženja pomika v desno. Posamezniki namreč v času na trg dela vstopajo minus varčevanje). pri višji starosti in se pri višji starosti tudi upokojujejo. Zaznati pa Za analizo ekonomske odvisnosti je potrebno oceniti številne je bolj očiten premik delovnega dohodka žensk v primerjavi z starostne profile. Starostni profili so starostni vzorci (povprečja) delovnim dohodkom moških. V obdobju med letoma 2000 in 2012 nadalje razčlenjenih spremenljivk, vključenih v računovodsko se v nižjih starostnih razredih povečuje razlika v delovnem dohodku identiteto. V prvem koraku s pomočjo SNA in drugih podobnih med spoloma, medtem ko se razlika v dohodku višjih starostnih podatkovnih virov izračunamo agregatne vrednosti posameznih razredov zmanjšuje. Zadnje je predvsem posledica procesa spremenljivk. V drugem koraku izračunamo relativno porazdelitev izenačevanja pogojev za upokojitev obeh spolov. Višja potrošnja določene spremenljivke po starostnih skupinah s pomočjo anketnih žensk v primerjavi z moškimi je značilnost celotnega obdobja in/ali administrativnih podatkov. Starostne profile iz drugega 2000–2012, razlike med spoloma v času materinstva pa se skozi čas koraka pomnožimo z ustreznim faktorjem prilagajanja (angl. povečujejo. adjustment factor), tako da se starostni profili, pomnoženi s starostno strukturo prebivalstva, ujemajo z agregatnimi vrednostmi iz prvega koraka. Večina starostnih profilov je izglajena; na ta način izločimo vpliv posledic slučajnih dejavnikov v vzorčnih podatkih [4]. Rezultati NTA so torej presečni rezultati, pridobljeni s pomočjo sekundarnih virov podatkov. Za ocenjevanje retrospektivnega NTA za Slovenijo so uporabljeni mikropodatki iz Ankete o porabi gospodinjstev za leta 2000, 2003, 2005, 2008, 2010 in 2012. NTA po spolu so ocenjeni podobno kot običajni NTA. Kadar so starostni profili izračunani na podlagi anketnih podatkov, je edina razlika ta, da moramo poleg povprečij po starostnih skupinah izračunati tudi povprečja po spolu. Starostni profili so prilagojeni na način, da se zagotovi skladnost z makroekonomskimi agregati in tudi s starostnimi profili običajne analize NTA [1]. V članku poleg grafične predstavitve razlik v potrošnji, delovnem dohodku in primanjkljaju življenjskega cikla prikazujemo tudi rezultate dveh kazalnikov, ki kažeta razlike v ekonomski odvisnosti med spoloma, in sicer (1) absolutno razliko v dolžini ekonomske neodvisnosti med obema spoloma in (2) razliko v obsegu ekonomske odvisnosti Slika 1: Dohodek iz dela in potrošnja moških in žensk, med spoloma, prilagojeno za velikost delovnega dohodka celotne Slovenija, 2000–2012 populacije. Vir: APG 2000–2012, Eurostat, mnogi drugi viri. Zaradi nižjega delovnega dohodka, a hkrati višje potrošnje žensk v primerjavi z moškimi, so ženske ekonomsko neodvisne krajše obdobje življenjskega cikla kakor moški. V letu 2012 je delovni dohodek žensk presegal njihovo potrošnjo zgolj med 27,7. 401 in 56,7. letom starosti (glej Tabelo 1). Na drugi strani so bili moški odvisnosti žensk potrebnega 4,7 % celotnega delovnega dohodka ekonomsko neodvisni med starostjo 24,1 in 60,0 let. Moški so bili več, kakor ga je bilo potrebnega za financiranje odvisnosti moških. tako v povprečju sposobni financirati svojo potrošnjo z delovnim V času se, skladno s premikom delovnega dohodka, v desno dohodkom 6,9 let dlje kot ženske. premika tudi starostni profil primanjkljaja življenjskega cikla. Krajše obdobje ekonomske neodvisnosti žensk in njihovo Znatnejši premik za ženske v primerjavi z moškimi vodi v daljše daljše življenjsko pričakovanje ob rojstvu vodi v daljše obdobje obdobje ekonomske neodvisnosti oziroma daljše obdobje presežka ekonomske odvisnosti oz. primanjkljaja življenjskega cikla žensk v življenjskega cikla za ženske, in sicer z 28,3 let v letu 2000 na 29,0 primerjavi z moškimi. Ekonomska odvisnost žensk pa ni zgolj let v letu 2012. Nasprotno se obdobje ekonomske neodvisnosti daljša, ampak je tudi bolj intenzivna. V letu 2012 je celoten moških celo rahlo skrajšuje, in sicer s 36,1 let v letu 2000 na 35,9 let primanjkljaj življenjskega cikla moških znašal 25,5 % celotnega v letu 2012. Razlika v dolžini ekonomske neodvisnosti med spoloma delovnega dohodka, medtem ko je celotni primanjkljaj se je tako skrajšala z začetnih 7,9 let v letu 2000 na 6,9 let v letu življenjskega cikla žensk znašal 30,2 % celotnega delovnega 2012. Ob tem se v času zmanjšuje tudi razlika v obsegu ekonomske dohodka. To pomeni, da je bilo za financiranje ekonomske odvisnosti, in sicer z začetnih 6,3 % celotnega delovnega dohodka v letu 2000 na 4,7 % v letu 2012. Tabela 1. Razlike med spoloma v dolžini/obsegu presežka/primanjkljaja življenjskega cikla, Slovenija, 2000–2012 Obseg Dolžina primanjkljaja presežka življenjskega Starostne meje življenjskega cikla glede ∆LCSM/Ž ∆NtaDRŽ/M Leto Spol presežka cikla življenjskega cikla na delovni (v letih) (v %) (LCS; v dohodek letih) (NtaDR; v %) Moški 22,5 58,6 36,1 25,3 2000 7,9 6,3 Ženski 24,4 52,7 28,3 31,6 Moški 23,3 59,7 36,4 25,8 2003 7,8 6,2 Ženski 25,4 54,0 28,6 32,1 Moški 23,5 59,9 36,4 24,7 2005 7,1 5,7 Ženski 25,4 54,7 29,3 30,4 Moški 23,4 60,5 37,1 24,3 2008 7,2 5,2 Ženski 26,3 56,3 30,0 29,5 Moški 23,9 59,6 35,7 27,1 2010 6,3 5,4 Ženski 26,7 56,2 29,4 32,5 Moški 24,1 60,0 35,9 25,5 2012 6,9 4,7 Ženski 27,7 56,7 29,0 30,2 Vir: APG 2000–2012, Eurostat, mnogi drugi viri. Iz Tabele 1 je razvidno tudi, da se je v obdobju pred krizo, med skrajševal. To lahko pojasnimo z varčevalnimi ukrepi javnega letoma 2000 in 2008, obdobje presežka življenjskega cikla sektorja, v katerem je zaposlen višji odstotek žensk kakor moških. podaljšalo za oba spola, vendar je bilo podaljšanje bolj očitno za Ne glede na to so se razlike med spoloma v dolžini presežka ženske kakor za moške. Kasneje je ekonomska kriza vplivala na življenjskega cikla zmanjšale tudi v času ekonomske krize, med skrajševanje obdobja presežka življenjskega cikla za oba spola. Kot letoma 2008 in 2012. rezultat visoke stopnje brezposelnosti v panogah, ki pretežno Ekonomska kriza je prav tako vplivala na razliko v obsegu zaposlujejo moško delovno silo, se je na začetku krize presežek ekonomske odvisnosti obeh spolov. Medtem ko se je v začetku življenjskega cikla moških skrajšal bolj, kakor se je skrajšal ekonomske krize razlika v obsegu ekonomske odvisnosti med presežek življenjskega cikla žensk. V razmahu ekonomske krize, ko spoloma povečala, se je v razmahu krize začela zmanjševati. Kljub se je presežek življenjskega cikla moških začel ponovno začetnemu povečanju razlike v obsegu ekonomske odvisnosti obeh podaljševati, se je presežek življenjskega cikla žensk še nadalje spolov, se je le-ta v celotnem obdobju krize zmanjšala. Če 402 povzamemo, navkljub temu da je ekonomska kriza prekinila približevanje ekonomske (ne)odvisnosti žensk k ekonomski (ne)odvisnosti moških, se je razlika v ekonomski (ne)odvisnosti obeh spolov zmanjšala tudi v celotnem preučevanem obdobju krize. 4 SKLEP V pričujočem članku predstavimo rezultate retrospektivne analize NTA po spolu. NTA nam s pomočjo koncepta primanjkljaja oz. presežka življenjskega cikla omogočajo analizo posameznikove ekonomske odvisnosti oz. neodvisnosti skozi življenjski cikel. Iz naših rezultatov izhaja, da je razlika med spoloma v delovnem dohodku prisotna pri vseh starostih, ko ženske zaslužijo manj kot moški, medtem ko je razlika v potrošnji očitna predvsem v času materinstva, ko ženske porabijo več kot moški. Ženske so tako ekonomsko odvisne daljše obdobje življenjskega cikla. V letu 2012 so bile ženske sposobne financirati svojo potrošnjo v starostnem razponu 29,0 let, moški pa 35,9 let. Vendar pa se v času razlika v dolžini ekonomske neodvisnosti skrajšuje, s 7,9 let v letu 2000 na 6,9 let v letu 2012. Prav tako se v času zmanjšuje tudi razlika med spoloma v obsegu ekonomske odvisnosti. Kljub temu da je ekonomska kriza prekinila približevanje obdobja ekonomske neodvisnosti in obsega ekonomske odvisnosti žensk vrednostim za moške, so se razlike med spoloma tudi v celotnem obdobju krize zmanjšale. LITERATURA IN VIRI [1] Donehower, G. (2014). Incorporating gender and time use into NTA: National Time Transfer Accounts methodology (version 4, May 2014). Internal materials of the NTA project. [2] Lee, R., & Mason, A. (2011). Population aging and the generational economy: A global perspective. Cheltenham, UK; Northampton, MA: Edward Elgar. [3] Statistični urad Republike Slovenije. (2013). Anketa o porabi gospodinjstev za leta 1993, 1998, 2000, 2003, 2005, 2008, 2010, and 2012 (interni podatki). Ljubljana: Statistični urad Republike Slovenije. [4] United Nations. (2013). National Transfer Accounts Manual: Measuring and Analysing the Generational Economy. New York: United Nations. 403 Demonstrational vegetable garden with ReSoil remediated soil Domen Leštan Envit Ltd. and University of Ljubljana Ljubljana, Slovenia domen.lestan@bf.uni-lj.si ABSTRACT reused in a closed loop, no wastewater is generated, and only solid waste enriched with toxic metals is produced. The EDTA The contaminated calcareous soil from Prevalje, Slovenia was is poorly biodegradable and persist in the environment. This has EDTA-washed using novel ReSoil technology. Washing raised concerns about leaching of toxic chelates from remediated removed 71, 28 and 53% of soil Pb, Zn and Cd, respectively. The soil and risking groundwater contamination. In ReSoil extensive vegetable garden with 3 raised beds with non-remediated rinsing of remediated soil removes the majority of toxic chelates (original) and 6 beds with remediated soils was set up and from the soil and zero-valent Fe (ZVI) is applied to the soil slurry realistically tended; a selection of 10 different produces were to facilitate the permanent adsorption of the remaining chelates. grown. All vegetables reached the mature phase without We demonstrated that in ReSoil toxic emissions are not an issue difficulties or visible deficiencies, irrespective of soil treatment. [2, 4]. Grown on original soil all plants exceeded limits for Pb The aim of this study was to scale-up the ReSoil technology concentration in their edible parts stipulated by European Union to provide enough soil to set-up and manage the genuine legislature. In remediated soil only carrot exceeded limit for Pb. vegetable garden and to examine the possibility of production of Remediation was less efficient in mitigation of Cd hazard; safe food on remediated soil. concentration of Cd in spinach, second cut of radicchio, and carrot exceeded the allowed values. The vegetable type is a strong determinant of metal concentration in edible crop. The 2 MATERIALS AND METHODS selection of excluders instead of accumulators will thus be crucial for production of safe food on ReSoil remediated soils. 2.1 Soil Remediation The surface soil was excavated from grassland in the bank of the KEYWORDS river Meza in city of Prevalje in Meza Valley, Slovenia. The Soil, Toxic metals, Remediation, Vegetable garden excavated soil was in situ homogenized and then transported to a nearby remediation facility for EDTA-soil washing using ReSoil technology. 1 INTRODUCTION Fertile soil is a valuable, limited resource. As human population 2.2 Experimental garden and pressure on limited soil resources are continuously growing, Raised beds (4 x 1 x 0.5 m) were constructed and vegetables: more and more land contaminated with toxic metals is expected buckwheat, spinach, lamb’s lettuce, radicchio, garlic, onion, to be put under agricultural production in a delicate balance of leek, lettuce, carrots and kohlrabi were grown in 6 rotations from needs, social & economic benefits and health risks. The harmful, the July 2018 until the end of November 2019. pandemic effect of toxic metals on human health is well documented and governments are setting remediation of 2.3 Analysis contaminated soil as a national priority. Samples of soil and vegetables were prepared as described before We have recently introduced ReSoil soil washing technology [4] and analyzed using graphite furnace AAS. which uses ethylenediamine-tetraacetate (EDTA) as a chelator [1, 2, 3]. The EDTA forms water-soluble complexes (chelates) with most toxic metals and is the most efficient chelator. The 3 RESULTS AND DISCUSION ReSoil was designed to recycle most of EDTA and all process water. For this to achieve the process solutions are treated by The novel remediation plant with ReSoil technology is depicted low-cost materials: lime, H2SO4, and wastepaper to impose pH in Figure 1. The Technology Readiness Level of plant operation gradient and induce recycling (substitution, precipitation and was TRL 7 (EU, NASA methodology). The permit for adsorption) reaction. The recycled EDTA and process water are construction of ReSoil soil washing plant was granted by Slovenian Environmental Protection Agency in 2017, and the Permission to make digital or hard copies of part or all of this work for personal or operating permit to remediate in July 2018. For this study the classroom use is granted without fee provided that copies are not made or distributed contaminated soil was remediated in series of 16 batchers – these for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must were at the same time the first batches carried out in novel be honored. For all other uses, contact the owner/author(s). remediation plant. In total 16 tons of soil was washed. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 20 Using EDTA in ReSoil technology decreased Pb, Zn and Cd 20 Copyright held by the owner/author(s). soil concentration from 1854 ± 120, 3833 ± 135 and 21.2 ± 1.2 mg kg-1 to 545 ± 17, 2743 ± 120 and 9.9 ± 0.4 mg kg-1, 404 respectively. To improve physical properties of remediated soil antagonistic micronutrients with similar ionic radius. The for vegetable production the buckwheat was sown as the first smallest difference in Cd uptake, 33%, was measured in roots of crop. Buckwheat is often used for green manuring. It has carrots grown on remediated soils, the highest reduction, 90.8 branched root system that reaches deep into the soil and improves and 91.4% was in the second cut of radicchio and leek. soil aggregation through extensive network of fine roots. The European Union has defined maximum levels of Pb and The future of ReSoil, as of any other technological eco- Cd to be found in vegetables. To facilitate comparison with EU innovation, relies on its social acceptance. Local population was guidance values the vegetable samples were analyzed for toxic therefore invited to select the final assortment of produces. All metals also on a fresh weight basis (Figure 3). Grown on original plants grown on original and remediated soil reached the mature soil all vegetables exceeded stipulated limits for Pb concentration phase without difficulties or visible deficiencies. We observed no in their edible parts. In remediated soil only carrot exceeded limit statistically significant differences in plant biomass, and no for Pb. Remediation was less efficient in mitigation of Cd chlorosis indicating lack of micronutrients (Figure 2). hazard; concentration of Cd in spinach, second cut of radicchio, The metal plant uptake is known to vary strongly across plant and carrot exceeded the allowed values. In accordance to our species and growing stages. Soil washing with ReSoil the most results spinach and carrots are often identified as the major Cd consistently prevented accumulation of Pb in edible parts of accumulators. Substantial genotypic variation, however, exists vegetables. The Pb uptake was reduced from 76% in garlic to among species and cultivars [5]. For example Kugonič et al. [6] 95% in kohlrabi. The uptake of essential element Zn was reported that carrot grown in Zasavje region in Slovenia in distributed more uniformly, with differences of only 14% unpolluted calcareous soil (similar to soil used in our study) with between lettuce grown remediated and original soil, and the Cd concentration ranging from 0.13 - 0.69 mg kg-1 accumulated highest reduction of 76% in the first cut of radicchio. Cadmium 0.3 - 0.8 mg kg-1 of Cd in roots, which is higher than stipulated (and Pb) is believed to be non-essential element. Nevertheless, by EU, and higher than in carrot grown on remediated soils in plants often adsorb Cd instead of Zn, which is biologically our study. Figure 1: Demonstrational soil-washing plant (TRL 7) with ReSoil technology in the city of Prevalje, Slovenia. The plant with capacity of 1.5 tons of soil per batch is operated by Envit Ltd. The plant construction was supported by the EU project LIFE12 ENV/SI/000969 (http://www.envit.si/). 405 Figure 2: Vegetable garden with remediated (raised beds 2, 4, 5, 7, 8, 9) and original (beds 1, 3, 6) soil. The growth of leek, lettuce and carrots (4. Rotation, Maj 20, 2019) is depicted. Figure 2: Concentration of Pb and Cd in edible parts of vegetables (wet biomass) grown on original soil (black circles) and remediated soil (blue circles). Horizontal lines depict maximum permissible levels of Pb and Cd in vegetables as stipulated by European Union legislature. Data are given as average of 3 samples with standard error. ACKNOWLEDGMENTS This work was supported by the EU project LIFE12 REFERENCES ENV/SI/000969 and by the Slovenian Research Agency under [1] Lestan, D., 2017. Novel chelant-based washing method for soil Grants J4-8219 and P4-0085. contaminated with Pb and other metals: A pilot-scale study. L. Degrad. Dev. 28, 2585-2595. 406 [2] Lestan, D., 2019. Curbing toxic emissions from remediated substrate. EP 3 492 187 A1 [3] Lestan, D., Finzgar, N., Gerl, M., Gluhar, S., Lakovic, G., Hamiti, B., [6] Kugonič, N., Grčman H., 1999. The Accumulation of Cadmium, Lead and 2018. Method for soil and sediment remediation. EP 3 153 246 B1. Zinc by different Vegetables from Zasavje (Slovenia). Phyton (Austria). [4] Gluhar, S., Jež, E., Lestan, D., 2019. The use of zero-valent Fe for curbing Phyton 39, 161-165. toxic emissions after EDTA-based washing of Pb, Zn and Cd contaminated calcareous and acidic soil. Chemosphere. 215, [5] Yang, J., Guo, H., Ma, Y., Wang, L., Wei, D., Hua, L., 2010: Genotypic variations in the accumulation of Cd exhibited by different vegetables. J. Environ. Sci., 22, 1246–1252. 407 Lahko migracije zaustavijo pritisk staranja prebivalstva Slovenije na ekonomsko vzdržnost? Can migration stop the pressure of population ageing in Slovenia on economic sustainability? Jože Sambt Tanja Istenič Ekonomska fakulteta, Univerza v Ljubljani Ekonomska fakulteta, Univerza v Ljubljani Kardeljeva ploščad 17, 1000 Ljubljana, Slovenija Kardeljeva ploščad 17, 1000 Ljubljana, Slovenija Tel: +386 1 5892515; fax: +386 1 5892698 Tel: +386 1 5892778; fax: +386 1 5892698 e-pošta: joze.sambt@ef.uni-lj.si e-pošta: tanja.istenic@ef.uni-lj.si indicator below an arbitrarily chosen level. It turns out that keeping POVZETEK this indicator on the current level would require unrealistically high Prebivalstvo Slovenije se bo v prihodnjih treh oz. štirih desetletjih net migration. Thus, in the future we will be able to use migration to hitro staralo. Najnovejše Eurostatove demografske projekcije somehow alleviate the demographic pressure on economic kažejo, da naj bi se delež starih 65 let in več povečal z 20,2 % v letu sustainability, but we can not expect to solve this problem. 2020 na okrog 31 % v letu 2050. Ekonomsko gledano, je še bolj Therefore, the solutions are expected to go in the direction of pomembno gibanje razmerja med starimi 65+ in prebivalci v delovni adjusting the systems in line with the changed demographic starosti 20-64 let. Prva starostna skupina namreč v glavnem circumstances. predstavlja ekonomsko odvisne prebivalce, druga skupina pa odvisne prebivalce ekonomsko vzdržuje. Hkrati s povečevanjem deleža starih 65+ se bo namreč približno v enakem obsegu KEYWORDS zmanjševal delež tistih v delovni starosti, zato se bo to razmerje, Population ageing, migrations, economic dependency, projections. imenovano »koeficient starostne odvisnosti starih« še posebej zaostrovalo. V članku pokažemo, kakšne bi morale biti neto migracije, da se ta kazalnik ne bi povečal čez določeno mejo. Izkaže se, da bi bile potrebne za ohranjanje tega kazalnika na sedanji ravni 1 UVOD povsem nerealistično visoke neto migracije. Torej bomo lahko v Spomladi 2020 je Eurostat objavil nove demografske projekcije prihodnje z migracijami zgolj nekoliko blažili demografski pritisk prebivalstva z imenom EUROPOP2019 [1]. Gre za neobičajno na ekonomsko vzdržnost, rešitve problema pa na ta način ne moremo odločitev, saj je bila ustaljena praksa, da jih pripravi na vsaka tri leta pričakovati. Tako bodo morale biti rešitve usmerjene predvsem v in prejšnje je po tem vzoru pripravil pred enim letom, torej leta 2019 ekonomsko prilagajanje sistemov spremenjenim demografskim z imenom EUROPOP2018 [2]. Eurostat namreč projekcijam razmeram. dodeljuje imena po letu, v katerem začne z izdelavo projekcij, hkrati pa iz tega leta tudi vzame dejansko število prebivalstva po starosti in KLJUCNE BESEDE spolu in na njega aplicira predpostavke o rodnosti, umrljivosti in staranje prebivalstva, migracije, ekonomska odvisnost, projekcije. migracijah, da dobi rezultate za vsa ostala leta projekcij. Glede umljivosti, ki jo običajno sintetično izražamo z življenjskim pričakovanjem ob rojstvu, so predpostavke v EUROPOP2019 skoraj iste kot v EUROPOP2018. Življenjsko ABSTRACT pričakovanje so rahlo popravili navzgor – za moške naj bi se od leta In the next three to four decades the population of Slovenia will 2019 do leta 2060 povišalo z 78,7 let na 84,6 let (prej 84,4 let), za rapidly age. The latest Eurostat population projections show that the ženske pa z 84,5 let na 89,4 let (prej 89,1 let). Rodnost so tokrat share of people aged 65 and over will increase from 20.2% in year popravili navzdol za nekaj manj kot 0,1 otroka na ženko, izraženo s 2020 to around 31% in 2050. From economic point of view, it is kazalnikom »stopnja celotne rodnosti«. Porast naj bi bil z 1,55 v letu even more important, how the ratio between individuals 65+ and 2019 na 1,67 v letu 2060 (prej 1,73). Največje razlike pa so pri (neto) working-age population develops. The former age group namely migracijah. Kot prikazano v Sliki 1, so v EUROPOP2018 namreč represent economically dependent individuals, whereas the second predpostavljali, da se bodo v obdobju do leta 2045 neto migracije group supports those dependent individuals. With the increasing gibale na ravni okrog štiri tisoč neto priseljenih na leto, nakar pa naj share of individuals 65+ the share of working-age population will bi se postopno znižale na okrog tri tisoč neto priseljenih na leto. Proti decrease accordingly, therefore this ratio, called “old age letu 2060 pa naj bi se še nadalje znižale na okrog dva in pol tisoč. dependency ratio” will aggravate even more. In this article we Medtem smo bili v zadnjih dveh letih v Sloveniji priča izjemno present how large the annual net migration should be to keep this visokemu neto priseljevanju v Slovenijo, in sicer 14.928 neto 408 priseljenih v letu 2018 in 16.213 v letu 2019 [3]. Povprečje za 2 METODOLOGIJA IN PODATKI obdobje 1991 do 2019 znaša namreč samo štiri tisoč neto priseljenih Pri analizi bomo izhajali iz najnovejših demografskih projekcij na leto, s tem, da lahko vrednosti močno porastejo v času Eurostata EUROPOP2019, ki so bile objavljene spomladi 2020. konjunkture. Tako so tudi v obdobju 2007-2009 neto selitve znašale Objavljene rezultate najprej reproduciramo z modelom, ki aplicira v povprečju 11,5 tisoč na leto, medtem ko so v obdobju po nastopu posamezne predpostavke glede rodnosti, umrljivosti in (neto) krize (2010-2017) znašale samo 624 oseb v povprečju na leto [3]. migracij na izhodiščno stanje prebivalstva po spolu in starosti iz V zadnjih projekcijah tako Eurostat predpostavlja postopno začetka leta 2019. Čeprav je v splošnem pristop pri vseh zniževanje iz teh visokih ravni v letu 2018 in 2019 na okrog štiri metodoloških izvedbah analitičnih demografskih projekcij zelo tisoč oseb na leto. Nato naj bi bile do leta 2045 neto selitve nekoliko podoben, vendarle obstajajo določene razlike glede posameznih višje kot so predpostavljali v EUROPOP2018 [2], predvsem pa naj tehničnih rešitev in uporabljenih predpostavk – npr. v najvišjem in po tem letu neto selitve ne bi začele upadati, temveč naj bi se začele najnižjem starostnem razredu. Uporabljene metodologije Eurostat ne povečevati, tako da bi v preostanku obdobja projekcij znašale okrog razkriva, zato reprodukcija rezultatov do zadnjega prebivalca pet tisoč neto priseljenih letno (Slika 1). natančno ni mogoča. Vendar pa so razlike med našimi in njihovimi rezultati zanemarljivo majhne (razlika v celotnem številu prebivalstva je največ 1258 oseb oz. 0,6 promila vseh prebivalcev, 12000 kar smatramo kot zanemarljivo). 10000 V različnih scenarijih demografskih projekcij, ki jih izdelamo, ihn EUROPOP2019 ohranjamo predpostavke glede rodnosti in umrljivosti povsem enake 8000 lje kot so v osnovni EUROPOP2019 varianti. Spreminjamo samo EUROPOP2018 rise p migracije, da dosežemo zastavljeni cilj. Pri tem spreminjamo samo 6000 toe raven migracij, medtem ko ohranjamo relativno porazdelitev nlo 4000 migrantov po starosti in spolu takšno, kot je v posameznih letih vieŠt projekcij v EUROPOP2019. Kot vidimo v Sliki 2, Eurostat 2000 predpostavlja, da se priseljujejo pretežno mlade osebe. Predpostavka seveda sloni na dejanskih podatkih o starostni strukturi migrantov. 0 2020 2025 2030 2035 2040 2045 2050 2055 2060 Eurostat podobno porazdelitev po starosti predpostavlja tudi v Leto preostalih letih projekcij, hkrati pa postopoma nekoliko zmanjšuje Slika 1: Predpostavke glede gibanja neto migracij v zadnjih razmerje med spoloma. V letu 2019, ki ga prikazujemo v Sliki 2, treh Eurostatovih demografskih projekcijah (vir: Eurostat, predstavljajo moški 78 % vseh migrantov, do leta 2060 pa se njihov 2019 & Eurostat, 2020) delež zniža na 60 %. Ob navedenih predpostavkah je v projekcijah EUROPOP2019 število prebivalcev v obdobju do leta 2060 za okrog 25 tisoč višje 500 kot v EUROPOP2018, saj višje neto migracije (še posebej v začetnih nekaj letih) več kot kompenzirajo učinek nekoliko nižje ij 400 predpostavljene rodnosti. ac Skupaj igr V nadaljevanju besedila nas bo bolj kot gibanje celotnega števila m 300 Moški to prebivalcev zanimala starostna struktura prebivalstva. Osredotočili e Ženske n se bomo na analizo »koeficienta starostne odvisnosti starih« (v 200 vilo nadaljevanju KSOS), ki je opredeljen kot razmerje med številom Šte prebivalstva v starosti 65+ in številom prebivalstva v delovni starosti 100 (20-64 let). 0 Najprej bomo prikazali naraščanje KSOS v bazni varianti 0 10 20 30 40 50 60 70 80 90 100+ EUROPOP2019, nato pa bomo z migracijami preprečevali porast -100 tega kazalnika nad izbrano vrednost. Zanimale nas bodo neto Starost migracije, ki bodo za to potrebne. Blaženje staranja prebivalstva bi se po predpostavki lahko dosegalo tudi z višjo rodnostjo, vendar se Slika 2: Porazdelitev neto migracij v letu 2019 po starosti in s tem dejavnikom dinamike prebivalstva v tem besedilu ne bomo spolu (vir: Eurostat, 2020) ukvarjali. Vplivanje na rodnost z ukrepi demografske politike je Ob prikazani starostni porazdelitvi migranti prispevajo k kompleksno in kontroverzno vprašanje, hkrati pa je domet tega pomlajevanju prebivalstva neposredno, hkrati pa priseljene ženske ukrepa na koeficient starostne odvisnosti starih v prihodnjih treh do po prihodu v državo realizirajo še določeno število rojstev, če se štirih desetletjih zelo omejen. Prvih dvajset let namreč višja rodnost priselijo v starosti, ko so še v rodni dobi ali pred njo. Predpostavlja nima nobenega pozitivnega vpliva na KSOS, saj prebivalstvo 0-19 se namreč, da priseljene ženske prevzamejo vzorce rodnosti od ne vpliva na ta kazalnik. Po drugi strani pa bi tudi v preostalih obstoječih prebivalk Slovenije. Vendar pa se sčasoma tudi migranti dvajsetih letih projekcij (2040-2060) bil vpliv višje rodnosti na postarajo in vstopajo v starostni razred 65+. Zaradi tega se začne KSOS omejen, saj ne bi bilo realistično predpostavljati takojšnjega vpliv migrantov na zaviranje staranja prebivalstva čez čas skoka na visoke vrednosti. zmanjševati. 409 V Sliki 3 prikazujemo gibanje kazalnika »koeficient starostne Slika 4: Dejansko gibanje neto migracij v odboju 1991-2019, odvisnosti starih« (KSOS) v skladu z osnovno varianto predpostavljeno gibanje neto migracij po osnovni varianti demografskih projekcij Eurostata. Hkrati nazorno predstavljamo, na EUROPOP2019 in potrebna raven migracij po zastavljenih katere tri ravni bomo v posameznem izmed treh scenarijev omejevali treh scenarijih (vir: Eurostat, 2020) vrednosti KSOS. Razberemo lahko, da bi pri scenariju omejevanja KSOS na največ 50 morale znašati neto migracije okrog leta 2040 približno 25 70 tisoč na leto, da bi preprečili porast KSOS nad 50. To je znatno več 60 ih kot so znašale najvišje vrednosti neto migracij v preteklosti. Če bi star 50 pričeli z višjimi migracijami že nekoliko prej, bi bile dovolj že sti nekoliko nižje vrednosti, v vsakem primeru pa se postavlja 40 visno vprašanje, ali bi bila družba te kontinuirano visoke migracije od ) e 30 sposobna sprejeti brez večjih družbenih nemirov in močne krepitve SOS(K nacionalističnih strank. Navedeno se namreč pogosto pojavi kot ostn 20 Omejevanje na 33,7 Omejevanje na 40 problem pri (pre)visokih migracijah, kar se je pokazalo tudi npr. ob star 10 Omejevanje na 50 masovnih migracijah iz Afrike v Evropo v zadnjih nekaj letih. Osnovna varianta ficient Drugi scenarij predpostavlja omejevanje KSOS na največ 40, oe 0 K kjer rezultati kažejo, da bi bile potrebne zelo visoke migracije že v 2020 2025 2030 2035 2040 2045 2050 2055 2060 Leto letu 2027 in to kar več kot 30 tisoč za obdobje nekaj let, nato pa med 20 in 25 tisoč letno. Najbolj ekstremen pa je scenarij, v katerem bi Slika 3: Gibanje koeficienta starostne odvisnosti starih po KSOS ohranjali na ravni iz leta 2020. To bi zahtevalo takojšnje in osnovni varianti EUROPOP2019 in zastavljenih treh scenarijih povsem nerealistično visoke neto migracije v višini skoraj 60 tisoč Pri prvem scenariju postavimo zgornjo mejo dovoljenega oseb, v preostanku obdobja projekcij pa med 30 in 50 tisoč neto povišanja KSOS na 50. Ko razmerje med starimi 65+ na 100 priseljenih vsako leto. Prikazane vrednosti moramo jemati zgolj kot prebivalcev v delovni starosti doseže vrednost 50, začnemo torej matematično vajo in kot kazalnik nerealističnosti, da bi lahko ustrezno zviševati neto migracije, da KSOS te vrednosti ne preseže. prihajajoče staranje prebivalstva z migracijami preprečili. Ukrepati začnemo v letu 2040, ko bi vrednost KSOS sicer presegla Ti rezultati bi tudi povsem spremenili število prebivalcev 50. V drugem scenariju je ta meja postavljena na 40, kar pomeni, da Slovenije. V Sliki 5 prikazujemo število prebivalcev Slovenije po začnemo migracije zviševati že v letu 2027. V tretjem scenariju pa teh treh scenarijih. preverimo, koliko bi morale znašati neto migracije, da bi ohranjali KSOS na ravni iz leta 2020, torej na vrednosti 33,7. To pomeni, da začnemo migracije zviševati že v letu 2021. 4,0 3,5 i) 3,0 3 REZULTATI ilijon 2,5 V Sliki 4 prikazujemo potrebne neto migracije po vseh treh opisanih v (mce scenarijih, hkrati pa še za prej prikazano osnovno varianto 2,0 ivalb Eurostatovih projekcij EUROPOP2019. Prikazujemo tudi dejansko re 1,5 p gibanje neto migracij v preteklosti – od leta 1991, ko je Slovenija Omejevanje na 33,7 vilo 1,0 Omejevanje na 40 postala samostojna država, pa do leta 2019. Na ta način postavimo Šte Omejevanje na 50 dobljene rezultate v kontekst velikosti neto migracij iz preteklosti. 0,5 Osnovna varianta 0,0 2020 2025 2030 2035 2040 2045 2050 2055 2060 Leto 60 Omejevanje na 33,7 Omejevanje na 40 ) 50 Slika 5: Gibanje števila prebivalcev Slovenije po osnovni Omejevanje na 50 varianti Eurostatovih EUROPOP2019 projekcij in po isoč Osnovna varianta 40 (v t zastavljenih treh scenarijih. ih jen 30 Vidimo, da bi se ob teh izjemno visokih migracijah število risel prebivalstva Slovenije močno povečalo, še posebej v scenariju p 20 to ohranjanja KSOS na ravni iz leta 2020. V tem primeru bi namreč e n prebivalstvo Slovenije do leta 2060 naraslo na več kot 3,5 milijona 10 vilo prebivalcev. Te izjemno visoke vrednosti so samo še dodatna Šte 0 potrditev, da so tako visoke neto migracije povsem nerealistične. 1991 1994 1997 2000 2003 2006 2009 2012 2015 2018 2021 2024 2027 2030 2033 2036 2039 2042 2045 2048 2051 2054 2057 2060 Prikazujemo jih zgolj v potrditev, da z migracijami prihodnjega -10 Leto hitrega staranja prebivalstva in s tem močnega demografskega pritiska na ekonomsko vzdržnost ne bo mogoče preprečiti. 410 4 SKLEP V prihodnje bomo v Sloveniji in razvitih državah priča hitremu staranju prebivalstva, kar bo imelo močan demografski pritisk na ekonomsko vzdržnost. V besedilu smo preverili, ali bi lahko v prihodnjih štirih desetletjih z neto migracijami zaustaviti naraščanje razmerja med starimi 65 in več let ter prebivalci v delovni starosti. To razmerje se imenuje »koeficient starostne odvisnosti starih«. Ob predpostavljenih neto migracijah Eurostata v višini štiri do pet tisoč oseb letno bi se njegova vrednost povzpela z 33,7 v letu 2020 na 61,8 v letu 2060. V treh scenarijih smo naraščanje tega kazalnika omejili na vrednosti 50, 40 in pa ravni iz leta 2020, to je 33,7. Rezultati pokažejo, da bi že ob prvem scenariju morale biti neto migracije zelo visoke. V zadnjem scenariju pa bi morale biti povsem nerealistično visoke in sicer nekje med 30 in 60 tisoč neto migracijami na leto. Hkrati bi to pomenilo, da bi se do leta 2060 število prebivalcev povečalo na 3,5 milijona. Gre za povsem nerealistično raven migracij, ki kažejo, da z migracijami staranja prebivalstva ne bomo mogli zaustaviti. LITERATURA IN VIRI [1] Eurostat, “Population projections EUROPOP2019,” 2020. https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=proj_19np&lang=e n (accessed Aug. 20, 2020). [2] Eurostat, “Population projections EUROPOP2018,” 2019. https://ec.europa.eu/eurostat/data/database?node_code=proj (accessed Sep. 19, 2019). [3] Statistični urad RS, “Meddržavne selitve po spolu, Slovenija, letno,” Podatkovni portal SI-STAT/Začetna stran/Demografsko in socialno področje/Prebivalstvo/Selitve/Meddržavne selitve/Meddržavne selitve po spolu, Slovenija, letno, 2020. https://pxweb.stat.si/SiStatDb/pxweb/sl/10_Dem_soc/10_Dem_soc__05_preb ivalstvo__40_selitve__05_05N10_meddrzavne/05N1002S.px/. [4] Eurostat, “Population projections 2015 at national level,” 2016. . 411 Vetrne elektrarne niso za Slovenijo Wind turbines not for Slovenia mag. Tomaž Ogrin dr. Ferdinand Deželak Odsek za anorgansko kemijo in Slovensko društvo za akustiko tehnologijo Ljubljana, Slovenija Inštitut Jožef Stefan ferdo.dezelak86@gmail.com Ljubljana, Slovenija tomaz.ogrin@ijs.si javnosti v Zakonu o varstvu okolja (ZVO-1), da ga argumentirano uporabi. Vetrne elektrarne (VE) v Sloveniji so taka zabloda. K sreči imamo šele dve, zato je še čas, da se POVZETEK izognemo razvrednotenju slovenskega višavja, gozdov, krajine, V prispevku je kritično obdelana problematika vetrnih elektrarn uničevanja turizma ter zdravja prebivalcev s posebnim hrupom v (VE), predvsem iz vidika specifičnega hrupa, ki škoduje zdravju. nizkofrekvenčnem območju (pod 200 Hz) in z infrazvokom (pod Opozorjeno je, z utemeljitvami, na odsotnost predpisov za 20 Hz). merjenje hrupa VE. Zdravju škodljiv hrup VE je bil ugotovljen Tudi v znanosti je argumentiran kritičen odnos osnova za že v 80-tih letih prejšnjega stoletja. Kljub temu predpisov še napredek. Le politika ga ne sprejema. nimamo, ker jih politika zaradi pritiska proizvajalcev VE in Pozno lekcijo na področju vetrnih elektrarn in njihovega investitorjev v VE (korupcijsko tveganje) noče sprejeti, kljub političnega ' Energiewende' v Nemčiji doživljamo v sedanjiku. O tem obstaja več strokovnih študij, na primer: dr. Fritz zahtevam nevladnih organizacij in civilnih iniciativ. Slovenske Vahrenholt: Germany's Energiewende, A Disaster in the making izkušnje s tem hrupom so podobne svetovnim, zato ni nobenega (2017) [3]. Nedavno je bil nemški elektroenergetski sistem pred razloga za ignoriranje zahtev po ustreznih predpisih. Na tem razpadom [4]. Ni bilo vetra. Izpadlo jim je za 20.000 MW vetrnih področju imamo odsotnost prava, ljudje in narava niso pravno elektrarn. S svojo rezervo je pomagala reševati nemški elektro zaščiteni. sistem tudi Slovenija. Vetra pa ni bilo kaj več niti v sosednjih državah: Avstriji, Franciji, Danski in Veliki Britaniji. Nemčija je KLJUČNE BESEDE bila zaradi pomanjkanja vetra že večkrat na robu zloma. Poljska in Češka pa sta se zavarovali pred nenadnimi sunki vetrne Ključne besede: vetrne elektrarne, nizkofrekvenčni hrup, elektrike iz Nemčije s prečnimi transformatorji. Kaj gre narobe? infrazvok, predpisi, zakoni Politika ignorira naravno zakonitost, da s seštevanjem naključnih, kaotičnih ABSTRACT pojavov kot so lokalni vetrovi, ne moremo dobiti stalnega vira torej stacionarnega stanja. Z vetrnimi elektrarnami Problems with wind turbines (WT) is critically described. ne moremo zamenjati jedrske elektrarne (24/7 vir) pa obe ne Specifically, from the point of view of noise which is harmful to spuščata CO2, če že gre za ta cilj, da izjemno velike razlike v health. There are no rules to measure and assess this noise. That gostoti energije niti ne omenjamo. WT noise is harmful to health was confirmed already in eighties. Politicians ignore demands of NGOs and civil initiatives to set 1.1 Kakšno korist bi imeli od vetrnih elektrarn up the proper rules. It could be that corruption risks are on work po hribih? pushed by investors and producers of WT. Slovenian experience with the WT noise is similar to other countries in the world. Poglejmo izkoristek obeh vetrnic na Primorskem (Tabela 1). There is an absence of regulation in this area in Slovenia and Borzenov Center za podpore spremlja tudi učinkovitost obeh people are unprotected. vetrnic v Sloveniji, ki jim plačuje elektriko. VE 15 je oznaka za VE Dolenja vas, v KS Senožeče, občina Divača z nazivno KEYWORDS (teoretično pri nas) močjo 2,3 MW, višina stebra 90 m, ki obratuje večinoma z močjo do 1 MW, saj tudi na Primorskem ni Keywords: wind turbines, low frequency noise, infrasound, stalnih močnih vetrov. Druga VE je v Razdrtem, z 1 MW nazivne rules, law moči, višina stebra 55 m. Spodnja preglednica razgali izredno nizek izkoristek in količine elektrike, ki jih mimogrede lahko privarčujemo za bistveno manjši denar ali pa ta denar raje 1. UVOD vložimo v zmanjšanje uporabe kurilnega olja za gretje, kjer lahko neposredno izračunamo zmanjšanje CO2. Izkoristek v prvih 8. Brez kritičnega odnosa do razvojnih usmeritev ni napredka. mesecih leta 2019 je bil za VE15 16,73 %, za VE Razdrto pa Razvoj je sprememba s časom, lahko je pozitiven, lahko pa tudi 14,84 %. negativen. Pretekle zablode so obdelane v publikaciji EEA (2001) (European Environmental Agency – Evropska agencija za Tabela 1: Izkoristki obeh večjih vetrnih elektrarn v okolje): Pozne lekcije iz zgodnjih svaril: previdnostno načelo Sloveniji 1896-2000 [1]. Leta 2013 je izšel drugi zvezek (Vol. II): Late lessons from early warnings: science, precaution, innovation [2]. Slovenskega prevoda še ni. Previdnostno načelo je na razpolago 412 Na zgornje vprašanje so dolgoročno odgovorili na Južnem Nad Dolenjo vasjo v KS Senožeče, občina Divača, 850 m od Tirolskem, tudi alpski deželi. Energetski razvoj, ki ne bi prvih hiš, obratuje vetrna elektrarna z nazivno (teoretično) močjo škodoval krajini, turizmu in prebivalcem tako 2,3 megavata (MW), ki običajno dela z močjo 1 MW. Prebivalci , kot vetrne so bili sprva naklonjeni njeni postavitvi, že po dobrem letu elektrarne, so opredelili v dokumentu Energetski model – Južna obratovanja vetrnice pa so bili odločno proti. Tudi z Tirolska 2050 (Energy model-South Tyrol 2050) [5]. V njem ne referendumom leta 2014 v KS Senožeče, katerega rezultat je tudi predvidevajo vetrnih elektrarn, sončne elektrarne pa umeščajo na občinski svet občine Divača sprejel. zgradbe, razen kulturne dediščine, nikakor pa ne na zemljišča. Brutalno razvrednotenje gorske krajine zaradi načrtov o 19 28. februarja 2014 pa so poslali ministru za infrastrukturo in vetrnih elektrarnah na grebenu Sattelberg, Italija, v bližini prostor Samu Omerzelu pismo, v katerem opisujejo tudi vpliv prelaza Brenner in meje z Južno Tirolsko, pa je leta 2012 sodišče tega hrupa na spanje: preprečilo. Med argumenti je bila Alpska konvencija in tudi '' Ko so vremenski pogoji za delovanje vetrnice ugodni, človek predpisi o zaščiti hribovitega sveta Južne Tirolske nad 1600 metri težko normalno funkcionira. Ponoči, ko bi človek potreboval mir [6]. in tišino, da se naspi in odpočije za naslednji delovni dan, je to Pri nas, na primer, krajine kot pomembnega turističnega žal nemogoče. Če nam že uspe nekako zaspati, nas zbudi sredi produkta sploh ne priznamo. Kar velja seveda za primitivno noči in od spanja se lahko poslovimo. Kako je drugi dan, pa si politiko prostora, ki se boji vsakršnih zaščit, saj je brez selektivne lahko predstavljate - kot po prekrokani noči. In to je dan na dan, strategije razvoja Slovenije. noč za nočjo. In tako nas je situacija privedla do tega, da smo začeli preko spleta "izobraževanje" o vetrnicah, in med drugim ugotovili, da poleg fascinantnega slišnega hrupa, oddaja še nizkofrekvenčne zvoke, ki so zelo nevarni za zdravje ljudi – pa 2. HRUP VETRNIH ELEKTRARN ŠKODUJE nam tudi tega ni nihče predstavil!'' ZDRAVJU Od takrat se ni nič spremenilo. Zasebni lastnik vetrnice je niti V tem krajšem prispevku se ne moremo posvetiti vsej ponoči noče ustaviti. Pomembnejši mu je dobiček. Prijave problematiki vetrnih elektrarn. Posebno pozornost pa moramo inšpektorjem niso dale rezultatov, saj so izjavljali, da za hrup nameniti hrupu VE, ker je pri nas popolnoma ignoriran s strani vetrnih elektrarn ni predpisov. In teh še danes ni. Politika v politike, ki vsiljuje VE po Sloveniji, ne glede na to, da hrup VE navezavi s kapitalom jih noče sprejeti, kljub mnogim protestom dokazano škoduje zdravju prebivalcev. in predlogom nevladnih organizacij in civilnih iniciativ. 2.1 Domače izkušnje 2.2. V čem je posebnost hrupa vetrnih elektrarn? Izkušnje z VE Dolenja vas v KS Senožeče, občina Divača kažejo, da hrup VE močno zniža kakovost bivanja in ovira spanje. Pri načrtovanju VE po Z izrazom hrup označujemo neželeno zvočno valovanje ali Sloveniji na prebivalce nismo mislili. Predpisov za merjenje specifičnega hrupa VE nimamo. vibracije (lokalne spremembe pritiska) zraka, ki zadenejo ves naš Inšpekcije ne morejo ukrepati, da bi vsaj ponoči VE ustavili. organizem, ne le slušni del. Večinoma ga slišimo (preko bobniča se prenaša v notranjost ušesa), obstajajo pa tudi vibracije, ki jih le čutimo, slišimo pa ne. In vetrne elektrarne oddajajo zdravju 413 škodljiv hrup ravno v tistem delu spektra, ki ga slabše slišimo raziskovalnih inštitucij in NASA (tudi že 1982). Dr. Kelley je v (nizkofrekvenčni hrup, pod 200 Hz) ali pa sploh ne (infrazvok, več člankih (npr:1985) [7] podrobno predstavil meritve zunaj in pod 20 Hz). Vibriranje zraka (spremembe tlaka) izražamo s v stanovanjskih prostorih prebivalcev in dokazal škodljiv vpliv številom nihanj vibracij na sekundo, ki ga imenujemo frekvenca, hrupa vetrnih elektrarn na človeka. Modernejše turbine večjih ime za enoto pa je hertz (Hz). moči in višin oddajajo še bolj zdravju škodljiv hrup kot vetrne elektrarne starejšega tipa. Merilo za vpliv vibracij na naš organizem pa ni zgolj slišnost, Že leta 1979 so pri dvokrilni vetrni elektrarni (2 MW MOD-1) ampak še bolj vibracije, ki jih posamezni deli organizma dobili vrsto pritožb zaradi hrupa in vibracij v razdalji do 3 km. občutijo. To, da nekih vibracij ne slišimo, še ni dokaz, da jih ni. Prav tako so ugotovili odboje in s tem ojačanje vibracij v Tovrstne vibracije niso lastnost le vetrnih elektrarn, ampak se notranjih prostorih (resonanca). Vse to imamo še danes, s ljudje pritožujejo tudi v mestih in ob določenih industrijskih pojavom višjih in močnejših vetrnih elektrarn še toliko bolj. Že obratih in letališčih. Vzrok so slabo nameščene velike klimatske takratna vetrna elektrarna je oddajala najbolj škodljiv naprave na strehah ali določeni veliki vrteči stroji i pulzni , gradbena hrup. Na spodnji sliki Diagram 1 [7] je prikaz tega hrupa, kjer mehanizacija in podobno. Hrup vetrnih elektrarn pa ima še eno, za zdravje zelo škodljivo se vidi, da pulzi dosežejo nivo preko 100 dB. Zato so pulzi tako posebnost, ki ga bistveno loči od vseh drugih hrupov. Vetrna nevarni. Na sliki so štirje pulzi, ki so nastali, ko je krak vetrnice elektrarna oddaja zračne vibracije v ritmu vrtenja krakov vetrnice šel mimo stebra. Njihov učinek na organizem je podoben in sicer na način pulzov, sunkov. Vsakič ko gre krak mimo kapljanju vode na čelo, na primer. Koliko časa ga lahko stebra vetrne elektrarne in tudi ko zareže zrak zaradi sile vetra, prenašamo? Kaj pa je ena kapljica za drugo, bi pomislil. odda pulzno vibracijo, ki nas zadene. Ugotovljeno je, da se organizem sčasoma pred pogostimi pulzi brani s prekomerno tvorbo kolagena, to pa je po drugi strani Strokovno tovrstne pulzne vibracije imenujemo amplitudna povezano z odebelitvami žil, povrhnjice srca, spremembami v modulacija hrupa VE, ki je torej glavni vzrok za onesnaževanje notranjem ušesu in drugimi spremembami, ki vodijo v resna okolja s hrupom. Pri vrtenju krakov VE se namreč ustvarja obolenja. periodični amplitudno moduliran signal, ki ne odstopa bistveno od sinusne oblike. Amplitudna modulacija VE ima torej najpomembnejši vpliv in s tem so povezane tudi pritožbe izpostavljenih prebivalcev po vsem svetu. Znanstvene raziskave kažejo, da kar 85% izpostavljenih prebivalcev jasno zaznava hrup VE že pri ravneh 35 dBA . Prav tako je bilo ugotovljeno, da se počutje približno 30% vseh prebivalcev močno poslabša, kadar raven hrupa prometnih virov presega 70 dB(A), medtem ko se enakemu odstotku prebivalcev počutje močno poslabša zaradi hrupa VE, katerega raven dosega »komaj« 40 dBA. Hrup VE je namreč, za razliko od velike večine drugih hrupnih virov, tudi amplitudno moduliran in zaradi tega še posebej škodljiv. Takšna vrsta hrupa je invazivna in jo hrup ozadja zaradi prisotnosti drugih virov, lociranih blizu tal, težje zamaskira. Kot pove že samo ime, se pri amplitudno moduliranem hrupu njegova amplituda spreminja s časom, običajno periodično, kot na primer pri sirenah vozil na nujnih vožnjah. Takšen utripajoči hrup močno pritegne našo pozornost, saj izstopa iz ozadja celo v primeru majhnih amplitud oziroma ravni. V praksi nas pogosto opozarja na previdnost oziroma nevarnost, če pa predolgo traja Diagram 1 pa postane nadležen in stresen; pri vdoru v spalnico pa lahko onemogoči miren spanec prizadetim stanovalcem . Več o tem izvemo v predavanju dr. Pereire, ki ga je imela v Za razliko od visokofrekvenčnega zvoka, ki ga zadržijo oziroma Sloveniji v letu 2018 [8] [9]. odbijejo že manjše ovire, sta nizkofrekvenčni in infrazvok Življenjska doba VE je od 20 do 25 let. V Nemčiji na mestu izredno prodorna, poleg tega se na ovirah močno uklanjata in se odsluženih postavijo nove. Torej so cele generacije izpostavljene posledično širita okrog vogalov raznih objektov in celo preko temu škodljivemu hrupu. visokih hribov. Poleg tega pa kot rečeno prodirata tudi v notranjost prostorov, celo tistih, zaščitenih z masivnimi sten Ker se zaradi hrupa vetrnih elektrarn skupaj pojavlja določena ami. vrsta znakov, ki so jih iz vrste primerov po svetu prepoznali Škodljiv vpliv hrupa vetrnih elektrarn na zdravje prebivalcev je vedno v povezavi z vetrnimi elektrarnami, zaradi nizkofrekvenčnega hrupa in infrazvoka (vibracije) kot so: bil dokazan že v 80-tih letih prejšnjega stoletja. Ministrstvo za oviranje spanca, glavoboli, splošno slabo počutje, motenje energijo (DOE) v ZDA je že leta 1985 financiralo raziskave koncentracije na primer pri učenju in delu, hitrejše bitje srca, vpliva hrupa vetrnih elektrarn na ljudi. Vključenih je bilo več naraščanje pritiska, podobni občutki kot pri morski bolezni in še 414 nekaj drugih, se je uveljavil termin sindrom vetrne turbine ali elektrarne (Wind Turbine Syndrome) [10]. Diagram 2 (originalno: The A-contour filters out significantly more bass Wind Turbine Syndrome je tudi naslov knjige zdravnice dr.Nine than the others, and is designed to approximate the ear at around Pierpont (2009). Ameriška akademija znanosti je leta 2007 the 40 phon level. It is very useful for eliminating inaudible low naslovila ameriškemu kongresu vprašanje vpliva hrupa vetrnih frequencies.) [12 ] elektrarn na zdravje. Dr. Pierpontova je s študijskim delom v obliki opisa dejstev na primerih (angleško Case Series), ki je ena od znanstvenih metod dela, na terenu pri prebivalcih (10 družin, 38 posameznikov od otrok do starosti 75 let), ki so se pritoževali zaradi hrupa vetrnih turbin moči od 1,5 MW do 3 MW, želela najti odgovore na to vprašanje. Nekateri prebivalci od obiskanih so se kasneje izselili, drugi so povedali, da ko so šli za nekaj časa daleč stran od svojih domov, so mnogi bolezenski znaki izginili. Po povratku so se spet pojavili. To je samo eden od strokovno proučenih primerov v svetu, ki dokazuje, da hrup VE res škoduje zdravju. 2.3. Zakaj predpisi za merjenje hrupa na delovnem mestu in v okolju ne zadoščajo za Diagram 3 merjenje hrupa vetrnih elektrarn? Vetrne elektrarne pa, kot rečeno, oddajajo škodljiv hrup izven Predpisi določajo merjenje slišnega hrupa oziroma je merjenje dBA in sicer v nizkofrekvenčnem območju in kot infrazvok, ki prilagojeno človeškemu ušesu. Hrup tako merimo z mikrofonom, jih filter A skoraj povsem zanemari. ki ne upošteva manj slišnega ali neslišnega hrupa. To naredijo tako, da ima mikrofon omejitev (filter) za manj slišni oziroma Uredba torej ne zajame hrupa vetrnih elektrarn. neslišni hrup. To je filter A Napačno merjenje hrupa vetrnih elektrarn v dBA je razvidno tudi (tudi utež imenovan). Enote za nivo iz Diagrama 2 za VE Dolenja vas (prikazan na Mednarodnem hrupa so decibeli, kar pišemo kot dB. Ko merimo s filtrom A, označimo enoto z dBA. Tako znanstvenem posvetu: Hrup vetrnih elektrarn in mogoči vplivi na Uredba o mejnih vrednostih življenjsko okolje, Ljubljana, 15. januar 2020, avtor diagrama dr. kazalcev hrupa v okolju predpisuje samo meritve s filtrom A, Ferdinand Deželak) [13], ki primerja merjenje s filtrom A (levo) torej v dBA [11]. in brez filtra (desno). Filter A izloči znatno več nizkih frekvenc kot drugih in je zasnovan tako, da posnema občutljivost ušesa pri glasnosti 40 Iz levega diagrama v Diagramu 2 je razvidno, da filter A vedno fonov. Zato je filter A zelo uporaben za izločanje slabo slišnih in bolj zmanjšuje obstoječi hrup proti nizkim frekvencam. Na neslišnih nizkih frekvenc skrajni levi je oznaka frekvence 12,5 Hz (kar spada v območje : Diagram 3. infrazvoka), kjer ta filter izmeri le še 5 dBA. Pravi hrup (vibracije) vetrne elektrarne dobimo, če filter A odstranimo in na 415 skrajni levi desnega diagrama ravno tako pri frekvenci 12,5 Hz, Energetika ne potrebuje subvencij, ki povzročajo tudi izmerimo dejanski hrup vetrne elektrarne, ki znaša blizu 70 dB. gospodarsko in finančno škodo državi. Ena 3 MW VE stane 3 To pa je izredno velika prekoračitev znosnega hrupa in je povsem milijone evrov. Zato je nujno uvesti poslovne modele brez nesprejemljiva za prebivalce. Posebno se to pozna ponoči, saj ta subvencij. hrup zaradi nizke frekvence (velike valovne dolžine) prodira Ni tudi odgovora na vprašanje, zakaj se proizvajalci VE in skozi zaprta okna. V stanovanjih pa se nizkofrekvenčni hrup, investitorji tako bojijo pravilnih meritev nizkofrekvenčnega katerega valovna dolžina je primerljiva z dimenzijami hrupa in infrazvoka, če pa obenem trdijo, da nimata nobenega posameznih bivalnih prostorov lahko še ojača zaradi resonance vpliva na zdravje ljudi in živali. Obenem zavzeto lobirajo proti (odbitega zvoka med stenami). uvajanju teh meritev, češ, da bodo morali postavljati VE dalj od naselij. Primer je danski proizvajalec VE Vestas s pismom danski Zato bi morali meriti hrup vetrnih elektrarn tudi v stanovanjih. okoljski ministrici leta 2011 [15]. Pa še z dodatno zahtevo, da se merijo pulzi vibracij in ne povprečje kot sedaj predvidevajo neprimerni predpisi. V Razen dobičkov nekaterih na račun degradacije slovenske narave povprečjih se pulzne vibracije zabrišejo, čeprav so glavni vir in zdravja prebivalcev, koristi od VE ni. Več držav je subvencije škodljivih vplivov na zdravje. za VE že pred leti opustilo. Pravno povsem neurejena je tudi razgradnja VE. Torej odpadki iz VE po končani življenjski dobi. Tudi, če hrup vetrnih elektrarn skušajo zatajiti pa je njegov Kraki VE iz kompozita, na primer, se ne reciklirajo ali sežgejo škodljiv vpliv na zdravje tudi že sodno priznan. Imamo torej in jih v Nemčiji kar zakopavajo na velikih površinah. pravno in sodno prakso, ko so se prebivalci zaradi njega pritožili. Tako je leta 2013 vrhovno sodišče Portugalske odločilo, da mora Zanimivo je še, da nihče od odločevalcev ne ve povedati, kateri investitor odstraniti 4 vetrne elektrarne, ki so bile v razdaljah od CO2 zmanjšujeta obe obstoječi VE, niti kateri CO2 naj bi se 322 do 642 metrov od hiš in od 182 do 566 metrov od hlevov zmanjševal zaradi delovanja več VE. Regulacija elektro sistema [14]. Da, tudi živali so ogrožene zaradi tega hrupa kot smo lahko (poraba – proizvodnja elektrike) namreč najlažje poteka s videli v predavanju dr. Pereire [8][9]. pomočjo daljinsko vodenih hidroelektrarn, s cenejšo elektriko od Seveda pa je smotrneje postavljanje vetrnih elektrarn takoj tiste iz VE in ne z nihanjem proizvodnje TEŠ6, na primer. odkloniti, kot se pozneje pravdati, s skladu z načelom previdnosti iz zakona o varstvu okolja. To pa naj bo izziv za drug prispevek še koga iz strokovnih krogov. 3 ZAKLJUČEK REFERENCE Seznanjanje z dogajanjem po svetu na področju hrupa vetrnih elektrarn nam je v veliko pomoč, da smo odločno proti [1] Pozne lekcije iz zgodnjih svaril: previdnostno načelo njihovemu postavljanju po majhni Sloveniji z razpršeno 1896-2000, ARSO, 2004. poselitvijo in čudovito krajino in naravo, ki ju tudi uspešno [2] Late lessons from early warnings: science, precaution, gospodarsko tržimo kot turistični produkt. innovation, EEA, 2013 Dejstvo je tudi, da nobena strojna naprava, postavljena v naravno [3] http:// www.thegwpf.org/content/uploads/2017/01/Vahren ali kmetijsko okolje, ni dosegla tako množičnega in ogorčenega holt-Energiewende.pdf svetovnega vseljudskega odpora kot ravno vetrne elektrarne. [4] https://oe.finance.si/8965937/Zakaj-je-bil-nemski- O tem se lahko prepričamo, če obiščemo na primer strani elektroenergetski-sistem-pred-razpadom-in-kako-je- www.epaw.org (European Platform Against Windfarms) in pomagala-Slovenija??src=ArtTop povezave na severnoameriške in avstralske strani ter na številne [5] http://www.eurac.edu/en/research/technologies/renewabl civilne iniciative. Nastaja občutek, da se o tem ne sme pisati. eenergy/publications/Documents/EnergyModellingSouth Tyrol_final_en.pdf Dokaz za vplivnost hrupa vetrnih elektrarn na prebivalce so tudi [6] https://www.cipra.org/en/news/4757 mednarodna srečanja. Vsaki dve leti, že od leta 2005, poteka [7] https://waubrafoundation.org.au/wp- mednarodna konferenca o hrupu vetrnih turbin (International content/uploads/2013/07/Acoustic-Noise-Associated- Conferences on Wind Turbine Noise). Deveta po vrsti bo with-the-MOD-1-Wind-Turbine.pdf naslednje leto v Dublinu, Irska. [8] Dr. Mariana Alves-Pereira, Letos januarja smo imeli tudi prvo mednarodno konferenco o tem https://www.youtube.com/watch?v=ZXCZ3OyklrE hrupu v Sloveniji v organizaciji Slovenskega društva za akustiko (angleška verzija) [13]. [9] Dr. Mariana Alves-Pereira, Nujno je, da se v Sloveniji problematika vetrnih elektrarn https://www.youtube.com/watch?v=sa2_dqLDmGk strokovno razčisti, saj ni predpisov, kot smo utemeljili, kakor (prevajano, z nagovori) tudi zato, ker prebivalcem grozijo državni in lokalni načrti za [10] Dr. Nina Pierpont, Wind Turbine Syndrome, 2009 postavitev preko 100 vetrnih elektrarn, od tega kar 60 v KS [11] Uradni list RS, št. 43/2018 in št. 59/2019 Senožeče (Slika 1), ki bi dobesedno obkrožile 6 naselij, kar bi bil [12] http://hyperphysics.phy- edinstven primer v svetu. Ali pa, zakaj potrebujejo Dravske astr.gsu.edu/hbase/Sound/acont.html#c2 elektrarne Maribor, ki upravljajo s hidroelektrarnami na Dravi, [13] http://www.drustvo- še nekaj nezanesljivih VE nad 1.200 m na Košenjaku nad akustika.si/files/2020/04/Zbornik_MEDNARODNI- Dravogradom, v pristni naravi in v poseljenem širšem območju, ZNANSTVENI-POSVET-O-HRUPU-VETRNIH- kjer bi za vsako posekali 100 x 60 m (nogometno igrišče) gozda ELEKTRARN-IN-MOZNIH-VPLIVIH-NA- in izravnali razgiban teren, razširili ali zgradili ceste za transport ZIVLJENJSKO-OKOLJE.pdf tovorov izjemnih velikosti (70 metrov) in teže 30 in več ton, ipd. [14] https://www.wind-watch.org/documents/portuguese- [16] (Slika 2) ? supreme-court-orders-4-wind-turbines-removed/ Vetrne elektrarne so spodbujane s takimi ali drugačnimi subvencijami in izprijenimi tržnimi olajšavami. 416 [15] https://stopthesethings.files.wordpress.com/2015/02/eng el-ditlev-vestas-letter-to-danish-environment-minister- in-english.pdf [16] https://www.gov.si/assets/ministrstva/MOP/Dokumenti/ DPN/Javne- razgrnitve/PVE_Ojstrica_povzetek_za_javnost.pdf Slika 1 Slika 2 417 Traffic Simulation Software in the Context of Mobility Policy Support System Programska oprema za simulacijo prometa v kontekstu sistema za podporo mobilnostne politike Maj Smerkol Žan Počkar maj.smerkol@ijs.si zan24pockar@gmail.com Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia Alina Machidon Matjaž Gams alina.machidon@ijs.si matjaz.gams@ijs.si Jožef Stefan Institute Jožef Stefan Institute Jamova cesta 39 Jamova cesta 39 Ljubljana, Slovenia Ljubljana, Slovenia ABSTRACT nepričakovanih dogodkov in identifikacije negativnih aspektov predlaganih rešitev. Ocenili smo več različnih paketov program- Due to novel challenges in large cities’ traffic landscape the de- ske opreme za simulcaijo prometa v kontekstu podpore razvoja cision makers face more and more complex situations that are mobilnostne politike. Ocenjene rešitve imajo podobne funkcional- hard to understand while changes to these compound systems of nosti, potrebovane v okviru projekta H2020 Urbanite, razlikujejo road infrastructure, drivers and other actors can cause hard to pa se predvsem v tehnologijah implementacije in statusu vzdrže- predict undesired effects. As part of the H2020 Urbanite project vanja, kar ima velik vpliv na uporabnost paketa znotraj projekta. a mobility policy support system is in development. One of the important aspects of this system is an appropriate traffic simula- tion system that enables non-invasive and cheap evaluation of KLJUČNE BESEDE proposed policies. Simulation results will be further analysed us- promet, simulacija, politika mobilnosti, prometni model, umetna ing advanced AI methods that will allow detection of unexpected inteligenca events and identification of proposed solutions’ negative aspects. We evaluated different traffic simulation software packages in the context of supporting mobility policy development. While 1 INTRODUCTION included simulation software packages mostly provide similar feature sets and capabilities they differ in technology and main- European cities are facing new challenges in the form of novel tenance status which has implications on the ease of integration and innovative mobility solutions. On one hand disruptive start- and general usability for the project. ups are providing mobility on demand using different car sharing models while citizens are also starting to use micro-mobility de- KEYWORDS vices, such as e-scooters and similar devices. These innovations traffic, simulation, mobility policy, traffic modelling, artificial have unforeseen consequences such as e-scooters causing traffic intelligence accidents in pedestrian zones, disruptions in the traditional public transport industry that have trouble competing with new busi- POVZETEK ness models and electric charging points exacerbating existing problems like the growing demand for public car spaces. Nosilci prometnih odločitev v velikih mestih se soočajo z novimi In order to analyse and understand the complex systems of oblikami izzivov, ki izhajajo iz velike kompleksnosti modernih city traffic a novel AI-aided software ecosystem URBANITE is be- prometnih sistemov, sestavljenih iz prometne infrastrukture, voz- ing developed as part of the Horizon2020 European research pro- nikov in drugih akterjev. Vnašanje sprememb v takšne sistemem gramme. The URBANITE project is focused in developing a smart lahko vodi povzroči nepredvidljive stranske učinke. Da se bodo city system that will help decision makers in cities handle these lahko odločevalci informirano spopadali z novimi metodami mo- new challenges. The project will provide a data management bilnosti se v okviru projekta H2020 Urbanite razvija sistem za platform supporting the whole data harvesting process includ- podporo mobilnostne politike. Med glavne komponente sistema ing collection, aggregation and provisioning the data, a decision sodi podsistem za simulacijo prometa, ki omogoča neinvazivno support system including AI based predictive algorithms and in poceni evalvacijo predlaganih politik. Rezultati simulacij bodo simulation models and a social policy lab build upon co-creation lahko s pomočjo sistema Urbanite nadalnje analizirani s pomo- session and the empirical analysis of trust, impact, benefits and čjo metod umetne inteligence, ki bodo omogočile zaznavanje risks of all stakeholders in the project. Permission to make digital or hard copies of part or all of this work for personal This mobility policy support system will support the decision or classroom use is granted without fee provided that copies are not made or makers throughout the process of policy design and implemen- distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this tation. The core system includes a data harvesting and curation work must be honored. For all other uses, contact the owner /author(s). module, an intelligent algorithmic package and an advanced vi- Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia sualization module. The traffic simulation tool is one of the main © 2020 Copyright held by the owner/author(s). components of such an ecosystem, providing information on 418 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Smerkol et al. the expected results of policy and the possibility of discovering their trips multiple times before an equilibrium is reached unforeseen consequences of policy changes. where all agents are somewhat satisfied, but global opti- The results of traffic simulations will be further analysed us- mum is not reached. This is more realistic than globally ing AI methods for problematic and unexpected traffic events. optimized plans as humans planning their trips have lim- The traffic data will be linked to other relevant data such as ited knowledge of the traffic system state. weather condition, street noise levels and air pollution levels. Us- • Submicroscopic traffic simulation simulates vehicles ing linked data the traffic simulation will also be informed about using physical models, including steering, power train, demographic statistical data, such as percentage of household braking and suspension of the vehicle. These are extremely owning cars, general income and education levels etc. Thus the computationally demanding and not commonly used in system will be able to take into account commuters preferences traffic related operational research. Submicroscopic traffic using the Belief-Desire-Intention cognitive architecture [6]. models have been shown to simulate lateral movement (lane switching, trajectory negotiation) with high accuracy 2 TRAFFIC SIMULATION [5]. As a tool for municipality decision makers the ecosystem needs to For the purposes of the project a microscopic simulation is provide accurate and easy to understand information on demand. needed for tasks such as predicting noise and pollution levels and Since implementing changes to traffic policy is very expensive parking spaces demand. For preliminary quick results a macro- and takes a lot of time, simulating traffic is a better option. Thus scopic traffic the users can analyse outcomes from traffic policy changes includ- Depending on how the simulators treat time and space, we ing changes to public transport, car parking and even changes to can further categorize them into the infrastructure itself. Traffic simulations are in the realm of • time and space continuous models: traffic flow mod- operational research, which deals with utilizing the use of avail- els (equation models, usually using Ordinary Differential able resources in an optimal way while reducing the negative Equations or Partial Differential Equations), pedestrian co-products and outcomes. movement (integration over path) etc. We can categorise traffic simulations based on the level of • time and space discrete models: cellular automata traf- detail simulation provides: fic models (e.g. rule 184 - not commonly used anymore) • Macroscopic traffic simulation does not simulate indi- and numeric models with limited precision (PDE based vidual cars but instead treats traffic flow like a fluid or a models, ODE based models, some Monte Carlo methods). gas [3], moving through a network of pipes. This allows Other combinations of time and space discrete and continuous for good estimations of general road network capacity and including discrete/continuous state can be identified. helps identify bottle-necks that cause traffic jams. Since the traffic flows are usually generic, therefore not 3 SIMULATION SOFTWARE PACKAGES split by mode of transport (driving a car, taking the bus, freight trucks etc.) macro simulators often cannot provide Simulator is a software package used to test, replicate and predict detailed analysis of generated pollution, noise or strain on real world traffic situations. They require a lot of processing the road surface. The LWR (Lighthill-Whitham-Richards) power to be as accurate as possible. Processing power needed is models common in macroscopic traffic simulators have largest for running microscopic simulations. Commonly multi trouble simulating shock wave traffic jams and phantom agent based they require to locally optimize plans for each agent. traffic jams, which can be problematic when simulating To run a minimal traffic simulation we need a representation longer road segments or motorways [9]. of the city road network and a representation of the population • Mesoscopic traffic simulation 1 deals with traffic flows that includes data informing agent’s planning decision . Most but takes individual vehicles into account in certain cases, traffic simulation software also allows other inputs: most commonly at junctions (nodes in the network). This • public transit lines and schedules, technique is a compromise between amount and accuracy • locations and capacities of parking places and public park- of the data generated and the amount of computing power ing houses and time needed to produce results [1]. • details about existing vehicles (e.g. a segmentation of ve- • Microscopic traffic simulation simulated individual cars hicles based on European emission standards), as they move through the network. The results can be anal- • bicycle lanes included in the road network, ysed per individual rather than only the general traffic • number of available taxi cabs, flow and different types of vehicles can be simulated. Dif- • locations of electric charging stations etc. ferent types of vehicles can also have different properties, therefore we can accurately predict vehicular noise and 3.1 Evaluated software packages generated pollution (e.g. heavy freight traffic produces more noise and pollution than car traffic). Different types We have evaluated the following packages: of vehicles can also be simulated using different models • SUMO (Simulating Urban MObility [4] or with different parameters, such as acceleration and • MATSim (Multi-Agent based Traffic Simulation [10], braking [4]. • PTV Vissim [2] [7] and PTV Visum [8], Microscopic traffic simulations are usually implemented using agent-based modelling, where each person in a city is represented as an individual agent. Each agent plans 1 To inform planning and routing choices of an agent one can take into account their trips according to their own scoring function, op- their financial status, largest allowed lateness of arrival, whether or not they own a timizing their own plan locally. Usually, agents re-plan car etc. 419 Mobility Policy Support System Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Figure 1: Part of a traffic simulation of Bilbao, made with MATSim. Triangles represent a sampled subset of the vehicles in the network, where cyan-colored vehicles are moving at high speed and pink-colored vehicles are stationary - either waiting at traffic lights or stuck in traffic. 3.2 Reasons for simulating traffic simulation packages is quite widespread, but most do not have a great variety of transport mode options. While using a car or Implementation of a new mobility policy is a long and expensive other similar transport modes such as taxi cabs or car sharing are process. Solving the problem of a single congested road may almost ubiquitously supported others are missing - even public results in other problems that can hardly be predicted without transport support is lacking in some of them. The biggest obstacle some computational help. Traffic simulations allow the traffic is simulation of bicycle traffic. engineers to see the impact of changes without testing them out in real world, which would take a lot of time and is very expensive. Some changes to the road network may also need 3.3 Evaluation results invasive actions such as relocating citizens. There needs to be 3.3.1 PTV Visum and PTV Vissim. PTV Group is a major com- strong evidence that the results will have positive impact before pany in the field of traffic management and both products are implementing such changes. the industry standards for macroscopic traffic simulation and Traffic simulations also allow cities to gain more insight into microscopic traffic simulation, respectively. While not useful for the city traffic patterns by identifying common trip patterns, the project due to copyright restrictions and proprietary source providing data about pollution and noise levels in residential code we have included them in order to compare with other open areas or identifying the areas where certain problem arise, such source tools. as low parking space capacities. PTV Visum is a macroscopic traffic simulation tool that sup- Some of the use cases identified in the project are: port multi-modal transport and transit. It’s primary purpose is • analysis of large, regional road networks it can also be used on traffic pattern recognition, • the level of a city. analysis of mobility modality - comparing travel by car, PTV Vissim is a microscopic traffic simulation tool that sup- bike, public transport or by foot, • ports multi-modal transport and many other advanced use cases analysis of public transport - line usage, congested lines, • such as indoor pedestrian traffic simulations and quasi-realistic identification of districts affected by noise and air pollu- 3D visualization. While Vissim can interact with GIS data sources tion, • it does not support importing open data sources and is primar- analysis of traffic accidents - most affected junctions or ily used to simulate small road subnetworks such as complex roads etc, • junctions that are usually designed using the inbuilt network analysis of universal access to facilities, • manager. identification of bicycle traffic patterns and bicycle traffic These tools are not extensible by third parties and while they jams, • provide beautiful user interfaces therefore not usable for the comparison of expected traffic trends with actual traffic projects. trends and • analysis of capacities and demand for parking places. 3.3.2 SUMO. SUMO is an open source, microscopic and space Through the use of advanced simulators one can simulate and time continuous traffic simulation software package. It sup- different aspects of traffic. All simulators considered for the ports multi-agent based multi-modal simulations. SUMO is a project include multi-modal approach supporting at least car, relatively old and mature software package that supports most public transport, bike and walk modes. Multi-modality support- of the identified use cases. It has been used in many real-world ing changing mode of transport during one trip is vital for our cases with good success. SUMO package contains all the tools goal of simulating the complex interactions between different needed to prepare a network, run a simulation and analyze the parts of the traffic system. Support for multi-modality in traffic results. 420 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Smerkol et al. It is a complete package containing a full set of GUI tools Finally, due to large amount of computer power needed to run which can prepare the network, model traffic demand, run the such simulations, for the project we will complement microscopic simulation and visualize the results. The GUI simulator applica- traffic simulations with faster and less precise macroscopic traffic tion allows even inexperienced users to set up simple simulations. simulations. Thus we will be able to run optimization algorithms However the true power of the package is unveiled when work- and evolutionary algorithms to discover possible solutions to ing with the command-line interface (CLI). There are a lot of traffic problems. utilities and tools included to manipulate the configuration of the scenario and to set up the network. ACKNOWLEDGMENTS However due to its monolithic nature (excluding CLI tools This paper is supported by European Union’s Horizon 2020 Re- that are mostly implemented as python scripts) it is not easily search and Innovation Programme, URBANITE project under extensible and adaptable to the project’s specific needs. Some of Grant Agreement No.870338. the problems we have encountered are out of date documentation, 2 the simulation crashing due to lack of memory available , lack REFERENCES of informative error reports that slow down the workflow and [1] Felipe de Souza, Omer Verbas, and Joshua Auld. 2019. Mesoscopic 3 lack of support for simulating bicycle traffic . traffic flow model for agent-based simulation. Procedia Computer Science, 151, 858 –863. The 10th International Conference on Am- 3.3.3 MATSim. MATSim is a java based framework which pro- bient Systems, Networks and Technologies (ANT 2019) / The vides the user with multitude of tools which are used to run 2nd International Conference on Emerging Data and Industry 4.0 agent-based large-scale simulations. MATSim’s strengths lie in (EDI40 2019) / Affiliated Workshops. issn: 1877-0509. doi: https: its adaptability and malleability for user preferences. 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Collision between bicycles is hard to model and detecting bicycle traffic jams is not possible. 421 Kako so predvidevale razvoj prebivalstva Slovenije tri izbrane projekcije prebivalstva Slovenije v preteklosti Janez Malačič Ekonomska fakulteta Univerze v Ljubljani Kardeljeva ploščad 17, 1000 Ljubljana, Slovenija e-naslov: janez.malacic@ef.uni-lj.si POVZETEK Besedilo obravnava (ne)uresničevanje treh avtorjevih 2 HIPOTEZE PROJEKCIJ IN DEJANSKI projekcij prebivalstva izdelanih za obdobje 35 let in objavljenih v šestih izdajah učbenika Demografija do leta RAZVOJ PREBIVALSTVA SLOVENIJE 2020 posebej za moške in ženske. Izmed vseh variant DO LETA 2020 (konstantna, nizka, srednja in visoka) treh projekcij se je do S pomočjo hipotez o smrtnosti, rodnosti in migracijah leta 2020 uresničila le visoka varianta projekcije 1991-2026 avtor projekcij predvideva prihodnji razvoj osnovnih za ženske. Vse ostale variante projekcij so podcenile demografskih procesov in s tem ključnih elementov dejansko rast števila prebivalstva Slovenije do leta 2020. prihodnjega razvoja prebivalstva v obdobju za katerega se izdelujejo projekcije prebivalstva. V konkretnih projekcijah uporabljeni računalniški program zahteva postavitev 1 UVOD hipoteze o smrtnosti v eni varianti ter hipotez o rodnosti in Projekcije prebivalstva običajno delimo na perspektive in migracijah v štirih variantah. Te variante so konstantna, napovedi. Prve izdelamo v več variantah. Največkrat so štiri: nizka srednja in visoka. Zaradi omejenega prostora tukaj ne konstantna, nizka, srednja in visoka. Napoved pa je moremo obravnavati hipotez v vseh elementih in praviloma ena sama in sicer tista, za katero avtor smatra, da podrobnostih, prav tako pa tudi ne bomo obravnavali se bo uresničila. V tem prispevku bomo obravnavali tri podrobnega dejanskega razvoja posameznega perspektive prebivalstva Slovenije, ki so bile izdelane za demografskega procesa. Omejili se bomo na nekaj pedagoške namene na osnovi Shorterjevega programa agregatnih kazalcev, ki pa kljub vsemu okvirno dovolj dobro FIVFIV in objavljene v šestih izdajah avtorjevega učbenika pokažejo razlike med postavljenimi hipotezami in kasnejšim Demografija (Malačič, 1993, 1996, 1997, 2000, 2003, 2006). dejanskim razvojem. Od objave je minilo dovolj dolgo obdobje, da lahko Naslednja pomembna omejitev naše obravnave je primerjamo dejanski razvoj prebivalstva Slovenije in dejstvo, da se projekcijsko obdobje še ni v celoti izteklo pri predvidevanje tega razvoja v treh izbranih projekcijah, ki so nobeni od treh projekcij. Zato bomo morali to dejstvo bile izdelane za 35 let (1991-2026, 1996-2031 in 2006-2041). upoštevati. Ker pa je narava hipotez takšna, da je težko Ker pa se projekcijsko obdobje še ni izteklo niti za eno enoznačno izdvojiti do leta 2020 pretečeno obdobje, bomo v projekcijo, bo naša obravnava le delna in bo zajela le malo nadaljevanju obravnavali tudi del obdobja, ki sega v celotno manj kot trideset let po letu 1991. Že sedaj pa lahko rečemo, projekcijsko obdobje. Pri obravnavi posameznih hipotez pa da je trideset let v modernem svetu izredno dolgo obdobje. bomo upoštevali tudi razlike med njimi samimi in način, Prostor nam tukaj ne dopušča zelo podrobne kako so konkretno vgrajene v sam program FIVFIV. analize razlik med projekcijami in dejanskim razvojem Upoštevati pa je potrebno še ažurnost statističnih podatkov v prebivalstva, saj bi takšna analiza zahtevala celo knjigo, ker času izdelave projekcij. Ta se je med tremi projekcijami je razvoj prebivalstva zelo kompleksen in obsežen, časovno izboljševala, saj se je uradna statistika v Sloveniji obdobje pa sorazmerno dolgo. Zato se bo naša obravnava izboljševala in nekje od sredine 1990ih let tudi hitro omejila na osnovne značilnosti posameznih hipotez projekcij evropeizirala. Pri prvih projekcijah, ki imajo začetek v letu in okvirne rezultate projekcij v primerjavi z dejanskim 1991, izdelane pa so bile v letu 1992, pa je na ažurnost razvojem prebivalstva Slovenije do leta 2020 ter na pomen podatkov vplival tudi razpad jugoslovanske države in takšne obravnave. nastanek samostojne Slovenije. Najbolj enostavna varianta projekcij je konstantna varianta. Pri njej vzamemo za rodnost, smrtnost in migracije podatke iz izhodiščnega leta ali zadnje razpoložljive podatke čim bližje izhodiščnemu letu in izdelamo projekcijo pod predpostavko, da ostanejo posamezni demografski procesi nespremenjeni naslednjih 35 let. V naših treh projekcijah smo pri zaporednih projekcijah 1991, 1996 in 2006 zabeležili 422 naslednje izhodiščne podatke: pri rodnosti Rn zaporedoma 1997 in 2005, kasneje pa z nekoliko zaostanka dobro sledi 0,70, 0,64 in 0,60, pri smrtnosti e0,m zaporedoma 67,34, dejanskemu gibanju. Za vse variante hipoteze o rodnosti 70,27 in 73,7 ter e0,f 75,16, 77,76 in 81,2 ter pri migracijah zadnje projekcije 2006-2041 pa lahko zapišemo, da so pod v povprečnem letnem meddržavnem migracijskem saldu pri močnim vplivom zelo nizke rodnosti v letih 2001 do 2005. moških zaporedoma 1300, 800 in 1950 ter pri ženskah 1200, Zaradi tega je bila predvidena rodnost v vseh variantah 700 in 450. Dejanski podatki, ki so na voljo leta 2020 kažejo projekcijskega obdobja do leta 2020 precej nižja od velika nihanja rodnosti in migracij ter hitro rast življenjskega dejanskih podatkov o rodnosti v tem obdobju. pričakovanja po petletnih obdobjih in tudi po spolu. Za hipotezo o migracijah v vseh treh projekcijah in Konstantna varianta bi bila primerna samo pri hipotezi o v vseh variantah lahko najprej ugotovimo, da je dosledno rodnosti v letu 1991, pa še pri tej le v povprečju in ne zaradi predvidevala pozitivne neto migracije tako za moške kot tudi konstantnosti. Rn se je namreč od 0,70 leta 1991 znižal na za ženske. To je bilo pravilno, saj so bile neto migracije le 0,59 v povprečju v obdobju 2001-05 in nato dvignil čez 0,7 izjemoma negativne v kakšnem letu ali pri spolu, nikakor pa od leta 2008 naprej. V letih 2016-19 je bila povprečna ne za pet let zapored ali za pet let v povprečju. Tudi pri tej vrednost 0,77. Vrednosti Rn za leti 1996 in 2006 sta bili hipotezi so dejanski podatki po petletnih obdobjih izrazito prenizki. Pri smrtnosti je bila konstantna varianta zaradi nihali, predvidene vrednosti v hipotezah pa nihanj razen velikega povečanja e0,m in e0,f slaba. Podobno velja pri izjemoma ne kažejo. To je po svoje razumljivo, saj so migracijah za moške in nekoliko manj za ženske, vendar je dejanska migracijska gibanja zelo odvisna od cikličnega pri migracijah ključni problem izredno veliko nihanje med gibanja gospodarstva, tega pa ekonomska znanost še ni posameznimi leti in tudi petletnimi povprečji. Podrobnejše sposobna napovedovati niti na srednji rok, na dolgi kar 35 let podatke o smrtnosti in migracijah bomo navedli nekoliko raztegnjen rok pa nikakor ne. Vse hipoteze o migracijah v kasneje. treh projekcijah so tudi bistveno podcenile razliko med Hipoteza o smrtnosti je bila postavljena za nizko, moškimi in ženskami. Migracijski saldi pri moških so v srednjo in visoko varianto projekcij samo v eni varianti, Sloveniji v dobrih in slabih časih bistveno večji kot pri vendar so bili uporabljeni kazalci koeficienti doživetja za ženskah. Za ženske lahko še zapišemo, da so hipoteze petletne starostne razrede, e0 in e5 za moške in ženske. Tukaj predvidevale praviloma previsoke neto selitve v vseh si bomo okvirno ogledali le hipotezo in dejanske podatke za variantah in vseh projekcijah. Če na kratko pogledamo še e0. Naša hipoteza o povečanju e0 v projekcijskem obdobju posamezne projekcije, lahko za projekcijo 1991-2026 35 let za tri projekcije je bila pri moških zaporedoma od ugotovimo, da nobena varianta ni predvidela zelo nizkega 67,34 na 72,51, od 70,27 na 73,8 in od 73,7 na 77,9 ter pri salda v prvih petih letih samostojne Slovenije. V kasnejših ženskah od 75,16 na 79,35, od 77,76 na 80,5 in od 81,2 na petletnih obdobjih se hipoteze pri ženskah gibljejo med 800 84,6 let. Hipoteze so prenizke, saj dejanski podatki za leto in 2500 na leto pri ženskah in med 900 in 2700 na leto pri 2019 kažejo, da je e0,m 78,5 in e0,f 84,22. Za projekcijo z moških. Dejanski petletni podatki pa nihajo med 441 in 2013 začetkom leta 1991 pa je potrebno dodati, da so bili ob na leto pri ženskah in 201 in 8005 na leto pri moških. Za leta izdelavi na voljo le skoraj deset let stari podatki iz tablic krize so hipoteze previsoke, za leta ugodnih gospodarskih smrtnosti. Pričakujemo pa lahko še nadaljnje naraščanje tega gibanj pa so prenizke. Projekcija 1996 – 2031 je v primerjavi kazalca in tudi, da sedanja kriza zaradi COVID 19 ne bo s prvo projekcijo znižala predvideno neto priseljevanje v bistveno vplivala na trend. Slovenijo v vseh variantah hipoteze o migracijah. Zato so v Naslednja hipoteza je hipoteza o rodnosti v nizki, njej dejanske neto migracije na splošno podcenjene v vseh srednji in visoki varianti treh obravnavanih projekcij. Prva variantah. Projekcija 2006-2041 je pod vplivom dejanskih značilnost hipoteze o rodnosti v vseh variantah in vseh treh podatkov o neto migracijah v letih 2001-2005 povečala projekcijah je ta, da razen izjemoma ne predvideva nihanja razliko med spoloma v korist moških. To razliko kasneje v navzdol in navzgor ali obratno. Omembe vredna izjema je le vseh variantah postopoma zmanjšuje, kar verjetno ne bo srednja varianta projekcije 1991-2026. Ta varianta se od dobro v naslednjih dvajsetih letih. Če pa se omejimo samo na začetne vrednosti Rn 0,70 v naslednjih treh vrednostih za prvih 15 let projekcijskega obdobja, lahko zapišemo, da je petletna obdobja spusti pod to raven (tudi do 0,62), v zadnjih hipoteza o migracijah v vseh treh variantah podcenjena. treh vrednostih pa se dvigne nad začetno vrednost vse do 0,84 v zadnjih petih letih. Na tak način v povprečju kar dobro odraža dejanska gibanja rodnosti. Nizka in visoka varianta te 3 REZULTATI PROJEKCIJ NA prve projekcije se nista uresničili, saj je projekcija predvidela PRIMERU ŠTEVILA PREBIVALSTVA za zadnjih pet let projekcijskega obdobja Rn vsega 0,50 za IN NJIHOVO (NE)URESNIČEVANJE nizko in kar 1,0 za visoko varianto. Na podoben način se Model analitičnih projekcij prebivalstva nam da izredno nista uresničili nizka in visoka varianta hipoteze o rodnosti v bogastvo podatkov o predvidenem prihodnjem razvoju projekciji 1996-2031, čeprav visoka varianta ni več prebivalstva v okviru projekcijskega obdobja. To velja tudi predvidevala dviga rodnosti na raven enostavnega za naše tri izbrane projekcije. Na voljo imamo podatke o obnavljanja prebivalstva do leta 2031. Tudi v tej projekciji je strukturi prebivalstva po starosti in spolu z intervalom pet bila najboljša srednja varianta hipoteze o rodnosti. Ta sicer let, izračunamo lahko celo vrsto enostavnih in bolj ni predvidela znižanja Rn na ravni med 0,60 in 0,57 med leti 423 kompleksnih kazalcev razvoja prebivalstva, vsekakor nobenih relativnih števil ali morebitnih drugih kazalcev, ki bi najpomembnejši podatek pa je število celotnega podrobneje prikazali primerjavo med predvidevanjem prebivalstva. Zaradi prostorske omejitve bomo obravnavali prihodnjega razvoja prebivalstva Slovenije v treh rezultate izbranih projekcij prebivalstva do leta 2021 na obravnavanih projekcijah prebivalstva in kasnejšim primeru števila prebivalstva posebej za moške in ženske. dejanskim razvojem prebivalstva. Za podrobnejši analitični Posebna obravnava moških in žensk je posledica narave prikaz razlik bi potrebovali veliko več prostora, kot je na modela projekcij prebivalstva pa tudi narave samih voljo v tem besedilu. Ne glede na vse to pa je iz tabele 1 že demografskih procesov. Že pri obravnavi hipotez projekcij na prvi pogled mogoče izluščiti osnovne in najbolj prebivalstva smo videli, da se podatki pri smrtnosti in pomembne značilnosti (ne)uresničevanja v projekcijah migracijah zelo razlikujejo po spolu. Te razlike pa se najlepše predvidenega razvoja prebivalstva Slovenije do konca pokažejo pri ločeni obravnavi rezultatov projekcij po spolu. drugega desetletja 21. stoletja. Podatki so v tabeli 1. Namen prikaza podatkov v tabeli 1 je izrazito ilustrativen. Na osnovi teh podatkov ne bomo izračunavali Tabela 1: Število prebivalstva po spolu v projekcijah 1991-2026, 1996-2031 in 2006-2041 in po dejanskem razvoju v izbranih letih. Vir: Malačič, 1993, 1997 in 2006; SISTAT, dostop 23. 9. 2020. Projekcija/ Leto Razvoj P Varianta Spol 2001 2011 2021 1 2 3 4 5 6 M 958.641 932.579 879.500 Nizka Ž 1.016.981 994.976 953.441 1991 – 2026 M 961.271 952.614 944.633 Srednja Ž 1.019.109 1.013.238 1.014-615 M 962.822 977.134 985.833 Visoka Ž 1.020.603 1.036.863 1.054.248 M 970.053 955.640 915.759 Nizka Ž 1.022.008 999.523 954.580 1996-2031 M 970.053 960.485 939.637 Srednja Ž 1.022.008 1.004.226 977.450 M 970.053 971.244 967.363 Visoka Ž 1.022.008 1.014.570 1.004.105 M - 978.933 952.735 Nizka Ž - 1.009.977 973.364 2006-2041 M - 978.933 957.879 Srednja Ž - 1.009.977 979.080 M - 978.933 966.772 Visoka Ž - 1.009.977 986.060 M 972.749 1.014.563 1.051.066x Dejanski razvoj Ž 1.017.352 1.035.626 1.044.795x Skupaj 1.990.094 2.050.189 2.095.861x x Podatek je za leto 2020 Rezultate projekcij in njihovo primerjavo z dejanskimi hipotez smo lahko videli, da so se predvidevanja slabo statističnimi podatki, ki jih je objavil Urad za statistiko uresničila. Republike Slovenije, je potrebno obravnavati skupaj z vsem Za obravnavo uresničevanja projekcij in njihovih tistim, kar smo povedali že pri obravnavi posameznih hipotez posameznih variant smo izbrali leta 2001, 2011 in 2021. Pri projekcij in primerjav hipotez z dejanskim razvojem na slednjem letu imamo dejanski podatek za leto 2020, vendar primeru posameznih uporabljenih kazalcev. Že pri obravnavi to ni problem, ker je zelo jasno, da so podatki za leto 2020 424 precej višji od vseh variant projekcij, z izjemo visoke variante projekcije 1991-2026 za ženske. Ta varianta je tudi edina, za katero lahko rečemo, da se je pri ženskah uresničila. Za vse druge variante projekcij za moške in ženske pa lahko rečemo, da so prenizke. Težko je na kratko dobro odgovoriti na vprašanje, zakaj smo pred 30, 25 in 15 leti predvidevali prenizko rast ali celo upadanje prebivalstva. Pri nizki varianti je to deloma tudi posledica narave nizke variante. Veliko bolj pomembno pa je bilo demografsko dogajanje v zadnjem desetletju prejšnjega in v prvi polovici prvega desetletja sedanjega stoletja. V tem obdobju je transverzalna rodnost v Sloveniji padla na najnižje do sedaj zabeležene ravni, kar je vplivalo v kombinaciji z gospodarskim in političnim dogajanjem na to, da so vsake naslednje projekcije slabše predvidevale dejanski razvoj. Dokončna analiza posameznih projekcij pa bo v celoti možna šele po izteku projekcijskih obdobij. 4 SKLEP Analiza uresničevanja v projekcijah prebivalstva predvidenega prihodnjega razvoja prebivalstva je pomembna zaradi številnih razlogov. Ti so tako strokovni kot širše družbeni in politični. Pri prvih je namen predvsem napredek pri razvoju metodologije in stroke, pri družbenih in političnih vidikih pa je najpomembnejša ocena uporabnosti projekcij prebivalstva za vodenje različnih konkretnih družbenih politik, od politike prebivalstva do gospodarske, socialne, regionalne in drugih politik. Projekcije, ki smo jih obravnavali v tem besedilu so bile izdelane za pedagoške namene. Zato verjetno niso imele posebnega vpliva na širše družbene vidike in vodenje konkretnih politik. Kljub temu pa so nekatere ugotovitve tega besedila širše pomembne. Verjetno sta najbolj pomembni dve. Prva je ta, da bodo strokovnjaki imeli zmeraj težave pri predvidevanju dolgoročnih gibanj procesov, ki so po svoji naravi ciklični. Prihodnje krize v več desetletnem obdobju verjetno ne bo nikoli mogoče točno napovedati. Druga ugotovitev pa je, da na vsako projekcijo najbolj vpliva gibanje demografskih procesov v pet do deset let dolgem obdobju pred izhodiščnim letom projekcije. Če se v tem obdobju pojavi odstopanje od siceršnjih trendov, bo to gotovo vplivalo na uresničevanje projekcij. LITERATURA IN VIRI [1] Malačič, J. (1993, 1996, 1997, 2000, 2003, 2006) Demografija. Teorija, analiza, metode in modeli. Šest izdaj. Ekonomska fakulteta Univerze v Ljubljani, Ljubljana. [2] Statistični letopis Republike Slovenije (1993, 1996, 2001, 2013). Statistični urad Republike Slovenije, Ljubljana. [3] SISTAT, baza podatkov. Statistični urad Republike Slovenije, Ljubljana. Dostop 23. 9. 2020. 425 426 Zbornik 23. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2020 Zvezek G Proceedings of the 23rd International Multiconference INFORMATION SOCIETY – IS 2020 Volume G Vzgoja in izobraževanje v informacijski družbi Education in Information Society Uredila / Edited by Uroš Rajkovič, Borut Batagelj http://is.ijs.si 9. oktober 2020 / 9 October 2020 Ljubljana, Slovenia 427 428 PREDGOVOR Letošnje šolsko leto je bilo povsem drugačno od preteklih let in tudi za prihodnje leto se nam obeta zelo posebno šolsko leto. Zaznamovala ga je odsotnost učencev iz šolskih prostorov in odsotnost neposrednega kontakta z učitelji, na vseh nivojih od vrtca do univerze. Pri tem so v ospredje stopili, bolj kot kadarkoli do sedaj, informacijsko komunikacijska tehnologija in veščine vzgoje in izobraževanja na daljavo. Zato je tudi letošnja konferenca drugačna od ostalih. Pogovorili se bomo predvsem o rezultatih novega načina dela, s katerim smo bili in bomo verjetno tudi v prihodnje soočeni. Pogledati moramo dobre prakse in tudi spodrsljaje. Iz obojega želimo izoblikovati sodobno digitalizirano vzgojo in izobraževanje, ki ne bo brez kontakta z učenci, brez učiteljev oz. brez neposrednega kontakta med vsemi deležniki, če je to le mogoče. Soočamo se s potrebo novega opolnomočenja učencev, staršev, učiteljev, vodstva šol, nenazadnje tudi državnih organov, kot sta Zavod Republike Slovenije za šolstvo in pristojno ministrstvo. Zato vas vabimo, da se aktivno udeležite konference Vzgoja in izobraževanje v informacijski družbi 2020, da predstavite svoje poglede in izkušnje ter da skupaj poiščemo rešitve za v bodoče. Uredniški odbor FOREWORD This school year was very different from previous years and we are looking forward to a very special school year ahead. It was marked by the absence of students from school premises and the absence of direct contact with teachers, at all levels from kindergarten to university. At the same time, information and communication technology and distance education skills have come to the fore, more than ever before. That is why this year’s conference is different from the others. We will mainly discuss the results of the new way of teaching and learning that we have been and will probably continue to face in the future. We need to look at good practices as well as shortfalls. We want to create a modern digitized education and training, which will not be without contact with students, without teachers or without direct contact between all stakeholders, if at all possible. We are facing the need for new empowerment of students, parents, teachers, school management, and last but not least, state bodies such as the National Education Institute Slovenia and the responsible ministry. Therefore, we invite you to actively participate in the conference Education in Information Society 2020, to present your views and experiences, and to find solutions for the future together. Editorial board 429 PROGRAMSKI SVET / STEERING COMMITTEE Matjaž Gams (chair), Institut Jožef Stefan Vladimir Batagelj, Univerza v Ljubljani, Fakulteta za matematiko in fiziko Saša Divjak, Univerza v Ljubljani, Fakulteta za računalništvo in informatiko Ivan Gerlič, Univerza v Mariboru, Fakulteta za naravoslovje in matematiko Iztok Podbregar, Univerza v Mariboru, Fakulteta za organizacijske vede Vladislav Rajkovič, Univerza v Mariboru, Fakulteta za organizacijske vede in Institut Jožef Stefan Niko Schlamberger, Slovensko društvo Informatika Tomaž Skulj Olga Šušteršič, Univerza v Ljubljani, Zdravstvena fakulteta Rado Wechtersbach PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Uroš Rajkovič (chair), Univerza v Mariboru, Fakulteta za organizacijske vede Borut Batagelj (co-chair), Univerza v Ljubljani, Fakulteta za računalništvo in informatiko Zvone Balantič, Univerza v Mariboru, Fakulteta za organizacijske vede Igor Bernik, Univerza v Mariboru, Fakulteta za varnostne vede Mojca Bernik, Univerza v Mariboru, Fakulteta za organizacijske vede Janez Bešter, Univerza v Ljubljani, Fakulteta za elektrotehniko Uroš Breskvar, Elektrotehniško-računalniška strokovna šola in gimnazija Ljubljana Andrej Brodnik, Univerza v Ljubljani, Fakulteta za računalništvo in informatiko in Univerza na Primorskem, Fakulteta za matematiko, naravoslovje in informacijske tehnologije Borut Čampelj, Ministrstvo za izobraževanje, znanost in šport RS Dejan Dinevski, Univerza v Mariboru, Medicinska fakulteta Tomi Dolenc, ARNES Marjan Heričko, Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko Eva Jereb, Univerza v Mariboru, Fakulteta za organizacijske vede Mirjana Kljajić Borštnar, Univerza v Mariboru, Fakulteta za organizacijske vede Alenka Krapež, Gimnazija Vič Franc Solina, Univerza v Ljubljani, Fakulteta za računalništvo in informatiko Branislav Šmitek, Univerza v Mariboru, Fakulteta za organizacijske vede Srečo Zakrajšek, Fakulteta za medije 430 RECENZENTI / REVIEWERS Alenka Baggia, Univerza v Mariboru, Fakulteta za organizacijske vede Jelka Bajželj, Šolski center Kranj, Višja strokovna šola Branka Balantič, Šolski center Kranj, Višja strokovna šola Zvone Balantič, Univerza v Mariboru, Fakulteta za organizacijske vede Igor Bernik, Univerza v Mariboru, Fakulteta za varnostne vede Mojca Bernik, Univerza v Mariboru, Fakulteta za organizacijske vede Borut Čampelj, Ministrstvo za izobraževanje, znanost in šport ter Visoka šola za upravljanje in poslovanje Novo mesto Dejan Dinevski, Univerza v Mariboru, Medicinska fakulteta Saša Divjak, Univerza v Ljubljani, Fakulteta za računalništvo in informatiko Branka Jarc Kovačič, Šolski center Kranj, Srednja tehniška šola Eva Jereb, Univerza v Mariboru, Fakulteta za organizacijske vede Alenka Krapež, Gimnazija Vič Robert Leskovar, Univerza v Mariboru, Fakulteta za organizacijske vede Matija Lokar, Univerza v Ljubljani, Fakulteta za matematiko in fiziko Vesna Novak, Univerza v Mariboru, Fakulteta za organizacijske vede Marko Novaković, Univerzitetni klinični center Ljubljana Uroš Rajkovič, Univerza v Mariboru, Fakulteta za organizacijske vede Tomaž Skulj, Inštitut Hevreka Gašper Strniša, Šolski center Kranj, Strokovna gimnazija Iztok Škof, Osnovna šola Toma Brejca Kamnik Branislav Šmitek, Univerza v Mariboru, Fakulteta za organizacijske vede Marko Urh, Univerza v Mariboru, Fakulteta za organizacijske vede Rado Wechtersbach, Zavod RS za šolstvo Anja Žnidaršič, Univerza v Mariboru, Fakulteta za organizacijske vede 431 432 Poučevanje programskega okolja LabView Teaching LabView software Jaka Albreht Šolski center Kranj Kidričeva 55 4000 Kranj, Slovenija jaka.albreht@sckr.si POVZETEK Predstaviti jim nameravamo tudi konkretne projekte iz industrije, kjer je bil uporabljen LabView. Dijaki se želijo izobraževati na področjih, ki so v praksi uporabna. Poznavanje programskega okolja LabView je vsekakor eno Vsekakor je LabView programiranje praktično uporabno, zato izmed njih. Gre za grafični programski jezik, kjer programiramo bomo z njegovim poučevanjem nadaljevali. tako, da povezujemo funkcijske bloke v celoto. Uporablja se v industriji za avtomatizirane meritve, vodenje sistemov, KLJUČNE BESEDE simulacijo in analizo signalov. LabView, grafično programiranje, Arduino UNO, DAQ kartice Podjetje National Instruments poleg programske opreme ponuja ABSTRACT tudi kartice za zajemanje podatkov (DAQ card). Nanje lahko priključimo vhodno-izhodne elemente kot so senzorji, tipke, Students want to be educated in areas that are useful in practice. LED, idr. Zaradi cenovne dostopnosti smo namesto kartic Knowledge of the LabView software environment is one of them. uporabili razvojno ploščo Arduino UNO, ki smo jo preko USB- It is a graphical programming language where we program by povezave priključili na računalnik, kjer je bilo nameščeno okolje connecting function blocks into a whole. It is used in the industry LabView. for automated measurements, system control, simulation and signal analysis. Pri praktičnem delu modula Regulacije smo najprej spoznali osnove LabView programiranja na primeru izdelave programa, Besides software, National Instruments also offers DAQ cards. ki je omogočal simulacijo nivoja tekočine. Izdelali smo tudi dva We can connect input-output elements such as sensors, keys, kompleksnejša programa, kjer lahko naključno izbiramo dijaka LEDs, etc. Due to affordability, we used the Arduino UNO in mu dodelimo izpitno vprašanje oz. generiramo loto development board instead of cards, which we connected via a kombinacijo. USB connection to a computer where the LabView environment was installed. V naslednjem koraku smo napisali program, ki je omogočal serijsko komunikacijo med razvojno ploščo Arduino UNO in In the practical part of the Control systems module, we first računalnikom. Preko virtualnega gumba smo nadzirali branje learned the basics of LabView programming in the case of analognih vhodov in prižigali oz. ugašali vgrajeno LED na enem creating a program that allowed the simulation of the fluid level. izmed digitalnih izhodov. We created two more complex programs, where we can randomly select a student and assign him an exam question, or Ob koncu pouka smo dijake v anketi povprašali kaj menijo o we generate a lotto combination. vključevanju vsebin s področja LabView programiranja v pouk. Večini se zdi, da je programsko okolje LabView uporabno. Kljub In the next step, we wrote a program that allowed serial temu, da svoje znanje ocenjujejo kot dobro, bi si ga želeli še communication between the Arduino UNO development board poglobiti in spoznati tudi praktične projekte iz industrije. and the computer. Through the virtual button, we controlled the reading of analog inputs and turn on or off the built-in LED on Glede na pozitivne odzive bomo v prihodnosti dijakom poleg one of the digital outputs. vsebin znotraj rednega pouka ponudili tudi LabView krožek, delavnice na Dnevih na vedoželjne, povezali se bomo s At the end of the lesson, we asked the students in the survey what podjetjem National Instruments ter spodbujali uporabo they thought about using the LabView programming in the lesson. programskega okolja LabView pri izdelavi zaključnih nalog. To most, the LabView software environment seems useful. Even though they assess their knowledge as good, they would like to deepen it and get to know practical projects from the industry. According to the positive responses, in the future we will offer Permission to make digital or hard copies of part or all of this work for personal or students a LabView circle, workshops at the Days of the Curious, classroom use is granted without fee provided that copies are not made or distributed connect with National Instruments and encourage the use of the for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must LabView software environment in the preparation of final be honored. For all other uses, contact the owner/author(s). assignments. We also intend to present concrete projects from Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia the industry where LabView was used. © 2020 Copyright held by the owner/author(s). 433 In any case, LabView programming is practically useful, so we imamo na voljo tudi strojno opremo kot so npr. kartice za will continue to teach it. zajemanje podatkov (DAQ – data aquisition) [2]. Pri poučevanju smo se osredotočili na to, kako zajeti signal s senzorja in ga KEYWORDS pripeljati do računalnika, kjer je nameščeno programsko okolje LabView, graphical programming, Arduino UNO, DAQ cards LabView. Podatke nato shranimo, prikažemo na grafu ali izvedemo izračune. Signal s senzorja je najprej potrebno ojačati, filtrirati in 1 UVOD prilagoditi območje. Nato sledi pretvorba v digitalno obliko, kar Dijaki se velikokrat sprašujejo kje se da znanja, ki jih pridobijo nam omogoča analogno-digitalni pretvornik. Kartice za v šoli, praktično uporabiti. Od tod tudi izvirajo vprašanja v zajemanje podatkov vsebujejo digitalne in analogne vhode ter smislu “Kdaj/kje bom pa to rabil?”. Menimo, da uvodna izhode (Slika 2). Nanje lahko priklopimo različne vhodno- motivacija dijakov izboljša proces pridobivanja znanja. izhodne elemente (senzorje, tipke, aktuatorje ipd.). Motiviramo pa jih lahko, da jim pokažemo kje so znanja, ki naj Obstajajo različni vmesniki, ki se razlikujejo po številu bi jih pridobili, tudi praktično uporabna. Da poučujemo tiste vhodov/izhodov, ločljivosti A/D pretvornika, hitrosti zajemanja stvari, ki se v praksi uporabljajo. podatkov itd. V Tabeli 1 so prikazane nekatere lastnosti kartice V nadaljevanju se bomo osredotočili na poučevanje NI USB 6009. programskega okolja LabView, podjetja National Instruments [1], katerega logotip prikazuje Slika 1. LabView je grafični Tabela 1: Lastnosti DAQ kartice NI USB 6009 programski jezik. Programiramo tako, da povezujemo bloke in programske strukture, ki tvorijo program. LabView se NI USB 6009 uporablja za avtomatizirane meritve, vodenje sistemov, Analogni vhodi 8 (14-bitni ADC) simulacijo in analizo signalov itd. Analogni izhodi 2 (12-bitni DAC) Digitalni vhodi/izhodi 13 Števec 32-bitni Slika 1: National Instruments – LabView logotip 2 LABVIEW Pomemben dejavnik za poučevanje tega programskega okolja je to, da se ga uporablja v marsikaterem podjetju oz. industriji. Če bi pobrskali po oglasih za delo, bi opazili, da nekatera podjetja zahtevajo znanje LabView programiranja. S tem znanjem smo torej konkurenčni na trgu dela. Pri podjetju National Instruments imajo tudi možnost Slika 2: Kartica NI USB 6009 in razporeditev vhodno- pridobitve certifikata, ki podaja oceno o našem znanju. izhodnih priključkov Certifikati so razdeljeni v več nivojev zahtevnosti: • CLAD (Certified LabView Associate Developer) - 2.2 Alternativa DAQ karticam osnovno poznavanje okolja • CLD (Certified LabView Developer) - načrtovanje in Glede na to, da DAQ kartice niso ravno poceni, bi bil nakup razvoj osnovnih aplikacij večjega števila le-teh kar velik finančni zalogaj. Zato smo se • CLA (Certified LabView Architect) - načrtovanje in odločili za alternativo. Namesto DAQ kartice lahko uporabimo razvoj zahtevnejših aplikacij tudi poljubno razvojno ploščo, s katero zajamemo signale. Certifikat pridobimo tako, da bodisi odgovarjamo na Odločili smo se za platformo Arduino UNO, ki jo dijaki dobro vprašanja izbirnega tipa oz. rešujemo problemske naloge. Preden poznajo, saj jo uporabljajo tako pri pouku kot tudi pri izdelovanju opravimo preizkus znanja nam je na voljo tudi tečaj, ki nas zaključnih nalog. Prav tako je omenjena platforma enostavna za pripravi na tovrstne naloge. Na spletu je možno dobiti tudi veliko uporabo in cenovno ugodna. LabView tudi omogoča gradiva, ki nam je v pomoč pri učenju. programiranje Arduino plošče z uporabo posebnega Preden se dijaki lotijo učenja je dobro, da imajo vsaj programskega modula. V okviru našega poučevanja smo sami minimalno znanje s področja programiranja. Zaželeno je tudi napisali program za enostavno serijsko komunikacijo med osnovno poznavanje elektronike in načinov komunikacije. Zato Arduinom in računalnikom, na katerem je nameščen LabView. bi, za srednješolski nivo, LabView priporočali višjim letnikom (3. ali 4.) srednješolskega strokovnega izobraževanja (SSI) s 3 LABVIEW V OKVIRU POUKA področja elektrotehnike ali mehatronike. Poleg organiziranja različnih krožkov, tečajev in delavnic lahko 2.1 NI USB 6009 znanje LabView programiranja dijakom ponudimo tudi v okviru Programsko okolje LabView je kompleksno in omogoča pouka. Na ta način namreč vsi dobijo potreben vpogled v izdelavo najrazličnejših aplikacij. Poleg programske opreme tovrstno programiranje. Strokovni modul Regulacije, ki se 434 poučuje v 4. letniku programa Tehnik mehatronike, pri praktičnem delu predvideva tudi spoznavanje programskega okolja LabView. Dijaki se seznanijo z osnovnimi strukturami in koncepti grafičnega programiranja. V nadaljevanju bo predstavljen potek poučevanja LabView-ja pri praktičnem delu modula Regulacije. 3.1 Prvi LabView program Ko odpremo programsko okolje, se nam prikažeta dve okni. Prvo okno imenujemo čelna plošča (front panel) (Slika 3). Na njej so elementi, ki so vidni uporabniku končne aplikacije. To so npr. grafi, gumbi, indikatorji, polja za vnos in prikaz podatkov. V drugem oknu pa izdelujemo program v obliki blokov, zato to okno imenujemo tudi bločni diagram (block diagram) (Slika 4). V prvem delu z dijaki naprej skupaj izdelamo preprost program, ki ga nadgrajujemo in spoznavamo osnove. Program omogoča simuliranje nivoja tekočine. V kolikor je nivo nad zgornjo mejo ali pod spodnjo mejo, se pokaže rdeč indikator, sicer pa zelen indikator. Dodatno se prikaže obvestilo “nivo je izven meja” ali “nivo je znotraj meja.” Na primeru omenjenega programa razložimo različne podatkovne tipe, pogojni stavek, zanko itd. Slika 5: Žrebanje Loto (čelna plošča) 3.3 LabView in Arduino Namesto DAQ kartice lahko za zajemanje podatkov uporabimo kar razvojno ploščo Arduino [3]. Potrebno je napisati program, ki bo omogočal serijsko komunikacijo med Arduinom in računalnikom, kjer je nameščen LabView. Slika 3: Simulacija merilnika nivoja tekočine (čelna plošča) Slika 6: Razvojna plošča Arduino UNO Oglejmo si nekaj preprostih programov, ki nam omogočajo upravljanje z razvojno ploščo Arduino UNO (Slika 6) preko serijske komunikacije. V prvem primeru s pritiskom na virtualni gumb nadziramo kdaj se preberejo analogni vhodi in njihova vrednost prikaže na čelni plošči (Slika 7,8,9). Gumb lahko v drugem primeru Slika 4: Simulacija merilnika nivoja tekočine (bločni odstranimo in dosežemo konstantno branje analognih vhodov in diagram) prikaz vrednosti na grafu čelne plošče LabView-a. Dijaki pod mentorstvom učitelja nadaljujejo z izdelavo preprostih programov, ki vključujejo osnovne programske strukture. 3.2 Nadgradnja Ko utrdimo osnove, skupaj naredimo dva bolj kompleksna programa. Pri prvem je omogočena naključna izbira dijaka s podanega seznama, pri drugem pa program izžreba loto kombinacijo (Slika 5). Slika 7: Branje analognih vhodov (čelna plošča LabView) 435 Rezultati ankete so prikazani na grafih (Slika 11). Dijaki so ocenjevali praktično uporabnost okolja LabView. Večina jih LabView prepoznava kot praktično uporabno programsko okolje. Slednje pomeni, da so verjetno tudi dovolj motivirani za nadaljnje izobraževanje, kar je potrdilo 7 od 11 dijakov. Prav toliko dijakov bi si želelo tudi predstavitve praktičnih projektov iz industrije. Svoje znanje jih na lestvici od 1 do 5 kar 9 od 11 ocenjuje kot dobro (3), kar je smiselno, saj si po eni strani želijo nadaljnjega izobraževanja. Po drugi strani pa so v okviru pouka že spoznali osnovne koncepte LabView programiranja. Glede zahtevnosti je večina dijakov odgovorila, da se jim zdi LabView programiranje srednje zahtevno oz. zahtevno. Iz tega Slika 8: Branje analognih vhodov (bločni diagram lahko sklepamo, da so bili učni cilji postavljeni ustrezno oz. LabView) nekoliko višje, kar je dobro, saj se morajo zaradi tega dijaki bolj potruditi. Rezultati ankete nam kažejo, da je potrebno s poučevanjem LabView-a nadaljevati, saj je bilo programsko okolje med dijaki dobro sprejeto. Slika 9: Programska koda Arduino Upravljamo lahko tudi digitalne izhode Arduino plošče. Preko virtualnega gumba na čelni plošči lahko prižgemo in ugasnemo vgrajeno LED, ki se nahaja na enem izmed digitalnih izhodov (Slika 10). Slika 11: Rezultati ankete 5 ZAKLJUČEK Predstavljeno je bilo poučevanje programskega okolja LabView. Zaenkrat le-to poteka zgolj pri praktičnem delu strokovnega modula Regulacije. Načrti za prihodnosti so sledeči. Za dijake bomo organizirali Slika 10: Vklop/izklop LED (čelna plošča LabView) LabView krožek. LabView vsebine bodo na voljo na Dnevih za vedoželjne. V preteklem letu smo jim to že ponudili in odziv je 4 REFLEKSIJA bil relativno dober, vendar za bolj poglobljeno delo ni bilo dovolj časa. So pa dijaki dobili dober vpogled. Dijake 4. letnikov programa Tehnik mehatronike smo po koncu Povezali so bomo s podjetjem National Instruments, ki trži pouka povprašali kakšno je njihovo mnenje o programskem programsko in strojno opremo in se pogovorili o možnostih za okolju LabView. Preko ankete na MS Forms smo jim zastavili sodelovanje. nekaj preprostih vprašanj izbirnega tipa. Anketo je izpolnilo 11 Spodbudili bomo dijake za uporabo LabView-a pri izdelavi dijakov. zaključnih nalog. 436 Predstavili jim bomo realen projekt iz industrije, kjer je bilo LITERATURA IN VIRI uporabljeno omenjeno programsko okolje. Na ta način jih bomo dodatno motivirali za učenje. [1] National Instruments www.ni.com, pridobljeno 20. 8. 2020 Menimo, da je poznavanje programskega okolja LabView [2] Data acquisition vsekakor dobrodošlo, zato bomo nadaljevali z njegovim https://en.wikipedia.org/wiki/Data_acquisition, pridobljeno poučevanjem in izvajanjem izobraževalnih dejavnosti. 20. 8. 2020 [3] Arduino www.arduino.cc, pridobljeno 20. 8. 2020 437 Programska koda kot izrazni medij ustvarjalnosti v izrednih razmerah Program code as an expressive medium of creativity in emergency situations Davorin Babič Srednja medijska in grafična šola Ljubljana Pokopališka ulica 33 1000 Ljubljana, Slovenija davorin.babic@smgs.si POVZETEK process. With a relatively satisfactory information and communication infrastructure with access to a wide range of Izobraževanje na daljavo je v času koronavirusa slonelo na different online learning environments and tools, some teachers sodobnih informacijskih tehnologijah, ki so zagotavljala tried to encourage students to fill part of their time with activities prostorsko in/ali časovno neodvisnost ključnim deležnikom v through systematic and structured management of the learning izobraževalnem procesu. Ob relativno zadovoljivi process through practical applications and creative media informacijsko-komunikacijski infrastrukturi z dostopom do practices. which are pushed to the periphery during the normal širokega nabora različnih spletnih učnih okolij in orodij, smo course of life, e.g. with contemporary media generative art. The nekateri učitelji s sistematičnim in strukturiranim vodenjem paper presents the activities that we carried out within the učnega procesa med drugim prek praktičnih aplikacij in professional module creative coding in the selected learning ustvarjalnih medijskih praks skušali dijake spodbujati, da del situation with the aim of empowering students in developing svojega časa zapolnijo z dejavnostmi, ki jih v času običajnega computer thinking to understand the role of new technologies in poteka življenja odrivajo na obrobje, npr. s sodobno medijsko the process of creating computer algorithmic art. After the generativno umetnostjo. V prispevku so predstavljene aktivnosti, learning situation, based on the evaluation of products, we found ki smo jih znotraj strokovnega modula kreativno kodiranje v that connecting certain programming concepts with the basic izbrani učni situaciji izvedli s ciljem opolnomočenja dijakov v principles of fine arts through appropriate programming razvijanju računalniškega mišljenja za razumevanje vloge novih language allowed students to develop their personal style to tehnologij v procesu ustvarjanja algoritmične računalniške create static digital visualizations and dynamic, interactive or umetnosti. Po opravljeni učni situaciji smo na osnovi evalvacije animation visual arts projects, but at the same time understand izdelkov ugotovili, da je povezovanje določenih konceptov the algorithmic way of thinking and thus get to know and programiranja z osnovnimi načeli likovne umetnosti prek consolidate the ability to solve problems in a given field. ustreznega programskega jezika dijakom omogočilo razviti svoj osebni slog za ustvarjanje tako statičnih digitalnih vizualizacij KEYWORDS kot dinamičnih, interaktivnih ali animacijskih projektov vizualne umetnosti, a hkrati razumeti algoritmični način mišljenja ter tako Computational thinking, algorithmic thinking, computational spoznavati in utrjevati zmožnosti reševanja problemov danega concepts, programming basics, principles of art and design področja. KLJUČNE BESEDE 1 UVOD Računalniško mišljenje, algoritmično mišljenje, računalniški Izredne razmere, ki jih je povzročila epidemija novega koncepti, osnove programiranja, načela likovnega snovanja in koronavirusa, so celotno izobraževalno sfero nedvomno oblikovanja postavile v povsem nove okoliščine, kjer so bili njeni ključni deležniki prostorsko oziroma časovno ločeni. Sodobne ABSTRACT informacijske tehnologije in novi mediji so v veliki meri postali At the time of the coronavirus, distance learning was based on osrednji vir znanja na šolah za kakovostno izvajanje modern information technologies that ensured spatial and / or izobraževanja na daljavo. Njihova integracija in učinkovita raba temporal independence for key stakeholders in the educational v učnem procesu, ob zadovoljivi informacijsko–komunikacijsko infrastrukturi, sta omogočala razvoj ustvarjalnega učenja in inovativnih metod poučevanja. Dostopnost do izbranih informacij v realnem času in velik nabor različnih spletnih učnih okolij sta bila osrednjega pomena. To je ob smiselno Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed organiziranih učnih vsebinah učiteljem omogočalo uporabo for profit or commercial advantage and that copies bear this notice and the full različnih spletnih orodij in elektronskih gradiv pri pouku za citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). sistematično in strukturirano vodenje učnega procesa ter Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia povezovanje s sodelavci, hkrati pa je dijake iz pasivnega © 2020 Copyright held by the owner/author(s). 438 postavilo v aktivnejši položaj, predvsem v smislu ustno in praktično. Ustno ocenjevanje je obsegalo večinoma intenzivnejšega vzpostavljanja medvrstniške komunikacije in odgovore na kontekstna vprašanja znotraj posameznih učnih bolj kreativne rabe spletnih orodij. Raziskava ZRSŠŠ [1] je sicer sklopov modula. Praktično ocenjevanje je zajemalo praktične pokazala, da so učitelji kot prevladujoči način izvajanja pouka izdelke in rešitve avtentičnih nalog, ki so jih dijaki shranjevali v navedli kombiniranje pouka z videokonferencami in usmerjanje digitalno tehnično mapo projekta, kjer so poleg kontekstualne učenja prek pisnih navodil. Ob uporabi raznolikih metod je vsebine posamezno, v paru ali skupinsko beležili napredek, ocenjevanje doseganja standardov znanja in učnih ciljev težave in načine reševanja zastavljenih problemov, opisali potekalo večinoma ustno prek videokonferenc, kot tudi strategije za njihovo reševanje in inovacije, ki so morda pri tem ocenjevanje praktičnih izdelkov in avtentičnih problemov. nastale. Po končanem učnem sklopu so dijaki za tehnično mapo V času negotovosti in socialne distanciranosti, ko so projekta prejeli oceno praktičnega izdelka. izobraževalne ustanove zaprle vrata in smo šolniki in šolajoči obtičali doma, smo nekateri med drugim ohranjali medsobojne povezave prek praktičnih aplikacij in ustvarjalnih medijskih 2 METODA DELA praks. Kot odziv na ohranjanje žive komunikacije ob hkratnem 2.1 Izpeljava učne situacije usvajanju učnih vsebin, smo dijake spodbujali, da del svojega Eden pogosto najzahtevnejših vidikov poučevanja in učenja časa zapolnijo s spoznavanjem sodobne medijske generativne osnov programiranja je najti zanimive vsebine, ki niso le zabavne umetnosti, natančneje z digitalno generativno postopkovno in navdušujoče, ampak tudi ponazarjajo obravnavano temo. V grafiko. Ustvarjanje te sodi v algoritmično računalniško našem primeru je ta vključevala računalniško manipulacijo umetnost, katere jedro sloni na postopku, s katerim opišemo različnih konceptov, ki so osnovni gradniki računalniške grafike: potek nastajanja digitalne slike v obliki navodil za računalnik točke, črte in oblike; teksture in barve; čas, z njim povezane (konceptualni model slike je vgrajen v algoritem ali program). spremembe osnovnih gradnikov in gibanje; reaktivnost, Sliko nato računalnik generira sam po navodilih, ki smo jih povezljivost in povratne informacije. Iskanje motivacije, izbira zapisali v programu. Na podlagi ustreznih navodil lahko ustreznega programskega jezika, opravljanje miselnih priprav, računalnik izdela množico slik – variacije o določeni temi v stilu, postavljanje ciljev, dodajanje nekaterih omejitev, skiciranje ki ga vgradimo v program. V nasprotju s koncepti klasične podrobnosti in kodiranje generativne postopkovne grafike so bile umetnosti sodobna medijska umetnost s svojim interaktivnim aktivnosti, ki so determinirale vsebino omenjene učne situacije. značajem vzpostavlja dvosmerno komunikacijo med Cilj učne situacije je bil združiti teorijo in metodologijo iz ustvarjalnim delom in gledalcem, torej uporabnikom. računalništva z načeli estetike in teorije vizualnih medijev, Pri strokovnem modulu kreativno kodiranje [2] smo v ta kreativno prakso, pedagoškimi pristopi iz likovne in grafične namen znotraj učne situacije Spoznavanje osnov programskega umetnosti ter vizualne kulture. Vsaka vsebinska enota je jezika JavaScript izvedli šest vsebinskih enot v predvidenem vključevala gradivo, osredotočeno na generativno umetnost in časovnem obsegu sedmih didaktičnih enot. Vsebinske enote so oblikovalske koncepte. Dijaki so se vključevali v koncepte tako, zajemale običajne ustvarjalne pristope in sodobne oblikovalske da so se učili iz obstoječih primerov in nato usvajali ustrezne prakse, ki jih medijski tehniki lahko uporabljajo v svojem učnem tehnične spretnosti za izdelavo digitalne generativne procesu, vključno z osnovami statičnega generativnega snovanja postopkovne grafike, ki je prikazovala določen koncept. S tem so (uporaba programskih konstruktov za ustvarjanje različnih hkrati vadili in utrjevali bistvene koncepte, ne le v sodobni enostavnih ali zapletenih vizualnih rezultatov iz enega dela medijski generativni umetnosti, temveč tudi v računalniškem napisane programske kode), dinamičnega snovanja (uporaba mišljenju, oblikovanju preprostih algoritmov in programiranju. programske kode za ustvarjanje dinamičnih vizualnih Prva enota je dijakom omogočila, da so začeli razvijati svoj komunikacij, ki se lahko spreminjajo s časom ali se odzivajo na umetniški in oblikovalski besednjak skupaj z uvajanjem v vstopajoče podatke) in interakivnega snovanja (uporaba razvojnem okolju in programsko sintakso. Druga enota je programske kode za ustvarjanje vizualnih rezultatov, ki so temeljila na nadgradnji ustvarjalnega besednjaka in dijakom prilagodljivi in vezani na odziv na dogodke uporabnika, omogočala, da so vadili svoje osnovne programerske spretnosti. povezane z uporabo miške ali tipkovnice). Omenjena učna Tretja enota je omogočala raziskovanje razlik med digitalno situacija se je v vsebinskem kontekstu opirala na ponavljanju in generativno umetnostjo z uporabo naključnih števil in izpopolnjevanju temeljnih programerskih konceptov in ponavljajočih se naključnih dogajanj ter klasično zasnovanih programiranju v izbranem besedilnem programskem jeziku z ustvarjalnih pristopov v tovrstni grafiki. V tej enoti smo med ustvarjalnimi vajami in majhnimi projekti. V ta namen so dijaki drugim uvedli tudi uporabo matematičnih funkcij (parametrično raziskali koncepte spremenljivk, uporabo več stavkov (ukazov) podane krivulje), da bi dijakom omogočili ustvarjanje organskih programske kode v določenem zaporedju (pomebnost vrstnega oblik. Dijaki so nadgrajevali svoje znanje iz programiranja s tem, reda), sprejemanje odločitev (vejitve) in ponavljanje istega da so razširili nabor rabe konstruktov za nadzor normalnega toka procesa (zanke), modularne strukture (uporabniške funkcije), programa pri ustvarjanju svojih umetniških del. Četrta enota je geometrijske transformacije na slikovni ravnini digitalnega predstavljala temeljne umetniške in oblikovalske koncepte, ki so platna, delo z nizi in s seznami, z objekti in z razredi ter s se nanašali na dojemanje informacij, pridobljenih iz svetlostnih funkcijami s programiranjem večpredstavnosti, kot so digitalna razlik na slikovni ploskvi digitalnega platna in njegove teksture. slika, digitalni zvok, digitalni video, digitalna animacija in Dijaki so nadgrajevali svoje znanje na rabi in razumevanju zank interaktivnost. (tudi vgnezdenih), za ustvarjanje strukturalnih lastnostit nastale Aktivnost dijakov oz. njihove učne obveznosti, ob digitalne grafike. Peta enota je dijake seznanila z digitalno morebitnem vključevanje drugih programskih enot, ki so bile del predstavitvijo slik in fotografij. Njen namen je bil spodbuditi ocenjevanja znanja ali pogoj za ocenjevanje znanja, smo izvedli dijake, da so s svojimi pametnimi telefoni posneli sebe ali 439 zanimive predmete v bližnji okolici in jih nato na kreativen način koncepte in konstrukte programiranja, povezane z likovno programsko spreminjati. Vključevanje ustvarjalnih praks popart kompozicijo in načeli likovnega reda. Cilj takšnega pristopa je umetnosti so združevale ustvarjalnost s tehnologijo, hkrati pa so bil prinesti navdušenje, ustvarjalnost in inovacije, ki jih spodbuja dijaki vadili in poglabljali razumevanje zank in seznamov. kontekst kreativnega kodiranja. Zadnja, šesta enota, je uvedla nekaj načel animiranja spletnih animacij z namenom dijakom pomagati ustvariti prepričljivejše 2.4 Programski jezik p5.js ter spletni učni okolji animacije. Uvedeni so bili nekateri naprednejši programerski editor.p5js in peblio.co koncepti, kot so objekti in razredi, ki so dijakom omogočali, da Relativna enostavnost učenja programskih jezikov na področju vidijo zmogljivejše podatkovne strukture v akciji. digitalne generativne vizualizacije, med katere nedvomno sodi p5.js, omogoča dostopnost besedilnega kodiranja v različnih 2.2 Pedagoško-didaktične ustreznosti učne disciplinah medijske produkcije. p5.js je JavaScript knjižnica s situacije široko paleto dodatnih programskih grafičnih knjižnic, ki v V praksi kreativnega kodiranja se algoritmična abstrakcija in svojem jedru ponuja preprost API (vmesnik za namensko slikovna konkretizacija združita v iterativni delovni proces. programiranje) za izrisovanje v strukturnem elementu Algoritemsko generirana digitalna slika je zato dvoplastna, v njej spletnega standarda HTML 5. Element < canvas> si lahko se prekrivata abstraktni formalizem in konkretna vizualizacija. predstavljamo kot digitalno slikarsko platno spletnih razvijalcev, Abstraktni formalizem, ki izraža pravilnost semantike ki omogoča prikazovanje dvorazsežne računalniške grafike, programskih stavkov, se v konkretni vizualizaciji kaže kot lik, izdelovanje spletnih animacij ter vključevanje zvočnih in video oblika, forma, barva, tekstura, ritem, kontrast, gibanje itd. vsebin, s čimer je zagotavljena večpredstavnostna Nastalo razmerje med abstrakcijo v programski kodi in funkcionalnost. Sintaksa med JavaScriptom in p5.js je identična, konkretizacijo v digitalni vizualizaciji naloge je dijakom na toda p5.js doda abstrakcije za grafiko in interaktivnost. Dijakom področju ustvarjalnosti omogočilo razumevanje artikulacije omogoča, da se po nekaj zaporednih vrsticah hitro potopijo v njene vsebine ter interpretacijo posamezne rešitve. Zato so programiranje, ki ustvarja sprotne vizualne rezultate. Zaradi vsebinske enote v uvodu vsebovale ali vsaj nakazale poti do razmeroma nizke krivulje učenja pomaga motivirati za nadaljnje pregleda zgodovine in prakse generativne umetnosti ter učenje jezika. Poleg tega p5.js pomaga dijakom bolje razumevati računalniške ustvarjalnosti s poudarkom na formalnih in razvijati nekatere logične spretnosti, povezane s paradigmah in algoritmih, ki so se uporabljale za generiranje programiranjem, ne da bi od njih zahtevali, da razvijejo toliko umetniških del generativne umetnosti, katera so dijakom tehničnega znanja kot mnogi drugi programski jeziki. Tak način ponujala priložnosti za reinterpretacijo in osebno ustvarjanje. razmišljanja je dijakom dragocena kompetenca za ustvarjalni Pedagoško-didaktične ustreznosti omenjene učne situacije so razvoj. Če združimo vse našteto skupaj, lahko dijaki razmeroma v učnem procesu obsegale naslednje pristope: strukturirani hitro in enostavno uporabijo programski jezik p5.js z namenom zaporedni vsebinski moduli, različne stopnje zahtevnosti razvijati kreativne in inovativne projekte, povezane z medijskimi reševanja problemov, navodila za izvedbo, ki jih je bilo študijami, ki ponujajo mešanico teorije in prakse. Osnovni enostavno razumeti, potrebno minimalno branje predstavljene pristop v razvoju urejevalnika namreč temelji na ideji o teorije, uporaba zanimivih in ustreznih primerov, možnost skiciranju. Tako kot je skiciranje mogoče razumeti kot takojšnje povratne informacije, učenje v ritmu z lastnim tempom minimalen pristop k risanju z namenom hitrega oblikovanja neke in daljinsko spremljanje dela dijakov, individualno delo. ideje, je tudi jedro p5.js zasnovano na konceptu pisanja Takšen način poučevanja zahteva uvedbo daljših in krajših minimalne količine kode, s katero svoje vizualne, interakcijske projektnih nalog ter njihov nadzor. ali animacijske ideje prenesemo na zaslon. Potrebe po namestitvi posebnega integriranega razvojnega 2.3 Kreativno kodiranje v konceptu splošne okolja IDE ni, saj p5.js premore precej dober in popoln spletni medijske umetnosti urejevalnik, ki se nahaja na spletnem naslovu editor.p5js.org Splošna medijska umetnost v srednješolskem izobraževanju je (Slika 1). Ob ustreznem vpisu in kasnejših prijavah v samem relativno nova pot v raziskovanju rabe programiranja za spletišču so dijaki pisali in poganjali izvorno kodo v lastnem ustvarjalno izražanje v digitalnem mediju. Vsestranskost spletnem brskalniku, jo ustrezno shranjevali v programskih kreativnega kodiranja medijskemu tehniku med drugim omogoča skicirkah, ki so jih glede na vsebino učne enote združevali v ustvarjanje izraznih del digitalne umetnosti. Učenje programskih zbirke, za povrh pa so zraven lahko naložili še slikovne datoteke, jezikov kreativnega kodiranja je bistvenega pomena za izražanje seveda v omejeni velikosti. Osnovni funkciji, ki tvorita v digitalnih medijih, ki ima vse večji pomen za mladino in družbo pomensko strukturo programske skicirke, v katerima opišemo na splošno, saj smo skozi pridobljeno prakso znotraj programske določene postopke brez vračanja rezultatov, sta funkciji setup() enote ugotovili, da ne gre samo za pasivni ogled ali predvajanje in draw() (Slika 2a). p5.js ti funkciji kliče v določenem zaporedju. digitalnih medijev, temveč tudi za konstruktivno izkušnjo, s Funkcijo setup() postavimo na začetek naše programske kode in pomočjo katere je mogoče vzpostaviti povezave z umetnostjo. se zažene samo enkrat na začetku programa. V njej inicializiramo Kreativno kodiranje je zelo interdisciplinarno zasnovano začetno grafično stanje svojega ustvarjalnega okolja v področje, ki združuje osnove računalništva z estetskimi načeli in programski skicirki. Funkcija draw() se prikliče neposredno po kreativnimi praksami iz umetnosti in oblikovanja. Dijaki so se s izvedbi funkciji setup() in vsa koda v njeni notranjosti se pomočjo programskega jezika p5.js urili v računalniškem neprestano izvaja (privzeto 60-krat na sekundo), dokler se mišljenju, povrh pa so ustvarili digitalni portfelj estetsko izvajanje programa ne ustavi (npr. z uporabo ukazov exit() ali zasnovanih generativnih vizualizacij, ki so vključevale osnovne noLoop()) . 440 Ustrezni nabor 2D grafičnih geometrijskih primitivov z natančno semantično opredelitvijo (točka, črte (daljice in krivulje), nekateri liki (trikotniki, štirikotniki in elipse)) nudi ustrezno grafično okolje s potrebnimi funkcionalnostmi za ustvarjanje v spletnem brskalniku. Poglobljeno spoznavanje lastnosti in zmogljivosti programskih gradnikov ter njihovo uspešno aplikacijo za ustvarjanje digitalne generativne postopkovne grafike so dijaki pridobivali na izvornem spletnem naslovu https://p5js.org. Različne spletne učne platforme, podprte z multimedijskimi gradniki in interaktivnimi nalogami dijakom omogočajo uporabo različnih oblik in metod za predstavitev kvalitativnih in deloma kvantitativnih podatkov, pa tudi zaključkov ob ustreznih rešitvah. V našem primeru smo dijakom ustvarili prilagodljivo spletno Slika 1: p5.js spletni urejevalnik, dostopen na naslovu učno okolje Peblio (Slika 3), dosegljivem na spletnem naslovu editor.p5js.org https://www.peblio.co, v katerem so ustvarjali v svojem tempu Poleg osnovnih strukturnih funkcij setup() in draw() se in imeli dovolj časa za učenje. Izbrali smo večpredstavnostna velikokrat uporablja funkcijo preload(). Ta priročna funkcija gradiva, ki spodbujajo pridobivanje in utrjevanja znanja. Z zagotavlja, da se digitalne slike ali drugi zunanji podatkovni digitalnimi orodji smo ustvarili interaktivne učne enote, objekti, končajo z nalaganjem v programski skicirki, preden se združljivimi za delo v vseh operacijskih platformah in spletnih pokličeta funkciji setup() in draw() (Slika 2b). brskalnikih. Slika 3: Spletno učno okolje Peblio Sprotno ustvarjanje in organiziranje predavanj, vaj in nalog, učinkovito posredovanje povratnih informacij in preprosto komunikacijo z dijaki smo dosegli na dva načina: z uporabo učnega okolja Googleove učilnice in s skupno rabo povezav znotraj omenjenega učnega okolja Peblio. Pri uporabi Googleove učilnice se je posamezni razred prijavil z ustreznim računom, interaktivne učne liste pa smo delili neposredno razredu s pritiskom na ustrezni gumb. Enako dinamiko smo lahko dosegli z deljenjem povezav naprej in nazaj. Kopirali smo povezavo do shranjenega interaktivnega učnega lista in jo delili po e-pošti ali znotraj uporabljenih komunikacijskih kanalov. Prek deljene povezave so Slika 2: Diagram poteka izvajanja kode v programski dijaki dostopali do interaktivnih učnih listov, ki so vsebovali skicirki p5.js brez prednaloženih zunanjih podatkovnih izvlečke predavanj, demonstracijskih vaj in kreativnih nalog. Ko objektov (a) in s prednaloženimi (b). Za pomensko so opravili tedensko določene naloge, so jih lahko odložili v učne strukturo in oblikovani izgled vizualizacije vsebine liste in nam nazaj delili svoje povezave. programske skicirke v spletnem urejevalniku skrbita Podrobnejša navodila za delo v predstavljenem spletnem vnaprej vzpostavljeni datoteki index.html in style.css. okolju se nahajajo na spletnem naslovu https://demo.peblio.co/. Spremenljivke so deklarirane s ključnima besedama var ali let. Obseg spremenljivk, deklariranih z var je globalni ali 3 REZULTATI IMPLEMENTACIJE funkcijski, medtem ko je obseg spremenljivk, deklariranih z let, POVEZOVALNIH KONCEPTOV lokalni. 441 Za usvajanje računalniškega mišljenja smo dijakom pripravili večkotnikov in črt (daljic), podlago za didaktične aktivnosti, prek katerih so usvojili ustvarjalna estetika osnovne programerske koncepte. Obseg in zaporedje v učni situaciji uporabljenih programerskih konceptov so determinirali vrstni red predstavljenih tehnik kreativnega kodiranja (Tabela 1). Vsebinske in tehnične prilagodljivosti znotraj posameznih učnih Rezultati preverjanja in ocenjevanja implementacije enot so dijakom omogočale, da so svoje ustvarjalne spretnosti povezovalnih konceptov skozi ustvarjene digitalne portfelje usmerili v sestavljanje tako preprostih kot zapletenih estetsko zasnovanih generativnih vizualizacij so pri 92 dijakih iz računalniških programov v ustvarjanju digitalne generativne populacije 136 dijakov (celotni tretji letnik na smeri medijski postopkovne grafike. Cilj, ki smo si ga zadali doseči, je obsegal tehnik) pokazali doseganje sposobnosti za reševanje tri stopnje: najprej smo dijakom predstavili osnove besedilnega kompleksnejših in zahtevnejših kreativnih nalog, doseganje programiranja in računalniškega mišljenja skozi učenje višjih ravni znanja, pridobivanje sposobnosti za povezovanje predstavljenega programskega jezika; nato smo izpostavili znanj z različnih strokovnih področij, razvijanje računalniškega scenarije, kje in kdaj je mogoče kodiranje uporabiti za skiciranje mišljenja in ustvarjalnosti. Preostali dijaki so delno (tudi konceptualnih idej in razvoja delujočih prototipov programske naključno) izpolnili zahteve po izdelavi kreativnih nalog in kode, ki se osredotočajo na izrazne medije; na koncu smo dijake digitalnega portfelja; najpogostejši navedeni vzrok je bil slabša spodbujali, da so razumeli etiko odprte kode z uporabo kode, ki internetna povezava ter zato posledično neaktivna udeležba na je na voljo na spletu, in s sprostitvijo in dokumentiranjem svojega videokonferenčnih prenosih predavanj in nepravočasna oddaja projekta z istim pristopom. izdelkov v pregled, zato smo pri njih iskali doseganje minimalnih Tabela 1: Povezovalni koncepti računalniškega mišljenja z standardov znanja. likovno vizualizacijo Predstavljeni sliki (Slika 4 in Slika 5) prikazujeta primere Osnovni programerski Tehnike kreativnega rabe različnih povezovalnih konceptov v ustvarjanju digitalne koncepti kodiranja generativne postopkovne grafike in sodijo v digitalni portfelj Vgrajene funkcije risanja, dijaških izdelkov. Osnove programiranja v osnovni liki (grafični izbranem programskem jeziku primitivi), koordinatni / okolju sistemi, načela kreativnega kodiranja Spremenljivke, podatkovni Risanje v ustreznem merilu, tipi, izrazi, stavki sorazmernost razdalj med grafičnimi primitivi Interakcije, ustvarjene s Liki in oblike, grafično klikom na miško ustvarjene z miško Uporaba preprostih iteracij za izrisovanje velikega števila Krmilne strukture in vejitve različnih likov in grafičnih oblik, uporaba pogojnih stavkov v preprostih simulacijah, rekurzija Izrisovanje parametrično Modularnost: pisanje funkcij, podanih grafičnih oblik:lega, z vsebovanimi krmilnimi velikost, barva obrobe in strukturami in generatorji polnila itd., naključno naključnih števil ustvarjene kompozicije na Slika 4: Raba preprostejših povezovalnih konceptov digitalnem platnu Kompleksnejše strukturne likovne kompozicije z mnogo Seznami in nizi različnimi oblikami (predmeti), shranjenimi v seznamih Uporaba matematičnih Kompleksnejše abstraktno / konceptov: kotne funkcije, geometrijsko oblikovanje, geometrijske transformacije strukturne likovne na ravnini kompozicije pravilnih 442 srečanj. Dijaki so lahko preizkušali in eksperimentirali z usvojenimi pojmi v tedenskih nalogah in v zaključni skupinski (predvsem v paru) predstavitvi, ki je nudila prostor za kreativno izražanje, raziskovanje in nadaljnje učenje. Predavanja v obliki demonstracij so bila strukturirana tako, da so čim bolj spodbujala interakcijo. Kodiranje v “živo” in praktični prikazi vaj so v dijakih vzbujali dvome in radovednosti glede tematske vsebine predavanja. Dijaki so tako lahko znotraj spletnega učnega okolja hitro preskusili svoje ideje, in posegali po pomoči učitelja, če niso razumeli določenih konceptov. Predstavljene študije primerov, ki so prikazovale kreativno rabo kode kot izraznega medija, so postale navdih za kasnejše ustvarjalno vzdušje. Poleg uvedbe programske kode v procesu ustvarjanja digitalne generativne postopkovne grafike in premagovanja tehničnih izzivov se z raziskovanjem individualnih in projektov v paru zdi samoumevno, da je kreativno kodiranje povzročilo večjo ustvarjalnost dijakov glede na doseženo stopnjo izvirnosti pri vsakem praktičnem izdelku. Iz navedenega je razvidno, da je bil obseg učne situacije v svoji ponovljivosti prilagodljiv in razširljiv: učitelji smo lahko skrajšali ali razširili vsebinsko strukturo odprtega kurikula glede Slika 5: Raba zahtevnejših povezovalnih konceptov na posebne okoliščine in s tematsko izbranimi vsebinami izpolnjevali njegove splošne cilje – uporabo kreativnega kodiranja v procesu reševanja problemov, oprtih na izrazne 4 ZAKLJUČEK zmožnosti sodobne medijske umetnosti. V prispevku smo predstavili dejavnosti v okviru izpeljave učne situacije, namenjene poučevanju medijskih tehnikov osnov besedilnega programiranja v programski knjižnici in naboru VIRI orodij p5.js, ki olajšajo uporabo programskega jezika JavaScript [1] Rupnik Vec, T. in Slivar, B. (7. 7. 2020). Izobraževanje na za kreativno kodiranje. Dijaki so skozi učne aktivnosti utrjevali daljavo v času epidemije Covid-19 v Sloveniji. Zavod RS način postopkovnega mišljenja, se sporazumevali o kodiranju in za šolstvo. Pridobljeno na ga usvajali v okviru svojih ustvarjalnih delovnih procesov. https://www.zrss.si/objava/izobrazevanje-na-daljavo-v- Poleg tega so dijaki ponovili, kako lahko strukturni elementi casu-epidemije-covid-19-v-sloveniji HTML in slogovni elementi CSS komunicirajo s p5.js, da v celoti [2] Babič, D. (2019). Kreativno kodiranje v medijski izkoristijo razvoj vsebine za brskalnik. produkciji. V U. Rajkovič, B. Batagelj (ur.), Zbornik 22. Učna situacija se je opirala na izbiro tehnologije, ki je Mednarodne multikonference Informacijska družba. dijakom pomagala ublažiti krivuljo učenja z zagotavljanjem Zvezek J. Ljubljana: Institut »Jožef Stefan«. Pridobljeno na http://library.ijs.si/Stacks/Proceedings/InformationSociety/ sprotnih vizualnih povratnih informacij. Učne vsebine smo 2019/IS2019_Volume_J%20-%20VIVID.pdf posredovali prek videkonferenčnih prenosov znotraj predstavljenih spletnih okolij v obliki demonstracij in projektnih 443 E-učenje na dokazih podprte zdravstvene nege E-learning for evidence based nursing Alenka Baggia, Robert Saša Mlakar, Katja Pesjak Manuel Lillo-Crespo, Jorge Leskovar, Branislav Šmitek, Fakulteta za zdravstvene vede Angele Riquelme Galindo Uroš Rajkovič Boškin Faculty of Health Sciences, Univerza v Mariboru, Fakulteta za Spodnji plavž 3 University of Alicante organizacijske vede 4271 Jesenice, Slovenija Carretera San Vicente Kidričeva cesta 55a smlakar@fzab.si del Raspeig s/n 4000 Kranj, Slovenija alenka.baggia@um.si ES-03690 San Vicente del Raspeig, Alicante, Spain manuel.lillo@ua.es Christine FitzGerald Lucia Cadorin Barbara Narduzzi, Sara Department of Nursing & Midwifery, Udine University Scarsini Faculty of Education & Health Viale Ungheria 20 Azienda Sanitaria Universitaria Friuli Sciences IT-33100 Udine, Italy Centrale Health Sciences Building, North lucia.cadorin@uniud.it Via Pozzuolo n. 330 Bank Campus, University of IT-33100 Udine, Italy Limerick, IE-Limerick, Ireland barbara.narduzzi@asufc.sanita.fvg.it christine.fitzgerald@ul.ie POVZETEK KLJUČNE BESEDE Znanstveni dokazi so zlato pravilo v primeru intervencij, ki jih izvajajo medicinske sestre, vendar pa medicinske sestre niso Na dokazih podprta zdravstvena nega, e-učenje, zdravstvena vedno usposobljene in vajene dela na osnovi raziskovalnih nega, projekt ProCare dokazov. Mednarodni izobraževalni programi s področja ABSTRACT zdravstvene nege, še posebej v trenutni situaciji, zahtevajo implementacijo v spletnem okolju. Platforme za spletno Scientific evidences are intended to be the gold standard for izobraževanje s svojimi raznolikimi aktivnostmi učinkovito nursing professional interventions, although nurses worldwide podpirajo učenje na dokazih podprte zdravstvene nege. V are not always trained and accustomed to working on the basis prispevku predstavljamo prototip spletne učilnice na platformi of this research evidence. International nursing education Moodle, ki je nastala v okviru projekta ProCare financiranega s programs, especially in the current situation, require strani Evropske komisije. Spletna učilnica vključuje različne implementation in an online environment. Online education interaktivne vsebine in aktivnosti. Poleg osnovnih aktivnosti, ki platforms effectively support evidence-based nursing through the jih ponuja Moodle, so dodane tudi aktivnosti, ki jih omogočata diversity of online activities. In this paper we present the vtičnika BigBlueButton in H5P. Na osnovi prikazanega prototipa prototype of an online classroom on the Moodle platform, which se izvajalci tečaja lažje odločajo o najprimernejšem načinu za was developed within the ProCare project funded by European prikaz posamezne tematike. V nadaljevanju nameravamo v Comission. The online classroom comprises a variety of spletno učilnico vključiti tudi koncept igrifikacije, ki udeležence interactive content and activities for the implementation of izobraževanj dodatno motivira, ter možnost dostopa do evidence-based nursing education. In addition to the basic virtualnega namizja s statističnimi orodji. activities offered by Moodle, there are also activities made possible by the BigBlueButton extension and the H5P plugin. Based on the prototype presented, it will be easier for course providers to choose the most appropriate way of presenting an individual topic. For the future we plan to expand the online classroom with the concept of gamification, which will provide additional motivation of the participants and the possibility of Permission to make digital or hard copies of part or all of this work for personal or accessing the virtual desktop with statistical tools. classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must KEYWORDS be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Evidence based nursing, e-learning, nursing, ProCare project © 2020 Copyright held by the owner/author(s). 444 1 UVOD okviru katerega so pripravili nekaj izobraževalnih vsebin v obliki Izobraževanje na vseh področjih je vedno bolj prisotno na spletu. spletnih tečajev. Različne prosto dostopne spletne platforme kot tudi specifične V nadaljevanju prispevka predstavljamo nekaj inovativnih interne spletne učilnice ponujajo raznolik nabor predstavitev, pristopov, ki jih je mogoče uporabiti kot metodo za učenje na aktivnosti in možnosti izmenjave mnenj sodelujočih v procesu dokazih podprte zdravstvene nege. izobraževanja. Na podoben način kot ostala področja, se razvija tudi podiplomski študij zdravstvene nege. V poročilu s srečanja 2.1 Skupnost praks Sekcije za informatiko v zdravstveni negi [1] je podan tudi sklep, Koncept skupnosti praks (ang. Community of Practice) se da se mora e-izobraževanje uveljaviti kot oblika formalnega, uveljavlja tudi na področju zdravstva. Skupnost praks je skupina vseživljenjskega in samoizobraževanja medicinskih sester. ljudi, ki si izmenjujejo mnenja o določenih tematikah in idejah Predhodne raziskave kažejo, da je e-učenje na področju na ta način krepijo svoje izkušnje [13]. Kot navaja [14] lahko informacijskih sistemov s pomočjo spletne učilnice in skupnost praks pomaga tako pedagogom kot študentom pri videokonferenčnega sistema enako učinkovit način učenja kot kompleksnem izobraževanju s področja zdravstva. Skupnosti klasična avditorna predavanja [2]. Podobno kot študij sestavljajo učitelji in študenti. V nekaterih primerih e- informacijskih sistemov, tudi področje študija zdravstvene nege izobraževanja se formirajo tudi virtualne skupnosti praks, v zahteva zbiranje, predstavitev, vizualizacijo in interpretacijo okviru katerih se razprave in izmenjave izkušenj na določenem podatkov. Vse to vodi v prakso, ki temelji na dokazih. Na področju izmenjujejo v spletnem okolju. Tovrstne skupnosti se dokazih podprta zdravstvena nega je proces, v katerem že oblikujejo in funkcionirajo, kot na primer skupnost v okviru medicinska sestra pri obravnavi pacienta sledi petim korakom: 1. projekta Palliare [15]. postavitev pravega vprašanja; 2. iskanje najboljših dokazov za odgovor na vprašanje; 3. evalvacija dokazov; 4. implementacija 2.2 Bralni klub izbranih dokazov v klinično prakso, ki vključuje predhodno Srečanja bralnih klubov (ang. Journal Club) so se tradicionalno proučene potrebe in pričakovanja pacientov in 5. evalvacija odvijala znotraj akademskih ali zdravstvenih ustanov, danes pa učinkovitosti uporabe na dokazih podprte prakse. Poleg 5-ih se v vedno večji meri selijo na splet in družbena omrežja [16]. korakov uporabi tudi svoje strokovno znanje, da zagotovi Srečanja, na katerih se razpravlja o novejši znanstveni literaturi, optimalno zdravstveno oskrbo za pacienta [3]. imajo dva osnovna cilja: spodbujati kritično razmišljanje in širiti Uporaba e-izobraževanja na področju zdravstvene nege še nova odkritja [17] in kot taka predstavljajo osnovno z dokazi vedno predstavlja izziv zaradi vrzeli v poznavanju metodologij podprtega izobraževanja v zdravstvu [18]. in uporabe programskih rešitev. Kot navajajo Rohwer et al. [4] učenje na dokazih podprte medicine lahko uspešno nadgradimo 2.3 MOOC z vključevanjem e-učenja, pri čemer se je kot posebej učinkovito Množičnih odprti spletni tečaj (ang. Massive Open Online izkazala kombinacija klasičnega in e-učenja. Pozivajo tudi, da se Course – MOOC) je koncept izobraževanja, ki omogoča na tem področju izvede več raziskav, ki bi bolj specifično načeloma neomejen dostop in udeležbo na tečaju preko spleta. pokazale, katera komponent e-učenja je bolj učinkovita. Različne Poleg klasičnih vsebin tečajev, MOOC omogoča tudi interakcijo kombinacije klasičnega in e-učenja so se izkazale kot učinkovite udeleženca izobraževanja pri različnih aktivnostih kot so forumi, za učenje na dokazih podprte zdravstvene nege. Chu et al. [5] razprave na družbenih omrežjih, ter s tem spodbuja razpravo med opisujejo primer obrnjenega učenja (ang. flipped learning), Oh in udeleženci tečaja, pedagogi in ustvarjalci vsebin tečaja. Uporaba Yang [6] pa primer mešanega učenja (ang. blended learning). MOOC se je v zadnjem času razširila tudi na področju zdravstva V okviru projekta ProCare (Hospitals and faculties together [12]. Izkušnje izobraževalnih ustanov s področja zdravstva for prosperous and scientific based healthcare) smo za e-učenje kažejo, da MOOC predstavlja nadgradnjo in dopolnitev na dokazih podprte zdravstvene nege izbrali spletno platformo obstoječega izobraževalnega sistema [19]. Moodle [7], v kateri nastaja spletna učilnica. Za lažjo izbiro primernih oblik e-izobraževanja prikazujemo nekaj naprednih, 2,4 Interaktivne vsebine inovativnih možnosti, ki jih ponuja platforma Moodle in njeni V okviru spletnega izobraževanja, tudi v obliki MOOC se kot vtičniki. posebej pomemben element pokažejo interaktivne vsebine. Gre za način predstavitve tematike, pri katerem lahko udeleženci izobraževanja aktivno sodelujejo tako, da se pomikajo po 2 E-IZOBRAŽEVANJE predstavitvah, odpirajo dodatne informativne vsebine, izbirajo Tudi na področju zdravstvene nege so študenti psihološko pravilne rešitve s pomočjo odločitvenih dreves, sproti preverjajo pripravljeni na e-izobraževanje [8], čeprav nekateri avtorji svoje znanje s kvizi in podobno. Kot navaja [20], uporaba menijo, da je učinkovitost e-izobraževanja na področju interaktivnih elementov pri e-izobraževanju s področja zdravstva zdravstvene nege odvisna od različnih dejavnikov [9]. E- spodbuja učenje. Čeprav prve raziskave na področju izobraževanje se izkaže še posebej uporabno v kombinaciji s izobraževanja v zdravstvu zaenkrat še ne kažejo pozitivnih klasičnim načinom poučevanja [10]. Čeprav pred leti študenti izkušenj z uporabo virtualne resničnosti [21], pa je uporaba zdravstvene nege v Sloveniji niso bili naklonjeni e-izobraževanju krajših izobraževalnih videoposnetkov izkazala kot zelo [11], pa se z leti nivo informacijske pismenosti viša in tako tudi uporabno [22]. v slovenskem okolju najdemo nekaj primerov e-izobraževanja na področju zdravstvene nege. Kot del uvajalnega seminarja za zaposlene v zdravstveni ustanovi [12] predstavljajo projekt v 445 2.5 Igrifikacija nastavi uro, ko je mogoče dostopati do sistema. Dostopne pravice Igrifikacija (ang. Gamification) je uporaba elementov in imajo vsi udeleženci izobraževanja, ki se lahko prijavijo na postopkov igre v izobraževalne namene. Udeleženci platformo Moodle. Ena od možnosti za izmenjavo mnenj in izobraževanja s pomočjo elementov igre rešujejo različne izkušenj v okviru videokonferenčnega sistema so tudi skupni probleme. Igrifikacija ima velik vpliv na uspeh spletnega zapiski (ang. Shared notes). Skupne zapiske lahko uporabimo za izobraževanja posameznika [23], zato se poskusi uporabe simultano pripravo dokumenta, pri katerem sodelujejo vsi igrifikacije pojavljajo tudi na področju izobraževanja v zdravstvu udeleženci sestanka. [24]. Kot po pregledu uporabe principov igrifikacije v visokošolskem izobraževanju ugotavlja, lahko pravilna uporaba igrifikacije motivira študente k učenju [25] ter hkrati poveča študentov učni uspeh, tehnične in vedenjske veščine [26]. 3 METODOLOGIJA Pred pripravo vsebin oziroma prototipa spletne učilnice za podporo učenja na dokazih podprte zdravstvene nege, smo izbrali spletno platformo Moodle, v okviru katere bo potekalo izobraževanje [7]. Platforma Moodle že v osnovi ponuja nekaj Slika 1. Videokonferenčni sistem BigBlueButton aktivnosti, ki poleg prikaza vsebin vključujejo tudi sodelovanje udeležencev izobraževanja (forum, klepet, oddaja naloge, 4.2 Skupnost praks virtualna knjiga, kviz ipd.) in tako omogoča izvedbo nekaterih Ideja o skupnosti praks na področju zdravstvene nege ni nova, naprednejših oblik e-izobraževanja. Če želimo izgled spletne saj se že dlje časa uporablja v zdravstvenih ustanovah. Novost učilnice pripraviti na bolj atraktiven način, pa uporabljamo predstavlja skupnost praks v spletni učilnici. Kot primer različne razširitve oziroma vtičnike. skupnosti praks v spletni obliki, smo v testni učilnici pripravili Zelo dobrodošlo razširitev predstavlja videokonferenčni forum. Posebna tema »Welcome – new members« je namenjena sistem BigBlueButton [27], ki ga lahko vgradimo v spletno kratkim predstavitvam vsakega od udeležencev izobraževanja, učilnico in omogočimo virtualno druženje udeležencev kar predstavlja izhodišče za lažjo komunikacijo v spletnem izobraževanja. Vtičnik H5P [28] lahko uporabimo za pripravo okolju. Ostale teme moderator dodaja glede na predloge še bolj atraktivnih in interaktivnih aktivnosti [29]. Tako lahko v udeležencev v procesu izobraževanja. Slika 2 prikazuje vstopno spletno učilnico vključimo na primer časovni trak za zgodovinski stran v forum z najpogosteje porabljeno temo »Resources«, kjer pregled razvoja posameznega področja, odločitveno drevo, ki udeleženci objavljajo povezave do virov in raziskav s področja udeležencu pomaga pri izbiri ustrezne metode dela, stolpce s zdravstvene nege. sprotnim preverjanjem znanja, zvočne in videoposnetke, pa tudi virtualne oglede in še mnoge druge aktivnosti. 4 PRIMERI NA DOKAZIH PODPRTEGA UČENJA ZDRAVSTVENE NEGE Spletne učilnice postajajo vse pogosteje tudi del izobraževalnega procesa na področju zdravstva in zdravstvene nege. Pri razvoju Slika 2. Skupnost praks v spletni učilnici spletnih učilnic pa zaradi specifike poznavanja tehnologije pogosto poleg pedagoškega osebja sodeluje tudi tehnično osebje. 4.3 Bralni klub Pedagoško osebje prispeva vsebine, ter ideje kako predstaviti Zanimiva aktivnost za podporo obrnjenega učenja (ang. flipped posamezno temo, tehnično osebje pa pomaga pri sami learning) je bralni klub. Bralni klubi v obliki fizičnega druženja implementaciji ideje v spletni učilnici. V okviru projekta so stalna praksa pri študiju zdravstvene nege. Bralni klubi kot ProCare smo za lažje odločanje pedagogov o uporabi različnih aktivnost v spletni učilnici pa predstavljajo svojevrstno novost. aktivnosti v okviru na dokazih podprtega učenja zdravstvene V prototipu spletne učilnice so predstavljene 3 možnosti za nege, pripravili nekaj predlogov aktivnosti, ki jih lahko uporabijo izvedbo bralnega kluba, ki omogočajo različne načine interakcije za predstavitev vsebin. (slika 3): 4.1 Videokonferenčni sistem BBB • Spletni klepet v živo Razširitev platforme Moodle z vtičnikom BigBlueButton (BBB), • Razprava preko videokonferenčnega sistema ki omogoča izvedbo videokonferenčnih sestankov ali predavanj, predstavlja osnovo e-izobraževanja, saj omogoča enostavnejšo • Razprava v obliki foruma komunikacijo med udeleženci izobraževalnega procesa. Poleg predlogov za izvedbo sestanka bralnega kluba, je Videokonferenčni sistem BBB je enostaven za uporabo, saj je potrebno v spletno učilnico vključiti tudi ocenjevalni list, na podoben ostalim sistemom, ki jih je svet dodobra spoznal v času katerem udeleženci bralnega kluba kritično ocenijo prispevek, o izobraževanja in dela od doma zaradi COVID-19. Na sliki 1 je katerem teče beseda. Ena od možnosti za implementacijo zbirke predstavljeno osnovno okno videokonferenčnega sistema, ki je mnenj, ki jo lahko vidijo vsi udeleženci izobraževanja je vgrajen v spletno učilnico. Pred uporabo vodja izobraževanja aktivnost baza podatkov. V primeru, da sestanek poteka preko 446 videokonferenčnega sistema, pa udeleženci mnenja o prispevku lahko delijo tudi preko skupnih zapiskov. Slika 5. Lekcija za predstavitev raziskovalnih baz Del izobraževalne vsebine v prototipni rešitvi smo prikazali kot e-knjigo, v katero je mogoče vključiti tudi zunanjo vsebino, Slika 3. Možnosti izvedbe sestankov bralnega kluba na primer videoposnetek, kot prikazuje slika 6. 4.4 MOOC Odprti spletni tečaji so načeloma prosto dostopni in je za vstop potrebna samo registracija. Vsebine MOOC med drugim vključujejo povezave na družbena omrežja in javno dostopne vire informacij, do katerih lahko dostopajo udeleženci tečaja. Na sliki 4 je prikazan primer povezave na MOOC druge izobraževalne institucije, ki se enostavno vključi v spletno učilnico. Slika 6. E-knjiga Podobno kot v e-knjigi lahko vsebine na interaktiven način predstavimo tudi v aktivnostjo »Course presentation«, ki jo ponuja vtičnik H5P. »Course presentation« omgoča še več sodelovanja udeleženca izobraževanja, saj vsebino lahko dopolnimo tudi s sprotnim preverjanjem znanja, na primer na karticah z vprašanji in odgovori, ali s trditvami in primeri kot Slika 4. Povezava do zunanjega MOOC-a prikazujeta sliki 7 in 8. 4.5 Interaktivne vsebine Pri pripravi interaktivnih vsebin v okviru platforme Moodle lahko izbiramo med vsebinami, ki jih ponuja sama platforma, ali pa dodamo vtičnike za naprednejše aktivnosti. Lekcija omogoča, da pripravimo razvejano vsebino z različnimi dodatki in možnostjo prehajanja med posameznimi vsebinami. Ker je eno od ključnih področij za uspešno raziskovanje na področju zdravstvene nege tudi poznavanje raziskovalnih baz, smo kot lekcijo pripravili uvod ter navodila za uporabo raziskovalnih baz, kot prikazuje slika 5. Slika 7. Trditev na kartici 447 Slika 11. Odločitveno drevo za izbor statistične metode Slika 8. Primer povezan s trditvijo Zanimiv primer nadgradnje e-knjige v »Course presentation« aktivnost je tudi dodajanje preverjanja znanja znotraj multimedijske predstavitve, kot lahko vidimo pri vprašanju, ki se pojavi znotraj posnetka na sliki 9. Slika 12. Začetni ekran vodiča za izbor statistične metode Slika 9. Preverjanje znanja med predvajanjem posnetka Zgodovino razvoja posameznega področja lahko na zelo pregleden način predstavimo s časovnim trakom H5P. V časovni trak lahko vključimo povezave in fotografije (slika 10). Slika 13. Končni ekran vodiča za izbor statistične metode Eno od zanimivih možnosti v spletni učilnici predstavlja tudi slovar novih izrazov, pri čemer lahko vsebino lahko dopolnjujejo vsi udeleženci izobraževanja (slika 14). Slika 10. Časovni trak razvoja zdravstvene nege V okviru zdravstvene nege izvajamo tudi različne raziskave, pri katerih za analizo zbranih podatkov uporabljamo statistične metode. Udeležencem izobraževanja lahko pomagamo tako, s pripravo odločitvenega drevesa za izbor prave statistične metode (slika 11). Vprašanja povezana z vzorcem in njegovimi značilnostmi (slika 12) ter odgovori uporabnika pripeljejo do izbora najustreznejše statistične metode (slika 13). Slika 14. Slovar novih izrazov 448 5 ZAKLJUČEK [6] E. G. Oh and Y. L. Yang, “Evidence-based nursing V prispevku prikazujemo predlog uporabe spletne učilnice za education for undergraduate students: A preliminary učenje na dokazih podprte zdravstvene nege. Za razvoj prototipa experimental study,” Nurse Educ. Pract. , vol. 38, pp. je bila uporabljena platforma Moodle, z vtičnikoma 45–51, 2019. BigBlueButton in H5P z več aktivnostmi. Prikazani so primeri [7] A. 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M. 12th Annual University of Glasgow Learning and Medaglia, “Combining Gamification and Active Teaching Conference, 2019. 450 Inovativni pristop k širjenju znanja o standardih Innovative approach to the dissemination of knowledge about standards Alenka Baggia, Maja Bučer, Brigita Gajšek, Amanda Adrijana Mastnak, Mateja Betka Fink Butkovič, Jovana Kolidžić Podgorelec Univerza v Mariboru, Fakulteta za Univerza v Mariboru, Fakulteta za Univerza v Ljubljani, Pedagoška organizacijske vede Logistiko fakulteta Kidričeva cesta 55a Mariborska cesta 7 Kardeljeva ploščad 16 4000 Kranj, Slovenija alenka.baggia@um.si 3000 Celje, Slovenija 1000 Ljubljana, Slovenija Valentina Slodnjak Nina Fanedl Mateja Podlogar Univerza v Ljubljani, Fakulteta za Univerza v Mariboru, Pedagoška GS1 Slovenija družbene vede fakulteta Dimičeva cesta 9 Kardeljeva ploščad 5 Koroška cesta 160 1000 Ljubljana, Slovenija 1000 Ljubljana, Slovenija 2000 Maribor, Slovenija POVZETEK topic. After an analysis of the current situation, different innovative approaches to learning were examined. Experiential Inovativni pristopi v izobraževanju udeležencem izobraževanj learning was assessed as the most appropriate learning method ponujajo širok nabor možnosti, s katerimi lahko enostavneje in for the selected case. Modern technology offers many different bolj učinkovito napredujejo in osvajajo nova znanja. V prispevku ways to use ICT elements to support experiential learning. Using predstavljamo rezultate projekta Inovativni pristopi k širjenju advanced plug-ins in the online classroom, educational content znanja o standardih, sledljivosti, preskrbovalni verigi in trgovini was presented in an innovative and participant-friendly way that v visokošolsko izobraževanje, katerega cilj je bil razviti prototip encourages the participant to successfully complete the training. inovativnega izobraževanja o obravnavani tematiki. Po analizi Several effective interactive approaches to present content that obstoječega stanja smo raziskali različne inovativne pristope k can be used to learn GS1 standards are presented. učenju ter kot najprimernejšo metodo učenja za izbrani primer ocenili izkustveno učenje. Sodobna tehnologija omogoča veliko KEYWORDS različnih načinov uporabe IKT elementov za podporo izkustvenega učenja. V spletni učilnici smo s pomočjo naprednih GS1 standards, global, education, e-classroom, Moodle vtičnikov predstavili izobraževalne vsebine na inovativen in udeležencu prijazen način, ki udeleženca spodbuja k uspešnemu 1 UVOD zaključku izobraževanja. V prispevku prikazujemo nekatere učinkovite interaktivne načine predstavitve vsebin, ki jih lahko Sodobna podjetja se vedno bolj zavedajo pomena standardov, ki uporabimo za izobraževanje o globalnih standardih GS1. z enotnimi pravili omogočajo bolj zanesljivo, učinkovito in okolju prijaznejše globalno poslovanje. Standardi sledljivosti KLJUČNE BESEDE GS1 določajo minimalne podatkovne zahteve in aktivnosti, ki jih Standardi GS1, globalni, izobraževanje, spletna učilnica, Moodle je treba izvajati v organizacijah ali v skupini poslovnih partnerjev za dosego učinkovitega sistema sledljivosti [1]. Izobraževanje o ABSTRACT standardih je redko vključeno v ustrezne izobraževalne Innovative approaches in education offer participants a wide programe, zato se GS1 Slovenija kot neodvisna in nepridobitna range of opportunities to progress more easily and effectively and organizacija na področju standardov GS1 v Sloveniji sooča tudi acquire new knowledge. In this paper we present the results of s problemom širitve znanja o uporabi standardov v gospodarstvu. the project Innovative approaches to the dissemination of S ciljno usmerjenimi aktivnostmi se je tako GS1 Slovenija v knowledge about standards, traceability, supply chain and trade zadnjih letih aktivno vključil v izobraževalni proces nekaterih in higher education. The main objective of the project was to visokošolskih institucij [2]. Seznanitev s standardi GS1 v develop a prototype for innovative education on the discussed terciarnem izobraževanju poteka po vnaprej določenem sistemu, ki vključuje frontalna predavanja (v zadnjem času tudi kot spletni seminarji), študij literature ter izpit za pridobitev certifikata Certifikat stopnje 1 - Razume standarde GS1. V okviru projekta Permission to make digital or hard copies of part or all of this work for personal or Inovativni pristopi k širjenju znanja o standardih, sledljivosti, classroom use is granted without fee provided that copies are not made or distributed preskrbovalni verigi in trgovini v visokošolsko izobraževanje for profit or commercial advantage and that copies bear this notice and the full smo kot nadgradnjo obstoječemu sistemu preučili možnosti citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). uporabe kreativnih, inovativnih pristopov za širjenje znanja o Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia standardih, sledljivostiin učinkoviti preskrbovalni verigi med © 2020 Copyright held by the owner/author(s). 451 študenti. Dodatne kompetence ter poznavanje delovanja obnavljanja certifikata ter katere vsebine so bolj in katere so manj preskrbovalnih verig s podporo standardov GS1 namreč pomembne za pripravo na certificiranje kar pa je posledica študentom omogočajo konkurenčen vstop na trg dela. nekoliko skrajšanega uvodnega predavanja. Predavanje so si V prispevku je opisan trenuten postopek izobraževanja o zapomnili po energičnosti predavatelja in sproščenem ozračju. standardih GS1. Predstavljeni so nekateri inovativni pristopi k Anketiranci so izrazili tudi mnenje o različnih inovativnih izobraževanju. Prikazana je prototipna rešitev, ki je nastala na pristopih k izobraževanju, med katerimi so kot bolj zanimive osnovi analize obstoječega stanja. izbrali aplikacije za izvajanje kvizov preko mobilne naprave, prikaz v virtualni resničnosti, metode igrifikacije ter e-učilnico. 2 METODOLOGIJA 2.2 Izdelava prototipa spletne učilnice S ciljem izdelati prototip rešitve inovativnega pristopa k V okviru projekta smo se odločili za izdelavo prototipa spletne izobraževanju o standardih GS1, smo analizirali obstoječ sistem učilnice. Med različnimi sistemi za podporo spletnega učenja izobraževanja. V analizo obstoječega stanja smo vključili tudi smo izbrali okolje Moodle, ki s svojimi razširitvami ponuja zelo anketiranje študentov, ki so bili udeleženi pri izobraževanju o širok nabor možnosti inovativnega načina poučevanja. Moodle standardih GS1. S pomočjo opisne statistike smo interpretirali se že uporablja v akademskem okolju in je študentski populaciji zbrane rezultate in jih analizirali. Preučili smo literaturo s poznan. Poleg osnovnih elementov, ki jih ponuja Moodle, kot je področja inovativnih pristopov k izobraževanju, jih kratko koledar, html okno in slovar, smo uporabili dva vtičnika, ki sta predstavili ter analizirali njihove prednosti in slabosti. Na osnovi predstavljena v nadaljevanju. analiz smo za pripravo učnega okolja izbrali sistem Moodle ter s pomočjo vtičnikov izdelali prototip e-učilnice. Vtičnik H5P Vtičnik H5P [3] je brezplačen dodatek za Moodle, ki omogoča 2.1 Analiza obstoječega stanja izobraževanja o izdelavo, deljenje in ponovno uporabo različnih interaktivnih standardih GS1 HTML5 elementov. V spletno učilnico tako lahko vključimo V sklopu certificiranja izobraževanje o standardih GS1 obsega igre, multimedijo, interaktivne predstavitve, kvize, drevesa več tematik, ki jih predavatelji predstavijo s kombinacijo odločanja, časovne trakove in podobno. predavanj in praktičnih primerov. V primeru izobraževanja, ki se je izvajal v 2. semestru študijskega leta 2019/20, so bili Vtičnik LevelUp! organizacija GS1 ter standardi GS1 študentom najprej Vtičnik LevelUp! [4] pa omogoča dodajanje elementov predstavljeni na dvournem uvodnem predavanju. Pregled vsebin, igrifikacije z zbiranjem točk za opravljene aktivnosti. ki so vključene v certificiranje, je mogoč v učbeniku Upravljanje Udeleženec izobraževanja z opravljanjem posameznih nalog in globalnih preskrbovalnih verig [1]. Dodatno je študentom na aktivnosti zbira točke. Na osnovi zbranih točk se premika po voljo spletni delovni zvezek, s katerim lahko utrdijo znanje z stopnjah usposobljenosti ter na ta način dobi povratno vajami in vprašanji. Nekaj dni pred certificiranjem je potekal informacijo o svojem znanju in hkrati tudi tekmuje z ostalimi dvodnevni spletni seminar, na katerem so 3 predavatelji udeleženci izobraževanja. posamezne tematike predstavili še bolj podrobno ter jih podkrepili s konkretnimi primeri. Vsa predavanja so bila posneta in na voljo udeležencem za ponoven ogled do termina 3 INOVATIVNI PRISTOPI V certificiranja. IZOBRAŽEVANJU Uvodno predavanje so najprej analizirale študentke, ki so bile Med inovativne pristope k izobraževanju lahko štejemo različne vključene v projekt. Izpostavile so nekatere dobre značilnosti oblike poučevanja in učenja, kot so na primer obrnjeno učenje, predavanja (npr. prikaz na konkretnih primerih, sodelovanje s študije primerov, problemsko zasnovano učenje in podobno. publiko), pa tudi elemente predavanja, ki bi jih bilo mogoče Eden od inovativnih pristopov je tudi izkustveno učenje, ki se izboljšati (npr. aktivno vključevanje študentov z mobilnimi uporablja v različnih situacijah. napravami, reševanje izzivov v skupinah). Za 32 študentov, ki so V osnovnošolskem in srednješolskem izobraževanju se se udeležili uvodnega predavanja, smo pripravili anketni izkustveno učenje v večji meri nanaša na ekskurzije, projekte in vprašalnik, katerega namen je bil zbrati mnenja in povratne podobne aktivnosti, medtem ko se pri izobraževanju odraslih informacije o izvedbi predavanja. Odzvalo se je 23 študentov, ki izkustveno učenje običajno povezuje z uporabo predhodnega v večini primerov pred predavanjem niso poznali organizacije neformalnega znanja in izkušenj. Izkustveno učenje je vsako GS1 Slovenija (61 %), jih je pa večina (78 %) že slišala za učenje, pri katerem je učenec v neposrednem stiku z resničnostjo, standarde GS1. Med anketiranimi študenti se jih je 18 odločilo ki jo proučuje [5]. Kot eno od metod uspešnega učenja o za certificiranje, ker menijo da bodo s pridobljenim certifikatom preskrbovalnih verigah, izkustveno učenje predlaga tudi Weenk bolje zaposljivi, ker jim je to priporočal profesor ali jih je [6]. prepričalo uvodno predavanje. Eden od ključnih dejavnikov pri Na osnovi predhodnega študija inovativnih pristopov v njihovi odločitvi je tudi dejstvo, da je certificiranje zanje brez izobraževanju smo v okviru ankete med udeleženci uvodnega plačila. Študenti so ocenjevali tudi izvedbo uvodnega predavanja predavanja zbrali mnenje o orodjih na področju izkustvenega pri tem so kot najpomembnejše dejavnike dobrega predavanja učenja za katere študenti menijo, da so najbolj zanimivi. izpostavili jasnost razlage, praktične primere in energičnost predavatelja. Študenti so na predavanju pogrešali informacije o tem, kako lahko uporabijo certifikat, kakšen je postopek 452 3.1 Mobilne aplikacije mogoče izvesti v času projekta in je hkrati vključevala različne V spletnih trgovinah ponudnikov mobilnih aplikacij najdemo kar inovativne pristope. nekaj zanimivih možnosti, ki jih lahko v študijskem procesu uporabimo za interakcijo z udeleženci predavanj. Ne glede na to, 4.1 Nadgradnja uvodnega predavanja da uporaba aplikacij zmoti tok predavanja, pa se v večji meri Na podlagi odziva udeležencev uvodnega predavanja, smo izkaže kot zelo uporabno za pridobivanje pozornosti slušateljev pripravili posodobitev uvodnega predavanja, ki vključuje in spodbujanje medsebojne komunikacije o obravnavani tematiki nadgradnjo predstavitve, predstavitev spletne učilnice ter [7]. Med aplikacijami za takojšen odziv v pedagoškem procesu uporabo aplikacije za takojšen odziv. Izsek posodobljene se najpogosteje uporabljata aplikaciji Kahoot! [8] in Mentimeter predstavitve za uvodno predavanje je prikazan na Sliki 1. [9]. 3.2 Virtualna resničnost Tako kot na vseh področjih, se tudi na področju usposabljanja in izobraževanja virtualna resničnost vedno bolj uveljavlja ne samo kot napredno orodje za igranje iger, pač pa tudi kot učinkovit pripomoček za učenje. Z leti razvoja tehnologija postaja bolj dostopna širokemu krogu uporabnikov, s tem pa narašča tudi število primerov uporabe in raziskav učinkovitosti uporabe virtualne resničnosti v izobraževanju. Ne glede na dostopnost Slika 1. Posodobljena predstavitev na uvodnem predavanju. tehnologije, pa zahtevnost priprave izobraževalnih vsebin v Med aplikacijami za takojšen odziv, s katerimi poživimo virtualni resničnosti nemalokrat zavira priložnosti za uporabo, s diskusijo, predlagamo uporabo aplikacij Kahoot! (Slika 2) in tem pa onemogoča raziskave, ki bi analizirale njene učinke v Mentimeter (Slika 3). izobraževalnem procesu [10]. 3.3 Igrifikacija Sistem nagrajevanja oziroma učenje po principu računalniške igre, postaja v zadnjih letih zelo popularen način poučevanja digitalne generacije. Čeprav je primarni namen iger zabava, pa mnoge raziskave dokazujejo, da predstavljajo metode igrifikacije pomembno sodobno orodje, uporabno na marsikaterem področju [11]. Uporaba elementov igrifikacije pri poučevanju pripomore k učinkovitosti podajanja in utrjevanja študijske snovi [12]. Slika 2. Primer vprašanja v aplikaciji Kahoot! 3.4 E-učilnica Med vsemi izpostavljenimi inovativnimi pristopi je e-učilnica koncept, ki je v izobraževalnem okolju prisoten najdlje, zato so tudi učinki uporabe e-učilnice najbolj raziskani. Čeprav so, kot navaja [13] študenti v nekaterih primerih še vedno bolj zadovoljni s tradicionalnim načinom poučevanja, pa je učinkovitost in zadovoljstvo z e-učilnico odvisno predvsem od pripravljenosti le-te. Tako lahko z določenimi elementi inovativnih pristopov, kot sta obrnjeno ali izkustveno učenje, popestrimo okolje e-učilnice. Med primeri dobrih praks inovativnih pristopov v e-učilnici tako najdemo igrifikacijo [14] Slika 3. Primer vprašanja v aplikaciji Mentimeter ali predstavitev z interaktivnimi vsebinami [15]. 4.2 Prototip spletne učilnice Na osnovi raziskav različnih inovativnih pristopov k učenju Za pripravo prototipa spletne učilnice smo uporabili odprtokodni smo se osredotočili na izkustveno učenje, način učenja, v sistem Moodle, ki je v slovenskem izobraževalnem prostoru zelo katerega lahko vključimo različna orodja, ki omogočajo študentu razširjen. Moodle ponuja veliko raznolikih elementov in bolj pristen stik s proučevano problematiko. Na osnovi vtičnikov, ki jih lahko uporabimo za vzpostavitev izobraževanja navedenega smo izdelali prototipno rešitev. po metodologiji izkustvenega učenja. V prvi vrsti smo v spletno učilnico dodali koledar, na katerem lahko udeleženci spremljajo 4 PROTOTIPNA REŠITEV aktualne dogodke, ter povezavo na aktualne objave družbenega omrežja Twitter organizacije GS1. Prototipna rešitev predstavlja predlog prenovljenega procesa Pri izdelavi prototipa smo se osredotočili na 3. poglavje v izobraževanja o globalnih standardih GS1. Začetne ideje o učbeniku Upravljanje globalnih preskrbovalnih verig z naslovom uporabi virtualne resničnosti so se žal zaradi obsežnosti priprave Sistem standardov GS1. Uporabili smo vtičnika H5P za in situacijo zaradi izrednih razmer, izkazale za neizvedljive. interaktivno predstavitev vsebine ter LevelUp! za vzpostavitev Projektna skupina se je tako osredotočila na rešitev, ki jo je bilo 453 sistema igre v spletni učilnici. Za predstavitev zgodovine GS1 smo uporabili aktivnost časovni trak, ki je prikazan na Sliki 4. Slika 4. Časovni trak zgodovine GS1 Slika 7. Vprašanje za izbor simbologije S pomočjo aktivnosti interaktivna predstavitev smo pripravili predstavitev dela sistema GS1: Identifikacija enot (Slika 5). Slika 8. Izbrana simobologija za določen izdelek Sam postopek odločanja o izbiri simbologije je opredeljen vnaprej s pomočjo drevesa odločanja, ki je prikazano na Sliki 9. Slika 5. Interaktivna predstavitev V podpoglavje o aplikacijskih identifikatorjih GS1 smo vključili sprotno preverjanje znanja, kar nam omogoča aktivnost stolpec (ang. Column), ki je predstavljen na Sliki 6. Slika 9. Odločitveno drevo za izbor prave simbologije Slika 6. Stolpec s sprotnim preverjanjem znanja Podobno kot za podpoglavje o aplikacijskih identifikatorjih Kot način predstavitve nosilcev podatkov smo uporabili GS1, smo tudi za označevanje enot pripravili stolpec s sprotnim zvočni posnetek, ki si ga udeleženec izobraževanja lahko preverjanjem znanja. Pri tematiki nameščanja črtne kode na predvaja po potrebi. Za učenje o pravilni izbiri simbologije GS1 enoto pa smo podoben način dela prikazali na malce drugačen smo razvili drevo odločanja, ki na osnovi vprašanj (Slika 7) način in sicer kot kviz z izbirnimi vprašanji (Slika 10). udeleženca pripelje do pravilne izbire simbologije (Slika 8). 454 Slika 10. Kviz z izbirnimi vprašanji Pri podpoglavju o standardih GS1 za elektronsko poslovanje smo za prikaz različnih možnosti prikazali shemo izmenjave podatkov znotraj preskrbovalne verige (Slika 11) ter jo obogatili Slika 13. Virtualni ogled skladišča z informativnimi napisi, ki se prikažejo, ko uporabnik izbere Poleg vseh že prikazanih aktivnosti v spletni učilnici, ki so oznako za informacije na shemi (Slika 12). bile izdelane s pomočjo vtičnika H5P, smo v spletno učilnico vključili tudi slovar izrazov in kratic, ki je sicer ena od osnovnih aktivnosti v okolju Moodle. Naključen slovarski vnos se udeležencu izobraževanja prikazuje v bloku na desni strani spletne učilnice. S pomočjo vtičnika LevelUp! smo pripravili tudi lestvico dosežkov posameznika v spletni učilnici. Ob vstopu v spletno učilnico »Novinec« po pridobitvi 20 točk napreduje v »Radovedneža«, sledi »Vajenec« s 50 točkami, »Pripravnik« z 90 točkami in »Kandidat za izpit« s 140 ali več točkami. Udeleženec lahko svoj napredek spremlja preko bloka na desni strani spletne učilnice (Slika 14), če želi pa se lahko primerja tudi z ostalimi udeleženci (Slika 15). Slika 11. Shema za prikaz izmenjave podatkov Slika 12. Informativni napis na shemi S pomočjo sheme smo prikazali tudi vsebino podpoglavja o Slika 14. Pridobljena stopnja udeleženca standardih GS1 za sinhronizacijo podatkov. Zaključno tematiko o prednostih uporabe standardov GS1 smo podkrepili z video vsebino, ki je vključena v spletno učilnico. Kot zaključek izobraževanja v spletni učilnici smo za udeležence pripravili kviz z naključno izbranimi vprašanji, s čimer lahko udeleženci preverijo osvojeno znanje. V spletno Slika 15. Lestvica najboljših udeležencev učilnico smo dodali tudi element igrifikacije. Udeleženec s tem, ko si ogleduje in preskuša posamezne aktivnosti ter rešuje kvize, pridobiva točke, s katerimi napreduje po ocenjevalni lestvici. 5 ZAKLJUČEK Za prikaz dodatnih funkcionalnosti spletne učilnice Moodle V okviru projekta Inovativni pristopi k širjenju znanja o smo pripravili še virtualni ogled skladišča, ki ga prikazuje Slika standardih, sledljivosti, preskrbovalni verigi in trgovini v 13. S klikom se lahko premikamo po 360° sliki, poleg tega pa visokošolsko izobraževanje smo želeli poiskati in predlagati lahko pridobimo dodatne informacije o posameznem elementu inovativno alternativo obstoječemu sistemu izobraževanja o na sliki. standardih GS1. V prispevku smo predstavili rezultat večmesečnega dela, ki je obsegal analizo obstoječega stanja ter pripravo prototipa spletne učilnice. Organizaciji GS1 Slovenija smo predstavili predloge posodobitve uvodnega predavanja o organizaciji in sistemu certificiranja ter kot obogatitev izobraževalnih aktivnosti uporabo spletne učilnice, ki je danes vedno bolj aktualna oziroma brez nje skoraj ne gre več.Spletna učilnica razvita v okolju Moodle z uporabo vtičnikov H5P in 455 LevelUp! omogoča širok nabor možnosti, ki sledijo načelom interactions in a flipped classroom. Interact. Learn. izkustvenega učenja ter uporabljajo sodobne interaktivne Environ. 26, 1, 91–105. elemente učenja. Udeleženec izobraževanja tako na izkustven DOI=https://doi.org/10.1080/10494820.2017.1283332. način, s pomočjo različnih aktivnosti pridobiva znanje, pri tem [8] Licorish, S. A., Owen, H. E. , Daniel, B. in George, J. pa sodeluje še v navideznem tekmovanju z ostalimi udeleženci. L. 2018. Students’ perception of Kahoot!’s influence on Koncept igrifikacije se izkaže še posebej koristen tudi pri oceni teaching and learning. Res. Pract. Technol. Enhanc. lastnega znanja, saj udeležencu izobraževanja prikazuje stopnje Learn. 13, 1, 9 DOI=https://doi.org/10.1186/s41039- napredka. V svoji metaanalizi med najbolj temeljne elemente, ki 018-0078-8. so v več raziskavah izkazali največji učinek na proces učenja, [9] Mayhew, E. 2019. No Longer a Silent Partner: How uvršča ravno povratne informacije in podkrepitve [16]. Poleg Mentimeter Can Enhance Teaching and Learning prednosti, ki jih učno okolje prinaša za udeležence, Moodle Within Political Science. J. Polit. Sci. Educ. , 15, 4, 546– ponuja tudi nekaj prednosti za predavatelje, saj lahko s hitrimi 551. vpogledi v aktivnosti na spletni strani pridobijo vpogled v delo DOI=https://doi.org/10.1080/15512169.2018.1538882. udeležencev. Tako je povratna informacija v obliki spremljanja [10] Wohlgenannt, I., Grimstad, K. in Majchrzak, T. A. napredka udeleženca zagotovljena tudi predavatelju. Adamič 2019. aVirtual Reality in Higher Education: Preliminary [17] pri tem poudarja trojno funkcijo povratne informacije: Results from a Design-Science-Research Project kontrolno, motivacijsko in regulacijsko. V okviru regulacijske University of Agder. V Information Systems funkcije lahko predavatelj lažje regulira učni proces, tako da Development: Information Systems Beyond 2020 vsebine dodaja, spreminja, diferencira in individualizira glede na (ISD2019 Proceedings), C. S. A. Siarheyeva, C. Barry, viden napredek udeleženca . M. Lang, H. Linger, Ur. ISEN Yncréa Méditerranée, Toulon, France. [11] Brezavšček, A. in Minič, M. 2020. Izboljšanje ZAHVALA ozaveščenosti na področju informacijske varnosti z Projekt je bil sofinanciran iz javnega razpisa za dodelitev uporabo metod igrifikacije. Uporab. Inform. 28, 2. sredstev, ki ga delno financira Evropska unija iz Evropskega [12] Beranič, T., Rajšp, A. in Heričko, M. 2019. socialnega sklada. Javni razpis za dodelitev sredstev izbor Spoznavanje celovitih informacijskih rešitev z uporabo operacij se izvaja v okviru Operativnega programa za izvajanje igrifikacije. Uporab. Inform. 27, 1. evropske kohezijske politike v obdobju 2014–2020 kot [13] Tratnik, A., Urh, M. in Jereb, E. 2019. Student neposredna potrditev programa »Projektno delo z satisfaction with an online and a face-to-face Business negospodarskim in neprofitnim sektorjem v lokalnem in English course in a higher education context. Innov. regionalnem okolju –Študentski inovativni projekti za Educ. Teach. Int. 56, 1, 36–45. DOI= družbeno korist 2016–2020«. https:/ doi.org/10.1080/14703297.2017.1374875. [14] Sinnott, M. in Ling, A. X. 2020. A Review of the Moodle Gamification Plugin "Level Up": Using a LITERATURA Moodle Plugin to Gamify Learning of Academic [1] Martini M., Kovačič B. in Konda Z. 2014. Upravljanje Vocabulary. International J. Comput. Lang. Learn. globalnih preskrbovalnih verig. GS1, Ljubljana, Teach. 10, 3, 89-95. Slovenija. DOI=https://doi.org/10.4018/IJCALLT.2020070107. [2] GS1 Slovenija. 2020. Prenos vsebin GS1 študentom. [15] Hudson, J. Flipping Lessons with Moodle: Using the 27.8.2020 dosegljivo na naslovu: H5P Moodle Plugin to Deliver Online Sessions. 2019. https://www.gs1si.org/izobrazevanje-studentov. V 12th Annual University of Glasgow Learning and [3] Joubel. 2020. H5P. 27.8.2020 dosegljivo na naslovu: Teaching Conference (Glasgow, UK, 2-3 Apr 2019), https://h5p.org/. [16] Hattie, J. 2009. Visible learning: A synthesis of over 800 [4] Branchup. 2020. LevelUp! . 27.8.2020 dosegljivo na meta-analyses relating to achievement. Routledge, naslovu: https://levelup.plus/. London. [5] Marentič Požarnik, B., Šarić, M. in Šteh B. 2019. [17] Adamič, M. 2001. Predpostavke o didaktičnih Izkustveno učenje. Filozofska fakulteta, Ljubljana. razsežnostih zunanjega preverjanja znanja v 9. Razredu [6] Weenk, E. 2019. Mastering the Supply Chain: osnovne šole. V Zunanje preverjanje in ocenjevanje v Principles, Practice and Real-life Applications. Kogan osnovni in srednji šoli, B. Kožuh, Ur. Zveza društev Page Publishers. pedagoških delavcev Slovenije, Ljubljana. [7] Hsu, T.-C. 2018. Behavioural sequential analysis of using an instant response application to enhance peer 456 Lastna postavitev in uporaba spletne storitve za verzioniranje datotek Our own layout and use of the file versioning web service Miha Baloh Šolski center Kranj Srednja tehniška šola Kranj 4000 Kranj, Slovenija miha.baloh@sckr.si POVZETEK is very agile and has a friendly user interface. We completely avoid the web browser because we have the files physically in Na spletu obstaja množica spletnih storitev za shranjevanje the device memory. This also makes it easier to edit and modify datotek. Imenujemo jih spletni diski ali spletne datoteke ali files. The web service is an open source and centralized file datoteke v oblaku. Bistvo teh storitev je, da so datoteke ločene versioning system. od naših naprav (računalnik, telefon, itn.) in tako neodvisne od izgube naprave (okvare, zastarelosti, kraje). Njihova lastnost je KEYWORDS med drugim, da si datoteke lahko preprosto delimo med seboj. Ravno zadnje pa nujno potrebujemo pri pouku računalništva. Mi SVN, web service, file versioning, subversion pa smo vzpostaviti svojo lastno spletno storitev imenovano Subversion, ki nam omogoča učinkovito izmenjavo 1 UVOD računalniških datotek med učitelji in dijaki. Ima možnost nastavljanja pravic dostopa. Za posamezno uporabniško mapo Na spletu obstaja množica spletnih storitev za shranjevanje sistem beleži revizijsko sled in tako lahko spremljamo napredek datotek. Z nadpomenko jih imenujemo spletni diski (ang. online posameznega dijaka. Storitev je zelo agilna in ima prijazen drives), spletne datoteke (ang. online data storages) ali datoteke uporabniški vmesnik. Med drugim se popolnoma izognemo v oblaku (ang. cloud storages). V okviru teh storitev med drugim spletnemu brskalniku, ker imamo datoteke fizično na disku poznamo konkretne, kot so: Amazon Drive, Box, Citrix računalnika. Tako tudi lažje urejamo in spreminjamo datoteke. ShareFile, Hightail in MediaFire. Med najbolj množično Spletna storitev je odprtokodni in centraliziran sistem za uporabljenimi pa so: Dropbox, Google Drive, Microsoft verzioniranje datotek. OneDrive, Apple iCloud Drive in zadnje čase v porastu tudi Mega. Vse omenjene storitve smo spoznali in preizkusili. Za KLJUČNE BESEDE lastne potrebe pa izberemo samo eno izmed njih. Pametno pa je SVN, spletna storitev, verzioniranje datotek, subversion izbrati storitev, ki nam ponuja manj omejitev, to pa pomeni, čim več prostora za shranjevanje, neomejeno velikost ene datoteke in ABSTRACT neomejen čas uporabe. V večini primerov bi hitro našli primerno There are number of file storage services online. We call them ponudbo. Če se nam storitev dopade tudi v izgledu web drives or web files or cloud files. The essence of these uporabniškega vmesnika, torej prijaznosti in dostopnosti, si ni services is that the files are separate from our devices (computer, težko izbrati enega izmed naštetih. Zelo priporočljivo bi bilo phone, etc.) and independent of the loss of the device prebrati tudi pogoje uporabe. Torej, kje bodo shranjene datoteke, (malfunction, out of date, theft). Their feature is, among other v kakšne namene lahko uporabijo statistiko in analizo naše things, that the files can be easily shared with each other. Last uporabe, nam bodo glede na naše datoteke prikazovali advantage is needed in computer science lessons. We set up our prilagojene oglase, lahko naše fotografije postanejo last own online service called Subversion, which allows us to ponudnika ali pa jih celo lahko prodajo drugim osebam za efficiently share computer files between teachers and pupils. The potrebe oglasov. To so vedno zelo dolga besedila, ki ji velika service has the ability to set access rights. For an individual user večina ne bere in so preobsežna za povprečne uporabnike. Bistvo folder, the system records an audit trail and that is why the omenjenih spletnih storitev je, da imamo datoteke shranjene na progress of an individual student is easily monitored. The service varnem pred izgubo. Datoteke so ločene od naših naprav (računalnik, telefon itn.) in tako neodvisne od naprave (izgube, okvare, zastarelosti, kraje). Storitev je navidezno brezplačna, ker ne plačujemo mesečne naročnine, se nam pa prikazujejo oglasi in podobno. Individualnemu uporabniku bi opisana storitev Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed zadovoljila osnovne potrebe po shranjevanju pomembnih for profit or commercial advantage and that copies bear this notice and the full dokumentov in fotografij ter zaščito pred izgubo le-teh. citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Mi pa smo si postavili še višje cilje, kot je uporaba zgoraj Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia opisanih spletnih storitev. Želeli smo vzpostaviti storitev, ki bi © 2020 Copyright held by the owner/author(s). 457 nam omogočala kolaboracijo učiteljev in dijakov pri pouku sistem. Izbrali smo VisualSVN Server, ker je najbolj enostaven računalništva. Torej učinkovito izmenjavo računalniških datotek in prilagojen za namestitev v operacijski sistem Windows (Slika med omenjenimi udeleženci. Najbolj pogoste datoteke, ki jih 2). [2] izmenjujemo med poukom, so opisi vaj, navodila nalog, napisani programi, izvorne programske datoteke, načrti podatkovnih baz, skripte za podatkovne baze, seminarske naloge, razpredelnice, slike itn. Vsi udeleženci bi pošiljali datoteke v storitev in jih pridobivali iz nje. V njej bi uporabljali tudi pravice dostopa, torej pravice branja in pisanja za izbrane mape. Med drugim smo želeli preko omenjene spletne storitve spremljati napredek posameznega dijaka, torej število rešenih in oddanih vaj, število načrtovanih podatkovnih baz, število oddanih programskih datotek itd. Odlično bi bilo, če bi za posamezno akcijo v sistemu vedeli, kdaj se je zgodila (datum in ura). Vseh naštetih funkcionalnosti pa nam v zgornjem odstavku omenjene storitve niso omogočile oziroma so bile pri uporabi zelo omejene. Med drugim smo si želeli izogniti delu z datotekami v spletnem brskalniku, ker bi jih radi imeli fizično pri sebi na napravi, saj Slika 2: Namestitev serverja VisualSVN Server imamo le v tem načinu dela popoln nadzor nad njimi. Na tem mestu bi opozorili, da je verzija večja ali enaka 4.0 Iz izkušenj, pridobljenih v industriji računalništva, smo dobili dobila nove licenčne pogoje in postala bolj omejena in idejo, da bi si lahko pomagali s spletno storitvijo, imenovano neprimerna za uporabo velikega števila uporabnikov. V času verzioniranje datotek. Kot pravi O'Sullivan, nam ta sistem namestitve še ni obstajala, v tem času pa je že izšla. Ima omejitev omogoča zelo enostaven vmesnik za skupno rabo, napredno na 10 uporabnikov in posledično ni primerna za uporabo v šoli. dodeljevanje pravic, revizijo dogodkov, sočasno delo na istih Plačljiva verzija, ki nima omejitve števila uporabnikov, pa je zelo datotekah in še veliko več. [4] Tako smo se odločili, da bomo draga. namestili in začeli uporabljati lastni strežnik Apache Subversion, ki omogoča opisano storitev (v nadaljevanju SVN). [1] 3 KONFIGURACIJA STREŽNIKA VisualSVN Server ima zelo prijazen vmesnik za konfiguracijo 2 NAMESTITEV STREŽNIKA (Slika 3). V njem smo ustvarili nove uporabnike, uporabniška Za strežnik smo si izbrali običajni namizni računalnik s gesla, uporabniške skupine, novo odlagališče (ang. repository podpovprečno konfiguracijo: dvojedrni procesor, nekaj GB name) in osnovno strukturo map. RAM-a in običajni trdi disk. Na njega smo namestili licenčni operacijski sistem Windows 10 Education (Slika 1). Postavili in priklopili smo ga v strežniško sobo in na omrežje tako, da je dobil javni IP naslov, saj mora biti storitev dostopna od kjerkoli. V lokalni domenski strežnik (DNS) smo vpisali novo domensko ime, tako da je naša storitev postala dostopna s spletnega naslova https://svn.sckr.si/. Slika 3: Konfiguracijski vmesnik VisualSVN Server 3.1 Ustvarjanje uporabnikov in skupin Če želimo, da bodo vsi učitelji in dijaki lahko dostopali do storitve, moramo za vse ustvariti uporabniška imena in gesla. To storimo preko enostavnega vmesnika (Slika 4). Slika 1: Število dni delovanja brez prekinitve Potem pa je bilo potrebno v OS namestiti še SVN strežnik. Izvedb spletne storitve Apache Subversion je veliko. Posamezna izvedba je prilagojena za integracijo v specifični operacijski 458 Slika 4: Ustvarjanje uporabnika Za nastavljanje pravic je bilo bolj enostavno in smiselno določiti dve skupini uporabnikov: eno za vlogo učitelja in eno za Slika 6: Ustvarjanje novega odložišč dijaka. V vsako skupino smo dodali uporabnike (Slika 5). 4 DOSTOP IN UPORABA Spletna storitev deluje na konceptu odjemalec – strežnik. Strežnik je podrobno opisan v prejšnjem poglavju. Odjemalec pa je predstavljen v nadaljevanju. Imenuje se TortoiseSVN (Slika 7) in je brezplačna programska oprema. [3] Omogoča dostop in uporabo Apache Subversion storitve, ne glede na platformo strežnika. Dobimo ga na spletnem naslovu https://tortoisesvn.net/. Od tam ga prenesemo in namestimo v svojo napravo. Slika 5: Ustvarjanje uporabniških skupin 3.2 Ustvarjanje odložišča Slika 7: Odjemalec za spletno storitev SVN Po namestitvi v mapah raziskovalca, dobimo nove možnosti Preden sploh lahko začnemo uporabljati SVN datoteke, pa je na desnem kliku miške (Slika 8). potrebno ustvariti in poimenovati odložišče. Odložišče je mesto, kjer bomo hranili vse naše datoteke. Smiselno je za vsako generacijo dijakov ustvariti svoje odložišče. Ker je v tem primeru šlo za dijake »Računalniški tehnik – šolsko leto 2019/2020«, smo odložišče krajše poimenovali »RT1920«. Obstajata dve vrsti odložišč. Mi smo ustvarili običajno, ki v ozadju uporablja en strežnik. Možno je ustvariti tudi razpršeno odložišče (ang. distributed repository), ki omogoča večje število strežnikov, lociranih po vsem svetu. Prva izbira je bila tudi bolj Slika 8: Nove možnosti na desnem kliku miške enostavna (Slika 6). 4.1 Dostop do odložišča Že na začetku smo strežniku določili spletni naslov https://svn.sckr.si/. Kasneje pa smo ustvarili še ime novega odložišča »RT1920«. Tako se ti dve imeni v storitvi SVN združita in dobimo spletni URL naslov za dostop do odložišča https://svn.sckr.si/svn/RT1920. Naslov uporabimo v odjemalcu TortoiseSVN. To naredimo z ukazom »SVN Checkout. .« (Slika 9). Na disku se nam bo ustvarila nova mapa z imenom »RT1920«, ki jo kasneje lahko sinhroniziramo s SVN strežnikom. 459 Slika 12: Okno za izpis informacij "Update" Še bolj napredna funkcija pa je »Show log«, ki učitelju pokaže, katere vaje je dijak oddal, in to v časovni razpredelnici (Slika 13). Omenjena funkcija omogoča ogled zgodovine dela na Slika 9: Poveži mapo na SVN repositorij posameznih mapah (uporabniške mape) ali na posameznih 4.2 Delo v odložišču datotekah. V odložišču, ki se je naložil na naš računalnik, lahko urejamo datoteke kot običajno na disku računalnika. Ko delo zaključimo, spremembe pošljemo v strežnik (funkcija »commit«). Med delom lahko tudi prejemamo nove datoteke in spremembe obstoječih datotek, ki so jih v tem času ustvarili drugi uporabniki (funkcija »update«). Dve osnovni funkciji za delo z odložiščem se imenujeta »Commit« (pošlji spremembe v strežnik) in »Update« (prejmi novosti iz strežnika). Obe funkciji sta na izbiro z desnim klikom na katero koli SVN datoteko ali mapo (Slika 10). Slika 13: Ogled preteklega dela v uporabniški mapi Slika 10: Funkciji »Commit« in »Update« Obstaja pa še mnogo funkcij, ki jih je možno izvajati na Funkcija »Commit« odpre pogovorno okno, v katerem mapah (povrni na revizijsko številko, povrni vse spremembe na pregledamo spremembe, ki jih želimo poslati v strežnik (spodnja revezijo strežnika, počisti lokalne spremembe itn). Obstajajo pa polovica okna) in sporočilo, ki bi ga radi zapisali k tem še napredne funkcije (Slika 14), ki jih je možno izvesti samo na spremembam (zgornja polovica okna) (Slika 11). posamezni datoteki (izbriši, preimenuj, zakleni). Za učitelja se je za zelo uporabno izkazala funkcija pregled sprememb datoteke (ang. Diff with privios version). Omogoča, da na posameznem dokumentu pogledamo zadnje opravljene spremembe. Tako lahko lažje ocenimo oddano nalogo in preverimo dijakov napredek. Slika 11: Pogovorno okno za izvedbo funkcije "Commit" Slika 14: SVN funkcije na posamezni datoteki Funkcija »Update« odpre okno, v katerem vidimo vse novosti, ki smo jih prejeli iz strežnika (Slika 12). 5 ZAKLJUČEK Delo učitelja in dijaka je z uporabo tehnologije Subversion bolj učinkovito, pregledno in ažurno. Za učitelja to pomeni večjo kontrolo pri izvajanju praktičnega pouka pri modulih računalništva. Pregledovanje oddanih datotek v uporabniških 460 mapah je zelo olajšano zaradi enostavnega prenosa datotek od VIRI dijaka do učitelja. Tako učitelj utemeljeno zahteva sprotno delo [1] Apache Software Funcation, Apache Subversion. in pri pouku prakse je opazen bistveni napredek. Za dijaka je prva prednost dostopnost do skupnih in lastnih Pridobljeno (13. 8. 2020) s datotek na enem mestu, torej so dostopne povsod, kjer obstaja https:/ subversion.apache.org/. internetna povezava. Če pa je predhodno odložišče že preneseno [2] VisualSVN Software Ltd., Subversion Server for na lastno napravo, internetna povezava ni potrebna. Windows. Pridobljeno (13. 8. 2020) s Druga prednost je, da ima dijak datoteke shranjene varno in https://www.visualsvn.com/server/. enostavno. Žal dijaki dostikrat v časovni stiski uporabljajo neprimerne medije (USB ključ, neorganizirani spletni oblaki in [3] TortoiseSVN: the coolest interface to (Sub)version control. e-pošta) in posledično izgubijo ali ne najdejo svojega dela. V Pridobljeno (13. 8. 2020) s https://tortoisesvn.net/. našem primeru ni bilo zaznati teh težav. Ena izmed pomembnih prednosti, ki se je izkazala v zadnjem [4] B. O'Sullivan. Mercurial: the Definitive Guide. Sebastopol: času, je, da učitelji dijaku lahko pomagajo tudi na daljavo. V času O'Reilly Media, Inc., 2009. Pridobljeno (25. 8. 2019) s korona virusa in dela od doma je bilo orodje nepogrešljivo. http://hgbook.red-bean.com/read/. 461 Pregled in primerjava spletnih storitev za shranjevanje datotek Assessment and comparison of online file storage services Miha Baloh Šolski center Kranj Srednja tehniška šola Kranj 4000 Kranj, Slovenija miha.baloh@sckr.si POVZETEK V prispevku so predstavljeni glavni ponudniki shranjevanja 1 UVOD datotek na spletu. Z namenom izbire najboljših in V prispevku so predstavljeni glavni ponudniki shranjevanja najprimernejših med njimi, smo opravili primerjavo, pregled in datotek na spletu. Med njimi smo opravili primerjavo, pregled in oceno. Kriterij ocenjevanja temelji na podatkih, kot so: velikost oceno. Izbrani kriteriji ocenjevanja so: velikost prostora, prostora, omejitev velikosti ene datoteke in časovna omejitev omejitev velikosti ene datoteke in časovna omejitev uporabe. uporabe. Ocena je bila izračunana po modelu največ prostora in Ocena je izračunana po modelu največ prostora in čim manj čim manj omejitev oziroma čim več ugodnosti za čim manj omejitev oziroma čim več ugodnosti za čim manj denarja. denarja. Po tem kriteriju so se izkazali iCloud Drive, Google Drive, Microsoft OneDrive, Citrix ShareFile, MediaFire in Mega. Poleg glavnih tekmecev je v oceni tudi nekaj alternativnih 2 PROBLEMSKO STANJE ponudnikov. Nekatere storitve so se izkazale za zelo Najprej smo raziskali problemsko stanje na področju enakovredne, zato je končna odločitev uporabe vedno po izbiri shranjevanja datotek. Rezultat vprašalnika o shranjevanju uporabnika. datotek je pokazal, da se velika večina datotek, ustvarjenih na KLJUČNE BESEDE tujih napravah (v službi, šoli, knjižnici), shrani kot priponko v e- pošto (76 %), zunanjo napravo (15 %) in v namensko storitev (9 Shranjevanje datotek, spletne storitve, oblačne storitve, pregled %). Med drugim je bilo ugotovljeno, da dijaki na tujih napravah in primerjava za shranjevanje datotek zelo veliko uporabljajo e-pošto, čeprav ABSTRACT ni namenjena temu. Doma pa datoteke (fotografije, pomembni dokumenti itd.), ki The article presents the main providers of online file storage. In jih želijo imeti trajno shranjene, shranjujejo preveč razpršeno, in order to select the best and most suitable among them, a sicer v: osebni računalnik (77 %), namenske storitve (77 %), comparison, review and evaluation were carried out. Evaluation zunanje naprave (87 %) in druge medije (1 %). Torej, criteria is based on data such as: maximum space, size limit of zaskrbljujoče je, da imajo pomembne datoteke shranjene v one file and time limit of use. The estimate was calculated različnih medijih. Iz izkušenj vemo, da slabo organiziran sistem according to the following model - largest space, least capacity ne omogoča iskanja in posledično lahko prihaja do izgube limit and more benefits for less money. According to this datotek. Težje je tudi vzdrževati več sistemov, kot samo enega. criterion iCloud Drive, Google Drive, Microsoft OneDrive, Zgodi se, da nam en medij odpove in lahko izgubimo del Citrix ShareFile, MediaFire and Mega have proved to be the best. dragocenega arhiva. In addition to the main competitors, there are also some Drugi del vprašalnika je pokazal, da dijaki večinoma poznajo alternative providers presented. Some services have proved to be samo glavne ponudnike spletnih storitev shranjevanja: Google very equivalent, so the final decision is always the user's choice. OneDrive (38 %), Dropbox (89 %) in Microsoft OneDrive (72 %). Med manj poznanimi so Apple iCloud (13 %), Box KEYWORDS (2,5 %) in Mega (2,5 %). Ostalih spletnih ponudnikov, ki jih File storage, web services, cloud services, assessment and obravnavamo v tem prispevku, pa ne poznajo. comparison Tako smo naredili oceno in pregled spletnih storitev za shranjevanje datotek, da bi se dijaki v prihodnosti lažje odločali in izbirali ponudnike spletnih storitev, s katerim bi bili zadovoljni. Ključnega pomena je, da bi vse pomembne dokumente shranili Permission to make digital or hard copies of part or all of this work for personal or na varen in organiziran način. classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 462 3 PREDSTAVITEV GLAVNIH PONUDNIKOV MediFire [3] V Tabeli 1 so objektivno predstavljeni glavni ponudniki spletnih storitev shranjevanja datotek. Vsaka storitev je predstavljena z Osnovni podatki imenom lastnika oz. razvijalca, s katerimi programskimi jeziki je Razvijalec MediaFire ustvarjena, kdaj se je prvič pojavila na spletu in trenutnim Programski jeziki Java, JavaScript, Objective-C, številom uporabnikov na spletnem in mobilnem trgu. Poleg C++ osnovnih podatkov pa so navedene še podprte platforme. Resni Datum prve izdaje september 2013 ponudniki podpirajo vse glavne platforme, kot so namizni Št. uporabnikov > 10 milijonov računalniki Mac in Windows, mobilne naprave Android in iOS Podprti sistemi ter obvezno tudi dostop preko spletnega brskalnika (neodvisen Spletni dostop da od OS). Odstopanja so zelo majhna in so razvidna iz tabele. Če Android da bi primerjali storitve po številu uporabnikov na spletnem in iOS da mobilnem trgu, bi se skupno na prvo mesto uvrstili Google MacOS ne Drive, Microsoft OneDrive in Apple iCloud (vsak po več kot 1 Windows ne milijardo uporabnikov), na drugo mesto Dropbox (več kot 500 milijonov uporabnikov) in na tretje mesto Mega (več kot 50 Microsoft OneDrive [4] milijonov uporabnikov). Osnovni podatki Tabela 2: Predstavitev ponudnikov Razvijalec Microsoft Programski jeziki C#, Visual Basic Google Drive [1] Datum prve izdaje 1. avgust 2007 Št. uporabnikov > 1 milijarda Osnovni podatki Podprti sistemi Razvijalec Google Spletni dostop da Android da Programski jeziki Python, Objective-C iOS da Datum prve izdaje 24. april 2012 MacOS ne Št. uporabnikov > 1 milijarda Windows da Podprti sistemi Spletni dostop da Mega [5] Android da iOS da Osnovni podatki MacOS da Razvijalec Mega Ltd. Windows da Programski jeziki C++, JavaScript, Java, Objective-C Apple iCloud [2] Datum prve izdaje 19. januar 2013 Št. uporabnikov > 50 milijonov Osnovni podatki Podprti sistemi Razvijalec Apple Inc. Spletni dostop da Programski jeziki C, Objective-C Android da Datum prve izdaje 12. oktober 2011 iOS da Št. uporabnikov > 1 milijarda MacOS da Podprti sistemi Windows da Spletni dostop da Android ne iOS da MacOS da Windows da 463 Dropbox [6] Hightail [10] Osnovni podatki Osnovni podatki Razvijalci Dropbox Razvijalci Hightail (YouSendit Inc.) Programski jeziki Python, Go, TypeScript, Rust Programski jeziki ni podatka Datum prve izdaje september 2008 Št. uporabnikov > 50 tisoč Št. uporabnikov > 500 milijonov Datum prve izdaje 2004 Podprti sistemi Podprti sistemi Spletni dostop da Spletni dostop da Android da Android da iOS da iOS da MacOS da MacOS da Windows da Windows da Amazon Drive [7] 4 PREGLED IN OCENA BREZPLAČNE Osnovni podatki PONUDBE SPLETNIH STORITEV Razvijalci Amazon Mobile LLC V Tabeli 2 je primerjava in ocena brezplačnih spletnih storitev. Programski jeziki HTML, CSS, JavaSript, PHP, Pri primerjavi so bili vključeni naslednji kriteriji: velikost Java, C# prostora, največja velikost ene datoteke in časovna omejitev Datum prve izdaje 29. marec 2011 brezplačne uporabe. V zadnjem stolpcu je dodeljena ocena, ki je Št. uporabnikov > 1 milijon višja, če ima storitev več prostora in manj omejitev. Brezplačne Podprti sistemi storitve, označene z modro bravo, so se izkazale za najboljše. Spletni dostop da Med njimi pa je daleč v ospredju spletna storitev Mega. Android da iOS da Tabela 3: Lestvica ocenjenih brezplačnih storitev MacOS da Ime Velikost Velikost ene Časovna Ocena prostora datoteke omejitev Windows da Mega 50 GB neomejeno neomejeno 10 Google Drive 15 GB neomejeno neomejeno 9 Box [8] MediaFire 10 GB 4 GB neomejeno 8 Box 10 GB 250 MB neomejeno 7 iCloud Drive 5 GB ni podatka neomejeno 6 Osnovni podatki Microsoft OneDrive 5 GB neomejeno neomejeno 5 Razvijalci Box, Inc. Dropbox 2 GB neomejeno neomejeno 4 Programski jeziki Java, XML, drugo Hightail 2 GB 100 MB 7 dni 3 Datum prve izdaje 2005 Citrix ShareFile neomejeno 100 GB 30 dni 2 Amazon Drive slike + 5 ni podatka 30 dni 1 Št. uporabnikov > 10 milijonov GB video Podprti sistemi Spletni dostop da Android da 5 PREGLED IN OCENA PLAČLJIVE iOS da PONUDBE SPLETNIH STORITEV MacOS da V Tabeli 3 je primerjava in ocena plačljivih spletnih storitev. Windows da Izbrani so bili naslednji kriteriji: velikost prostora, cena naročnine in število let obstoja podjetja. Slednje je pomembno, Citrix ShareFile [9] saj število let kaže na uspešnost in stabilnost podjetja, kar predstavlja večjo verjetnost, da bo podjetje delovalo še naprej. Osnovni podatki Naši podatki pa bodo v tem primeru ostali shranjeni na varnem. Razvijalci Citrix Systems, Inc. Pri izračunu ocene smo najprej upoštevali velikost prostora in Programski jeziki ni podatka letno naročnino. Iz omenjenih podatkov smo izračunali ceno Datum prve izdaje november 2005 storitve na 1TB prostora. Tako smo ponudbe lažje primerjali. Ker Št. uporabnikov > 100 tisoč pa cena in velikost še ne povesta vsega o kvaliteti, smo dodali še Podprti sistemi datum ustanovitve podjetja in iz njega izračunali število let Spletni dostop da obstoja. Android da Končna ocena je seštevek cene na 1TB prostora in število let iOS da uspešnega delovanja. V končni oceni smo želeli upoštevati tudi MacOS da število zadovoljnih uporabnikov. Resničnost zadnjega podatek je Windows da zelo težko preveriti, tako da smo ga iz končne ocene in pregleda izključili. 464 Tabela 4: Lestvica ocenjenih plačljivih storitev Tabela 5: Lestvica združenih ocen brezplačne in plačljive Ime Velikost Letna Ustanovitev Let Ocena spletne storitve prostora naročni podjetja obstoja Ime Ocena Ocena Pri prehodu Končna -na podjetja Citrix ShareFile neomejeno 600 $ 1. 1. 1989 31 10 brezplačne s. plačljive s. ocena iCloud Drive 2 TB 120 $ 1. 4. 1976 44 9 iCloud Drive 6 9 + 16 MS OneDrive 1 TB 69,99 $ 4. 4. 1975 45 8 Google Drive 9 6 - 14 Amazon Drive 1 TB 59,99 $ 5. 7. 1994 25 7 MS OneDrive 5 8 + 14 Google Drive 2 TB 110 $ 4. 9. 1998 21 6 Citrix ShareFile 2 10 + 13 MediaFire 1 TB 45 $ 20.10. 2006 13 5 MediaFire 8 5 - 12 Dropbox 2 TB 120 $ 1. 6. 2007 13 4 Mega 4 TB 266 $ 19. 1. 2013 7 3 Mega 10 3 - 12 Hightail 25 GB 180 $ 1. 1. 2004 16 2 Amazon Drive 1 7 + 9 Box 100 GB 108 $ 1. 6. 2005 15 1 Dropbox 4 4 0 8 Box 7 1 - 7 Na prvo mesto se je uvrstil Citrix ShareFile, saj ima edini Hightail 3 2 - 4 neomejeno velikost prostora in dolgo zgodovino izkušenj. Sicer pa so vsi ponudniki v zgornji polovici tabele vredni preizkušnje. 7 ZAKLJUČEK Če pozabimo na Cistrix ShareFile in naredimo primerjavo samo po kriteriju cena na 1TB prostora, je na prvem mestu MediaFire Kratko raziskavo pregleda in ocene spletnih storitev za (45 $), na drugem mestu Google Drive (55 $) in na tretjem mestu shranjevanje datotek je smiselno predstaviti dijakom 1. letnikov iCloud Drive skupaj z Amazon Drive (60 $). srednješolskega izobraževanje pri predmetu informatike, saj je to pravi čas, da se odločijo, kje bi imeli dolgoročno shranjene pomembne datoteke. Sprva bi jih bilo smiselno ozavestiti, da so 6 KONČNA OCENA IN PREGLED mediji, kot so USB ključki, SSD diski, telefoni in druge naprave, BREZPLAČNIH IN PLAČLJIVIH neprimerne za dolgoročno ali trajno shranjevanje datotek in da SPLETNIH STORITEV so ob izgubi naprave najbolj dragocene ravno datoteke, ki jih pa brez uporabe spletnih storitev ne moremo povrniti. Raziskava bo V končni lestvici smo združil pregled in oceno brezplačnih in dijakom dala vpogled v osnovne podatke in vzbudila zanimanje plačljivih storitev. Večinoma uporabniki najprej izberejo za uporabo le-teh. Tako imajo na enem mestu pregledno brezplačne storitve. Kasneje, ko ugotovijo, da je storitev zelo predstavljene možnosti spletnih storitev. uporabna in začne primanjkovati prostora, pa se odločijo za plačljivo storitev. Torej, če razmišljamo za prihodnost, bomo verjetno vse VIRI pomembne datoteke (dokumente, slike, projekte ipd.) imeli shranjene v spletni storitvi. Mape in datoteke, shranjene pri [1] Google Drive. Pridobljeno (13. 8. 2020) s prvem ponudniku, pa bomo redko selili k drugem, ker to od nas https://www.google.com/drive/. zahteva dodatne veščine, delo in čas. Iz naštetih razlogov smo [2] Apple iCloud. Pridobljeno (13. 8. 2020) s naredili končno lestvico (Tabela 4) najboljših spletnih storitev https://support.apple.com/en- kot združitev ocene iz Tabele 2 in Tabele 3. gb/guide/icloud/welcome/icloud. Ocene Tabele 2 in Tabele 3 smo morali postaviti na skupni imenovalec, da se lahko oceni pravilno seštejeta. Tako smo [3] MediaFire. Pridobljeno (13. 8. 2020) s najbolje ocenjeni storitvi dodelil 10 točk, najslabše ocenjeni pa 1 https://www.mediafire.com/. točko. Opaziti je, da se v 90 % ocenjenih storitev spremenila [4] Microsoft OneDrive. Pridobljeno (13. 8. 2020) s ponudba iz prehoda brezplačne na plačljivo storitev. Zato smo https://www.microsoft.com/sl-si/microsoft- pri končni oceni upoštevali tudi ta argument. Če se je pri prehodu ponudba izboljšala, smo prišteli +1 točko, če se je poslabšala, 365/onedrive/online-cloud-storage. smo odšteli -1, če pa se kvaliteta ponudbe ni spremenila, smo [5] Mega. Pridobljeno (13. 8. 2020) s prišteli 0 (samo Dropbox). https://help.mega.nz/. Končna ocena je pokazala najbolj priporočljive ponudbe spletnih storitev v celoti. Kot vidimo, so si nekateri ponudniki [6] Dropbox. Pridobljeno (13. 8. 2020) s tudi enakovredni in je izbira med njimi odločitev končnega https:/ www.dropbox.com/basic/. uporabnika. [7] Amazon Drive. Pridobljeno (13. 8. 2020) s https://en.wikipedia.org/wiki/Amazon_Drive/. [8] Box. Pridobljeno (13. 8. 2020) s https:/ www.box.com/pricing/individual. [9] Citrix ShareFile. Pridobljeno (13. 8. 2020) s https://www.sharefile.com/features. [10] Hightail. Pridobljeno (13. 8. 2020) s https://www.hightail.com/file-sharing/. 465 Usvajanje digitalnih kompetenc in dodatna pomoč učencu s posebnimi potrebami pri izobraževanju na daljavo Acquisition of digital competencies and additional assistance to student with special needs in distance learning Aleksandra Borovnik Osnovna šola Draga Kobala Maribor Tolstojeva ulica 3 2000 Maribor, Slovenija aleksandra.borovnik@osdk.si POVZETEK encouragement, while at the same time guiding him and his parents so that he was able to successfully complete his school V prispevku je predstavljena dodatna strokovna pomoč učencu assignments and integrate in distance learning programme v osnovni šoli v času izobraževanja na daljavo. Učenec je že v without any major issues. as a consequence of this additional času izobraževanja v živo na šoli imel veliko pomanjkanje support he and his family have received, the student now has motivacije za šolsko delo, poleg tega pa ima zdravstvene težave, required learning skills and is well prepared for any re-education ki so zelo vplivale na njegovo uspešnost v šoli in življenju doma. online. Šolanje na daljavo je zanj predstavljalo velik izziv, saj se je moral digitalno opismeniti oziroma pridobiti nova znanja in digitalne KEYWORDS kompetence za normalno spremljanje pouka. Kot izvajalka dodatne strokovne pomoči sem učencu pomagala, da je skozi Acquisition of digital competencies, children with special needs, pogovor, razlago in s spodbujanjem pridobil te veščine. Hkrati distance learning pa sem usmerjala njega in svetovala njegovim staršem, da je uspešno opravil šolske naloge in se dobro, brez večjih težav, 1 UVOD vključil v šolanje na daljavo. Dodatno pomoč so učenec in starši sprejeli ter sodelovali. Učenec je tako pridobil zahtevane učne Sredi marca 2020 se je Slovenija zaradi razglašene epidemije čez spretnosti in je dobro pripravljen na morebitno ponovno noč odločila prekiniti redni pouk v šolah in prešla na šolanje na izobraževanje preko spleta. daljavo. Na to nihče ni bil pripravljen. Bile so narejene sicer nekatere grobe študije, kako naj bi potekal tak pouk, v eni od KLJUČNE BESEDE njih je avtor zapisal: » Tako bo potrebno še podrobneje Usvajanje digitalnih kompetenc, otroci s posebnimi potrebami, analizirati učenje na daljavo kot učni proces (npr. izvore učenja, šolanje na daljavo osnove pospešenega učenja, pogoje uspešnega učenja, etape v procesu učenja na daljavo), še podrobneje razdelati in definirati ABSTRACT učna načela učenja na daljavo, metode in oblike učenja na This paper explores the case of supplementary professional daljavo, postopke izbire in razvrstitve učiva, notranjo in zunanjo support for a primary school student during distance learning. organizacijo, preverjanje učnih uspehov in preprečevanje učnih the student in question has already had a lack of motivation for neuspehov, ocenjevanje v procesu učenja na daljavo itd.« [1] schoolwork during his face to face learning, and has also faced Skratka, stvari niso bile dorečene in to je bil velik zalogaj tako za health issues that were significantly affecting his performance at učitelje, kaj šele za učence, še posebej za učence s posebnimi school and his home life . distance learning was a great challenge potrebami, ki so zelo ranljive skupine in jim veliko pomeni for him, as he had to become digitally literate and acquire new osebni stik in osebna pomoč. skills and competencies in order to follow the lessons. as a provider of additional professional support, i helped the student 2 ZNAČILNOSTI UČENCA to gain those skills through conversation, explanation and Učenec je prišel na našo šolo ob koncu prvega vzgojno- izobraževalnega obdobja. Takrat ni kazal posebnosti, so se pa začele pojavljati v naslednjem razredu, ko je zaostajal z delom Permission to make digital or hard copies of part or all of this work for personal or zlasti pri nalogah, kjer je bilo potrebno nekaj natančno narisati. classroom use is granted without fee provided that copies are not made or distributed Takrat je narisano nenehno radiral in nikoli ni bil zadovoljen z for profit or commercial advantage and that copies bear this notice and the full nastalim izdelkom. Kasneje se je njegovo vedenje stopnjevalo z citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). umivanjem rok, ki je časovno zelo presegalo okvirje normalnega Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia umivanja. © 2020 Copyright held by the owner/author(s). 466 Težave so postale tako hude, da so zapolnile učenčev vsakdan. 3.1 Usvajanje in uporaba spletnih orodij Svoj prosti čas je preživljal v samoti, kjer je lahko nemoteno opravljal svoja dejanja (si več ur umival roke)… Začel je veliko 3.1.1 Google Meet izostajati od pouka. Ko je bil v šoli, je njegovo vedenje začelo Ker pogovori preko maila niso bili učinkoviti, sva se dogovorila, postajati moteče za delovanje razreda. Težko je shajal v da se slišiva preko Google Meet-a. Tu sem za pomoč prosila komunikaciji z drugimi, zato so se začeli pojavljati konflikti med dečkovega očeta, ki je učenca spomnil, da se ob pravem času njim in sošolci. Tako so se poslabšali odnosi med vrstniki, kar je priključi na povezavo oziroma priključi srečanju. Končno nama imelo za posledico slabše delovanje v šoli. Tudi doma so se je uspelo, da sva vzpostavila stik preko računalnika in tako pojavljale velike težave zlasti zaradi njegovih ritualov, pa tudi v izkoristila možnost video srečanja (slika 1). Na najinih urah v komunikaciji in v odnosih z družinskimi člani. Starši so mu živo sva se veliko pogovarjala. V začetku sva pregledala, preko poiskali pomoč in ugotovili so mu obsesivno kompulzivno katerih komunikacijskih kanalov bo v stiku z učitelji in učenci. motnjo. Ugotovila sem, da mu delo in povezovanje preko računalnika, Pri obsesivno kompulzivni motnji (OKM) so prisotne misli razen računalniških iger ne odgovarja. Na tem področju je bil vsiljivke (obsesije) in/ali prisilna dejanja (kompulzije). Obsesije praktično nepismen. Naredila sva načrt povezovanja s šolo. so vsiljive, ponavljajoče misli, ki jih posameznik doživlja kot mučne (na primer obsesija pred okužbami). Kompulzija je neobvladljiva potreba po opravljanju neke dejavnosti ali giba. Kompulzivna dejanja ali rituali, ki se osebi vsiljujejo, so ponavljajoča in neprijetna. [2] Učenec je dobil odločbo za otroke s posebnimi potrebami. V šoli sem mu pomagala kot izvajalka dodatne pomoči. Cilji so bili usmerjeni predvsem v socialne, komunikacijske in organizacijske veščine, saj je imel učenec na tem področju tudi največ težav. Kljub temu da je učenec veliko izostajal od pouka, je učno snov dokaj uspešno nadoknadil, saj učnih težav ni imel, snov in razlago pa si je zapomnil, če je le bil prisoten v šoli. Ostalo delo smo usmerjali in skušali realizirati znotraj ur dodatne strokovne pomoči. Učenec je bil računalniško opismenjen na določenih Slika 15. Pogovor z učencem področjih. Najbolj je obvladal igranje računalniških iger, saj je s tem doma preživel (pre)velik del prostega časa. Znal je napisati 3.1.2 Spletna učilnica tudi kak wordov dokument, pri ostalih stvareh pa so mu pomagali Ko je učenec nekako usvojil komunikacijo in delovanje Google družinski člani. Zato smo kot cilj v šoli dodali tudi digitalne Meet-a, sem ga usmerila v spletne učilnice, v katerih je potekal kompetence, kjer smo poleg brskanja na spletu in iskanja pouk na naši šoli. informacij, veliko pozornost namenili tudi komuniciranju in Njihov glavni namen je integracija tehnologij v skupek orodij, sodelovanju preko računalnika - torej sporazumevanju z uporabo ki so razumljiva tako učencem kot učiteljem in jim tako olajšajo digitalnih tehnologij. Vendar, kot smo kasneje ugotovili, še prenos znanja. [3] veliko premalo. Seznanil se je z delovanjem in uporabo le-teh in tako lahko sledil po posameznih predmetih navodilom in nalogam, ki so jih pripravljali učitelji. 3 IZOBRAŽEVANJE NA DALJAVO 3.1.3 Skype Marca 2020 je v Sloveniji izbruhnil korona virus. Čez noč je bilo Ker so imeli tedensko s sošolci razredne ure preko Skype-a, sem potrebno vzpostaviti stik na daljavo. Učenec je bil zelo vesel, ker učenca seznanila z možnostjo namestitve programa na je lahko ostal doma, socialna izolacija mu je v začetku zelo računalnik. Učenec je izkazoval velik odpor, ko bi moral v prijala. kakšno stvar vložiti trud in razmišljati, kako kaj deluje. Ta Ker od učenca kljub veliki vztrajnosti ni bilo nobene povratne »borba« je trajala štiri tedne, ko se je končno sprijaznil, da se bo informacije, sem kontaktirala preko telefona njegovega očeta. enkrat moral soočiti tudi s tem in uspelo mu je, da se je v petem Dogovorila sva se, da bom učencu pošiljala sporočila na tednu preko Skype-a povezal z razredničarko in sošolci na elektronski naslov, prav tako pa njegovim staršem, da bodo razredni uri. Seveda so bile tukaj del odpora tudi njegove težave seznanjeni s tem, kaj in kako poteka najino delo. Hkrati pa sem z OKM, saj je na kameri želel izgledati brezhibno, zato se je bila v navezi z učitelji, ki so mi posredovali povratne informacije včasih odločil, da kamere sploh ne bo uporabljal. tudi z njihove strani, kako se učenec odziva na njihove naloge. Težave so se pojavile že takoj. Najprej pri osnovni uporabi 3.2 Ure dodatne strokovne pomoči preko spleta elektronske pošte, nato pa pri uporabi spletnih aplikacij. Učenec Ko je učenec usvojil osnovna orodja, s katerimi se je lahko je potreboval veliko pomoči in vodenja, da se je znašel med vključeval v učni proces na daljavo, sem lahko del ur izkoristila poplavo podatkov in poiskal povezave, ki so se dotikale tudi za usvajanje ciljev, ki jih usvajava tudi v šoli, le da tokrat njegovega šolskega dela. na daljavo, a vseeno »v ŽIVO«. Z učencem sva se pogovorila o virusu, o strahu in tesnobi, ki ga doživlja ob tem še posebej on, ki ima še dodatne težave v zvezi z OKM. Govorila sva o empatiji, 467 usmerila sem ga v to, da sva se pogovarjala o tem, kaj se dejansko Starši so se veliko obračali po pomoč in nasvet v šolo, saj so dogaja. sedaj s težavami ostali sami med štirimi stenami, dnevi pa so bili Strukturiranje dneva: predlogi, časa preveč. Nenehno so bili skupaj, zato je med njimi Pomembno je bilo, da sva strukturirala dan. V času rednega prihajalo tudi do nerazumevanja, do konfliktnih situacij in starši izobraževanja v šoli je imel učence s časom že tako velike težave. so prosili za nasvete. Tako sem na nek način izvaja dodatno Zdaj pa je bilo potrebno natančno določiti potek dneva: čas za strokovno pomoč na daljavo tudi staršem. obroke, higieno in počitek, delo za šolo, domača opravila ter Glavno navodilo staršem preko elektronske pošte, pa tudi prosti čas. Pomembno je bilo tudi vključiti telesno aktivnost. preko telefona je bilo, da so v zvezi s situacijo glede korona Z učencem sva skupaj sestavila in napisala urnik. Tukaj sem virusa umirjeni v vseh pogledih, da bo otroku lažje. predvsem želela pomagati staršem, saj kot je navedeno pri Svetovala sem jim za različna področja učenčevega Svetovalnem centru za otroke, mladostnike in starše »Otrokom z funkcioniranja doma: dobrimi delovnimi in učnimi navadami to ne bo nič novega, če Druženje s prijatelji preko spleta: pa je otrok bil do sedaj premalo organiziran in samostojen ter Staršem sem svetovala, da je potrebno prosti čas na navajen, da ga motivirajo drugi, pa bo v strukturo dneva potrebno računalniku smiselno omejiti na določen čas, saj so imeli že v vnesti več napora. [4] preteklosti velike probleme z vzpostavljanjem nadzora nad Načrtovanje učenja: zaslonsko tehnologijo. V začetku so imeli s tem velike težave. Učenec je imel že prej zelo slabe delovne navade. Učil se je Kasneje je učenec del časa pred računalnikom namenil tudi le pred testi, a še to občasno. Prednost je bila ta, da če je le bil v šolskemu delu. Moj nasvet staršem je bil, naj spodbujajo otroka, šoli, si je zapomnil veliko stvari, zdaj pa je bila situacija zelo da če kaj ne ve za šolo, naj najprej vpraša svojega sošolca za drugačna. Pretirano rad je igral igrice in na tem področju je bil pomoč in tako se bodo bolj povezali. odličen. Ostale IKT veščine pa mu niso bile tako blizu, zato je Otrokov prosti čas: čutil do tega še posebej velik odpor. Dogovorila sva se, katere Največ sem usmerjala starše, kako naj vodijo otroka, da bo predmete bo v spletnih učilnicah najprej opravil in katere si lahko koristno preživel prosti čas in da ne bo hotel samo igrati igric. pusti za kasnejši čas ali razdeli na posamezne dele. S tem sva Predlagala sem jim, da skupaj z otrokom počnejo stvari, za katere razvijala veščine samoregulacije, hkrati pa je učenec spoznaval je prej zmanjkalo časa. Lahko se igrajo razne družabne igre, osnovno uporabo spletnih učilnic. Naučila sva se prijaviti v lahko rišejo stripe, morda je tudi čas za učenje kuhanja (slika spletne učilnice, ob tem sva se pogovorila tudi o pomembnosti 2)… Ker je učenec bil najraje pred računalnikom, sem mu gesla. Kako mora biti geslo sestavljeno in zakaj je dobro, da je predlagala, da skupaj z družino raziščejo različne uporabne geslo zapleteno, pa vendarle takšno, da si ga lahko zapomnimo. spletne aplikacije. Staršem sem svetovala, naj pustijo otroku, da Prosti čas: tudi on predlaga dejavnost in jo vodi. Naj takrat starši ne dajejo Tukaj se je pojavljal še posebej velik izziv za motiviranje predlogov, ne kritizirajo njegovih odločitev, lahko pa ga učenca. Ves prosti čas je želel porabiti za igranje igric, iz sobe se pohvalijo za njegovo izvirnost in kreativnost. Tako se je učenec pravzaprav ni premaknil. Ob najinih spletnih srečanjih sva seznanil z aplikacijo za izdelovanje fotoknjig in to je postala poiskala na Youtube video posnetek razgibavanja za hrbtenico in njegova zaposlitev za kar precej popoldnevov. sproščanja in naredila nekaj vaj, nato pa načrtovala prosti čas z družinskimi člani. Kot eno od nalog si je izbral nalogo, da bo z babico pripravil oziroma se naučil pripravljati njegovo najljubšo jed. To nalogo sva časovno opredelila tako, da jo je moral opraviti do konca šolanja na daljavo. Komunikacijske veščine: Druženje s prijatelji je bilo prej zaradi njegove diagnoze zelo oteženo, saj je nenehno prihajalo do konfliktnih situacij. Zdaj je to potekalo izključno preko socialnih omrežij. V začetku je bilo komuniciranje omejeno le na druženje skozi igranje iger. Po svetovanju staršem pa so se kasneje učenci res začeli povezovati ne samo v igricah, ampak so se začeli pogovarjati tudi o nalogah, kako je kdo kaj naredil. Vzpostavljala se je medvrstniška pomoč. Tukaj sem lahko realizirala enega od pomembnih ciljev, ki sem si jih zastavila v individualiziranem programu, in sicer razvijanje socialnih in komunikacijskih veščin. Učenci so si med seboj ustvarili skupine, preko katerih so sodelovali in si pomagali. Najina naloga je bila, učenca s posebnimi potrebami čim bolje vključiti v te skupine. Tako sem ga preusmerila iz igranja iger na medvrstniško sodelovanje. 4 VEŠČINE VZGOJE NA DALJAVO – POMOČ IN SVETOVANJE STARŠEM Šolajoči se na domu potrebuje nadzor, usmerjanje, spodbudo in Slika 16. Prosti čas v času šolanja na daljavo podporo ter pozitivno pozornost za dobro opravljeno delo. [5] 468 5 ZAKLJUČEK REFERENCE Naš skupni trud, trud staršev in šole ter usmerjanje učenčeve [1] Gerič, I. 2000. Učna načela učenja na daljavo - didaktične aktivnosti v njegovo dobro je v času šolanja na domu obrodil osnove. sadove. Učenec je usvojil osnovna orodja in se digitalno http://www2.arnes.si/~sspmgiac/mirk2000/clanki/gerlic.ht opismenil do te mere, da je dokaj tekoče opravljal svoje šolske m zadolžitve, pa tudi stanje doma se je dokaj normaliziralo. [2] Matijević, A. 2016. Imate obsesivno kompulzivno motnjo? Zapiranje med štiri stene, odvisnost od računalnikih igric in Preverite.. nerazumevanje med družinskimi člani je počasi izginilo. Učenec https:/ novice.svet24.si/clanek/zdravje/580e033239871/obs je začel komunicirati z domačimi in z njimi preživel tudi nekaj esivno-kompulzivna-motnja-ali-vecen-dvom prostega časa. Domači so ga tudi spodbudili, da je izpolnil [3] Wikipedia. 2012. Wikipedia: the Free Encyclopedia. nalogo, ki sva si jo zadala pri uri dodatne strokovne pomoči na Spletna učilnica. daljavo, da ga babica nauči pripraviti njegovo najljubšo jed. https://sl.wikipedia.org/wiki/Spletna_u%C4%8Dilnica Učenec, ki so ga še pred tedni komaj zvabili iz svoje sobe na [4] Zaposleni Svetovalnega centra za otroke, mladostnike in večerjo z družino, drugače je ure in ure preživel v svoji sobi, je starše Maribor. 2020. Navodila za starše v času socialne tokrat presenetil. izolacije zaradi virusa SARS-CoV-2 (COVID-19). S svojo babico je pripravil njegovo najljubšo jed. In http://www.svet-center-mb.si/navodilo-starem-v-asu- zadovoljen nasmeh na njegovem licu pove več kot tisoč besed. socialne-izolacije-zaradi-novega-virusa-sars-cov-19-covid- Tedni v času korone so bili za vse družine preizkus kvalitete 19.html odnosov, sposobnosti obvladovanja, potrpežljivosti in tolerance [5] Anita Kovačik. 2009. Človek v socialnem okolju. vseh družinskih članov. Tej družini je tokrat uspelo. http://www.impletum.zavod- irc.si/docs/Skriti_dokumenti/Clovek_v_socialnem_okolju- Kovacik.pdf 469 Učenje angleščine z uporabo spletnega orodja Quizlet Learning English by using Quizlet Urška Delovec Osnovna šola Matije Valjavca Preddvor Šolska ulica 9 4205 Preddvor, Slovenija urska.delovec@os-preddvor.si POVZETEK smiselno celoto, zato lažje razumemo njihov pomen in si jih tudi hitreje zapomnimo. Današnji najstniki pa žal niso preveč Razvoj sodobne tehnologije prinaša spremembe tudi v navdušeni nad branjem. Namesto knjig jih ves čas obkrožajo izobraževanju, saj si v šolah pouka brez računalnika skorajda ne računalniki in pametni telefoni, zato jih lahko z vključevanjem moremo predstavljati. Pri poučevanju tujih jezikov se nam elementov IKT v pouk dodatno motiviramo za delo. Z različnimi ponuja veliko možnosti za popestritev pouka z uporabo različnih spletnimi orodji jim lahko ustvarimo zanimive možnosti za spletnih orodij. Eno izmed orodij, ki omogoča zabavno učenje spoznavanje novega besedišča oz. fraz, za širjenje besednega jezika, je Quizlet. Uporabimo ga lahko predvsem za predstavitev zaklada ter tudi za utrjevanje že znanih besed na zabaven način. novega besedišča učencem ter za utrjevanje že znanega besedišča. Učenci lahko to orodje uporabljajo za povsem samostojno učenje doma, zato se je za uporabno izkazalo tudi v obdobju šolanja na 2 QUIZLET daljavo. Quizlet je eno izmed spletnih orodij, ki ga lahko s pridom KLJUČNE BESEDE uporabimo pri pouku tujih jezikov, predvsem za učenje besedišča. Učenci se s pomočjo kartic ('flashcards') učijo besed Quizlet, spletno učno orodje, učenje besedišča, tuji jeziki oz. jih utrjujejo. Uporabljajo ga lahko samostojno doma, delo s ABSTRACT tem orodjem pa je možno vključiti tudi v redne ure pouka (uro npr. izvedemo v računalniški učilnici). V razredu ga lahko Due to the development of modern technology and its influence uporabimo kot uvodno motivacijo ob začetku ure, za ponavljanje on education, it is almost impossible to imagine school lessons besedišča ob koncu učne enote ali ugotavljanje predznanja pred nowadays without the use of ICT. Foreign languages teachers novo učno enoto. Poleg učenja besedišča omogoča tudi can choose from a variety of online learning tools to make the utrjevanje slovnice. lessons more diverse. The aim of this article is to present one of Orodje nam ponuja dve glavni možnosti. Prva je, da na spletni such online tools, Quizlet. Quizlet is primarily used for strani https://quizlet.com/en-gb izberemo zavihek ‘Search’ vocabulary learning and it makes learning a foreign language (iskanje) in pregledamo bazo nalog, ki so jih ustvarili drugi more enjoyable and interesting. Students can also use it at home uporabniki ter kakšno izmed njih rešimo. Če smo prijavljeni v for independent studying and because of that, it proved to be of Quizlet, lahko naloge, ki so nam všeč, shranimo med svoje great use during the period of distance learning. gradivo. Pri vseh nalogah je na voljo tudi gumb 'Customise' (slika 1), ki nam omogoča, da naloge, ki so jih ustvarili drugi KEYWORDS uporabniki, predelamo oz. popravimo, dodamo nove primere ali Quizlet, online learning tool, vocabulary learning, foreign določene primere odstranimo. languages Druga možnost, ki jo nudi Quizlet, pa je ustvarjanje lastnega gradiva – zavihek 'Create'. [1] 1 UVOD Tekoče izražanje v tujem jeziku je odvisno predvsem od človekovega besednega zaklada. Poznavanje slovničnih pravil je sicer pomembno, a brez širokega nabora besedišča je včasih težko sestaviti smiselno poved. Največ besed lahko spoznamo z branjem različnih besedil, saj so besede v besedilu povezane v Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 470 Slika 2. Prva stran kartice s slikovno iztočnico in prevodom (VIR: lasten, zajem zaslonske slike) Slika 1. Gumb 'Customise', ki omogoča predelavo naloge (VIR: lasten, zajem zaslonske slike) 3 USTVARJANJE NALOG Če želimo ustvariti naloge, se moramo na spletni strani https://quizlet.com/en-gb najprej registrirati. Nato v zgornjem levem kotu izberemo možnost 'Create' (ustvari). Nalogi, ki jo želimo kreirati, določimo naslov, lahko pa dodamo tudi kratek opis. Nastavimo, kdo lahko dostopa do naloge ('visitable to') ter Slika 3. Druga stran kartice z angleško besedo (VIR: lasten, uredimo pravice urejanja naloge ('editable by'). zajem zaslonske slike) V stolpec 'Term' vnesemo besedo ali frazo, za katero želimo, 4.2 Zavihek 'Learn' da se jo učenci naučijo oz. jo utrdijo, v desni stolpec 'Definition' Zavihek 'Learn' ni več namenjen spoznavanju besed, temveč pa vnesemo iztočnico, na podlagi katere morajo učenci ugotoviti učenju. Iz celotnega nabora besedišča računalnik naključno pravo besedo. Ta iztočnica je lahko slovenski prevod, slika, izbere 7 enot in preverja razumevanje ter pravilen zapis besed. angleška razlaga besede … Če želimo dodati slikovno iztočnico, Ob sliki, prevodu oz. razlagi ponudi štiri možne odgovore, izmed moramo v stolpcu 'Definition' izbrati gumb 'Image'. Odpre se katerih učenci izberejo pravilnega (slika 4) ali pa od njih zahteva, nam nabor sličic, med katerimi eno izberemo. da besedo pravilno zapišejo. Učenci o pravilnosti odgovora Ob koncu pritisnemo gumb 'Create' ter ustvarjeno nalogo po dobijo takojšnjo povratno informacijo. želji delimo z drugimi. Za uspešno dokončanje naloge je potrebno vnesti vsaj dve besedi. 4 AKTIVNOSTI ZNOTRAJ NALOG Ko vnesemo izbrano besedišče in pritisnemo gumb 'Create', Quizlet iz vnesenih besed oblikuje različne aktivnosti. Izbiramo lahko med karticami za učenje, nalogami za utrjevanje zapisa besed, nalogami za preverjanje znanja na različne načine ter igrami za utrjevanje. Obstaja tudi možnost povezovanja igralcev v skupine. Slika 4. Primer kartice v zavihku 'Learn' (VIR: lasten, 4.1 Zavihek 'Flashcards' zajem zaslonske slike) Zavihek 'Flashcards' omogoča učencem pregled in spoznavanje 4.3 Zavihek 'Write' izbranega besedišča s pomočjo dvostranskih kartic. Najprej je Zavihek 'Write' je namenjen utrjevanju pisanja in črkovanja. Na prikazana tista stran kartice, ki ponuja slikovno iztočnico, podlagi besedne ali slikovne iztočnice morajo učenci besedo slovenski prevod oz. angleško razlago (slika 2). Če učenci zapisati (slika 5). Takoj dobijo povratno informacijo o pritisnejo na kartico, se le-ta obrne in prikaže se beseda, za katero pravilnosti zapisa. Če je zapis napačen, se jim prikaže pravilen želimo, da se jo naučijo (slika 3). Ob tem slišijo tudi izgovorjavo zapis, ob tem pa slišijo tudi izgovorjavo besede. Če učenci ne besede. Če želijo besedo slišati še enkrat, pritisnejo ikono vedo odgovora, si lahko pomagajo z gumbom 'Answer' zvočnika v zgornjem desnem kotu kartice. S puščicama levo in (odgovor). Prikaže se jim pravilna beseda, ki pa jo morajo desno, ki sta pod kartico, se premikajo skozi celotno besedišče. prepisati, če želijo nadaljevati z delom. 471 Slika 5. Primer kartice v zavihku 'Write' (VIR: lasten, Slika 8. Primer igre 'Gravity' (VIR: lasten, zajem zajem zaslonske slike) zaslonske slike) 4.7 Quizlet Live 4.4 Zavihek 'Spell' Spletno orodje ponuja tudi možnost Quizlet Live, kjer učenci Zavihek 'Spell' je zelo podoben prejšnjemu, dodana je le še tekmujejo med seboj v poznavanju besedišča. Učenci se prijavijo zvočna podoba besede. Učenci vidijo slikovno oz. besedno v Quizlet Live s kodo in svojim imenom, nato pa jih računalnik iztočnico ter slišijo izgovorjavo besede, nato pa morajo besedo naključno razdeli v skupine. Za tekmovanje med skupinami pravilno zapisati. Če se pri zapisu zmotijo, jih spletno orodje morajo biti v Quizlet prijavljeni vsaj štirje učenci, da lahko opozori na napako in pokaže, kako napako popraviti. poteka tekma med dvojicama. Več kot je prijavljenih učencev, 4.5 Zavihek 'Test' več skupin se tvori. Vsi učenci v skupini morajo sodelovati pri Ta zavihek preverja znanje učencev z različnimi nalogami (slika odgovarjanju na vprašanja, saj drugače ne morejo uspešno 6) in nudi takojšnjo povratno informacijo o njihovem znanju. zaključiti naloge. Vsak učenec ima namreč le del odgovorov, le eden v skupini pa ima pravi odgovor. Učenci morajo znotraj skupine dobro sodelovati med seboj, hkrati pa tekmujejo proti drugim skupinam. 5 PREDNOSTI QUIZLETA Ena izmed glavnih prednosti tega orodja je, da lahko učitelj na dokaj hiter in preprost način svojim učencem ustvari zanimive naloge za utrjevanje točno tistega besedišča, ki ga pri pouku z njimi obravnava. Z reševanjem teh nalog se lahko učenci doma samostojno pripravljajo tudi na ocenjevanje znanja. Učitelj jim lahko pripravi še dodatne naloge za širjenje besednega zaklada. Slika 6. Primer naloge v zavihku 'Test' (VIR: lasten, Orodje je možno uporabljati v različnih razredih, z različno zajem zaslonske slike) starimi učenci. Količino besedišča in zahtevnost nalog 4.6 Igri za utrjevanje znanja prilagodimo glede na razred in predznanje otrok. Za mlajše Quizlet vsebuje tudi dve zabavni igri za utrjevanje besedišča, učence pripravimo preprostejše naloge, kjer morajo povezati 'Match' (povezovanje parov) ter 'Gravity'. sličico z ustrezno besedo v tujem jeziku ali slovensko besedo z angleško (npr. slon – elephant). Za starejše učence ustvarimo Pri igri 'Match' morajo učenci poiskati pare, ob tem pa težje naloge, ki od njih zahtevajo, da povežejo pojme in definicije računalnik meri, kako hitro jim bo to uspelo (slika 7). (npr. waterfall – water, especially from a river or stream, Igra 'Gravity' od učencev zahteva, da zapišejo pravilno dropping from a higher to a lower point). besedo, preden bo Zemljo zadel asteroid. S pravilnimi odgovori Orodje lahko uporabimo tudi pri delu z nadarjenimi učenci, učenci zbirajo točke in napredujejo iz nižje na višjo stopnjo igre saj jih lahko prosimo, da pripravijo kakšno nalogo za svoje (slika 8). sošolce. Merjenje časa in zbiranje točk učence precej motivirata, saj Učenci si lahko s pomočjo tega orodja sami ustvarijo svoj med seboj radi tekmujejo in se trudijo doseči čim boljši rezultat. slovarček oz. seznam besed z definicijami, ki jih morajo znati. Quizlet je možno uporabiti tudi za utrjevanje nepravilnih glagolov ter različnih slovničnih struktur. Ena izmed možnosti je, da pripravimo tip naloge, kjer je potrebno glagol v oklepaju postaviti v ustrezen čas (t. i. 'gap fill'). S tem učenci vadijo rabo časov. 6 ZAKLJUČEK Slika 7. Primer igre 'Match' (VIR: lasten, zajem Quizlet se je meni osebno izkazal za zelo uporabno orodje. Po zaslonske slike) eni strani je zelo preprost za uporabo, po drugi pa učencem omogoča zabavno učenje jezika. Quizlet uporabljam v vseh razredih, ki jih poučujem. V prejšnjih letih sem učencem pripravljala naloge, da so lahko doma na drugačen način utrjevali 472 učno snov. Občasno so naloge reševali tudi v šoli v računalniški zabaven in zanimiv način ter jim omogoča boljše pomnjenje učilnici. V letošnjem šolskem letu pa sem ga uporabljala tudi snovi. med obdobjem poučevanja na daljavo. Učencem sem na ta način predstavila novo besedišče. S pomočjo slikovnih kartic so se najprej seznanili z besedami, ob tem so slišali tudi pravilno VIR izgovorjavo, nato pa so lahko reševali še naloge za utrjevanje. [1] Spletno orodje Quizlet Ob povratku učencev v šole se je izkazalo, da so snov dokaj https://quizlet.com/en-gb (pridobljeno 20. 8. 2020) uspešno predelali. Priprava nalog učitelju sicer vzame nekaj časa, vendar pa pester nabor aktivnosti učencem omogoča učenje jezika na 473 Razvoj krmilnika za upravljanje senčil Development of a controller for window blinds management Aleksandar Dojčinović Martin Prelog Uroš Rajkovič ADC sistemi d.o.o. Tenetišče 4 Univerza v Mariboru, Fakulteta za Medetova ulica 1 4204 Golnik, Slovenija organizacijske vede 4000 Kranj, Slovenija kobramic@gmail.com Kidričeva cesta 55a adojci@gmail.com 4000 Kranj, Slovenija uros.rajkovic@um.si POVZETEK izdelkov in študijo primera, kjer smo na podlagi kritične analize zbranih podatkov podali konno oceno. V prispevku smo obravnavali probleme senčil in njihovo krmiljenje preko mobilne naprave ali tablice. Podjetje ADC Med seboj smo primerjali sisteme za krmiljenje senčil različnih sistemi d.o.o. združuje tradicionalno upravljanje senčil s stikali z produktov (Sonfy, Fibaro, BleBox, Zamel, Elero itd…). Na novitetami na področju IoT. Časi se spreminjajo z temu pa tudi podlagi analize smo izbrane rešitve implementirali na testno naš način življenja in kjer je čas denar, smo omogočili, da okolje. Ob implementaciji smo odkrili veliko napak, ki jih redko obstoječe sisteme lahko nadgradimo in jih upravljamo z zalsedimo v teoriji. Implementacija vsakega krmilnika je zgodba telefonom, in to združeno. Sistem je primeren tako za zase. nadogradnjo obstoječih sistemov in to brez dodatnih gradbenih del, kot tudi za novogradnje. Poleg vsega naštetega stranka lahko KLJUČNE BESEDE upravlja senčila tudi z daljincem in tako je paket popoln. Stranka IoT, krmilnik, senčila, WIFI tako ni v dilemi, kateri sistem je boljši, kaj je bolj primerno. Z ADC sistemi stranka dobi popolni nadzor nad svojimi senčili. V ABSTRACT prispevku smo predstavili model, ki omogoča varnost, In the article we discussed the problems of window shades and zanesljivost, enostavnost in bo podprl zahteve strank. how to control them remotely by means of a mobile device or Z razvojem tehnologije se beleži porast IoT v vseh oblikah, zato tablet. ADC sistemi d.o.o. combines the traditional controlling of v zadnjem času vse več ljudi poizkuša uporabljati stortive window shades with switches, with the novelties of IoT. As our interneta v oblaku. Namen IoT-ja je avtomatizirati procese, ki so lives get drastically changed by new technology and our time del vsakdanja. V praksi je najbolj pogost način IoT-ja krmiljenje becomes more and more valuable, saving time on mundane tasks električnih elementov preko posameznih krmilnikov. becomes very important. That's why our solution allows existing systems to be easily upgraded and controlled remotely, Prispevek obravnava probleme krimljenja senčil in njihovih effectively saving you time and therefor money. The solution can implementacij. Ljudje se vse bolj zavedajo pomena interneta in be used to upgrade existing systems with no additional prednosti, ki jih ponuja. Sodobna informacijsko-komunikacijka construction work but it can also be installed in new buildings. tehnologija omogoča nove možnosti uporabe pametnih naprav, Besides the ability to control devices via your mobile device or hkrati pa se je strojna oprema v zadnjem času močno pocenila. tablet, the solution also offers a remote, so all grounds are Namen prispevka je razsikati, enostavno opisati in predstaviti covered and the customer needn't worry, about getting the best prednosti in slabosti ADC krmilnikov, ter jih implementirati na system for their use case, as the solution allows their preferences sisteme senčenja pri podjetju Roltek d.o.o. Cilj prispevka je to be respected. With ADC sistemi the customer gets total control analizirati ter teoretično in praktično utemeljiti stroškovno over their window shades. In the article we presented a model ugoden in učinkovit krmilni sistem za potrebe krmiljenja senčil. which allows for security, reliability, simplicity and supporting V prispevku je predstavljena tudi realizacija ADC krmilnika za the needs of customers. potrebe proizvajalcev senčil. With technological advancement IoT is growing in all directions, Pri pisanju prispevka smo se osredotočili na analizio primarnih and recently more and more people are trying to use cloud in sekundarnih virov, s primerjalno analizo konkurenčnih services. The purpose of IoT is to automate everyday processes. In practice the most common example of IoT is controlling electrical components with individual controllers. The article talks about the problems of systems controlling window shades and implementing such systems. People are Permission to make digital or hard copies of part or all of this work for personal or becoming more and more aware of the internet and the classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full advantages it offers. Modern information and communications citation on the first page. Copyrights for third-party components of this work must technology allows for new uses of smart devices, while also be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia drastically decreasing their cost. © 2020 Copyright held by the owner/author(s). 474 The purpose of the article is to research, simply describe and Obravnavali bomo uporabo IoT tehnologije za krmiljenje present the advantages and disadvantages of ADC controllers senčil. Tukaj se pogosto pojavljajo etična vprašanja kot so: and to implement them with window shading systems of the 1. varstvo osebnih podatkov, company Rolte d.o.o. The goal of this article is to analyze, 2. možnosti zlorabe teh podatkov, theoretically and practically, a cost effective and powerful 3. nedovoljeni vpogled nepooblaščenim oseba, controller solution for the needs of controlling window shades. 4. nadzor in kršenje pravic do zasebnosti. The article also desribes the realization of the ADC controller for IoT tehnologija na ljudi vpliva blagodejno saj ima na ljudi v the requirements of the manufacturers of window shades. psihološkem smislu (občutek varnosti) dober vpliv. Poleg When writing the article, focus was put on the analysis of nadzora senčil nam IoT ponuja ogromno drugih možnosti npr. primary and secondary sources, with comparative analysis of glasovno upravljanje itd. competeing products and a study of a concrete example, where a V zadnjih letih je IoT mnogo napredoval, saj se iz dneva v final score was derived from the critical analysis of collected data. dan izpopolnjuje in nadgrajuje. Nadzorovanje naprav preko interneta je najbolj razširjena metoda nadzorovanja. Poleg We compared different solutions for controlling window shades krmilnikov poznamo tudi druge proizvode, ki se uporabljajo za (Sonfy, Fibaro, BleBox, Zamel, Elero, etc.). Based on the krmiljenje senčil (fizično stikalo, daljinec itd…). analysis selected solutions were implemented in a test ADC krmilniki se iz dneva v dan vedno bolj razvijajo in environment. During implementation we discovered many njihova uporaba narašča. Vedno znova nadgradimo programsko shortcomins, which are rarely talked about in theory. The opremo, ki omogoča, da z malo znanja lahko popolnoma implementation of every controller is a story in of it self. nadziramo lasten sistem. KEYWORDS 2.2 Cilj Cilj prispevka je predstaviti rešitev, ki bo olajšala krmiljenje IoT, controller, blinds, WIFI senčil, omogočila večjo varnost sistema, prav tako pa olajšala delo proizvajalcem in kupcem. Poleg večje varnosti sistema vdor 1 UVOD v sistem je skoraj nemogoč. S tem pa so zaščitene tudi stranke, saj jim varnost in enostaven uporabniški vmesnik zagotovi Prvi produkt je nastal kot plod doktorske naloge. Želja oziroma kakovost, ki so jo plačale. Olajšano je tudi dodajanje novih cilj je bil podpreti IoT tehnologije (ang. Internet of Things), ki se naprav, ki je popolnoma avtomatizirano, saj se osebni podatki je nadgradila v lasten razvoj programske in strojne opreme. ADC hranijo v oblaku in do njih ne more nihče dostopati razen vmesnik za mobilno upravljanje senčil je tako postal prvi produkt uporabnika. ADC sistem je kompatibilen z vsemi obstoječimi podjetja, ki se je razširil v mobilno upravljanje električnih naprav sistemi senčenja, saj predstavlja zanesljiv, varen, pregleden in (rolete, senčila, tende, garažna vrata…). Pri razvoju produkta je učinkovit sistem za mobilno upravljanje senčil. sodelovalo več kot 30 oseb iz različnih strok. Z svojim znanjem so sodelovale tudi fakultete in sicer Fakulteta za organizacijske 2.3 Predpostavke in omejitve vede, Fakulteta za elektrotehniko in Fakulteta za računalništvo. V prispevku kot predpostavko navajamo zlorabo osebnih Strojna oprema je v celoti razvita v Sloveniji in s pomočjo podatkov, nenapovedano opazovanje, nadzor krmiljenja senčil in partnerski podjetij tudi narejena v Sloveniji. S tem sledimo kršenje pravic do zasebnosti. Zelo velik problem je, da zloraba ni visokim zahtevam Evropskih standardov in kvalitete. Vmesnik nikoli odkrita oziroma traja zelo dolgo časa, zato lahko je testiran v laboratoriju na Fakulteti za organizacijske vede na pričakujemo, da se bodo ta dejanja v prihodnosti še vedno več kot 1.000.000 premikov, kar v praksi pomeni, če bi v dogajala. V vsakdanjem življenju se srečujemo z novimi povprečju vsak dan naredili 10 premikov z roletami, bi imeli oblikami zlorab, ki nam škodujejo. Predpostavimo lahko, da na vmesnik več kot 273 let. podlagi prejšnjih ugotovitev postavimo model, ki bo temeljil na Za celoviti spekter ponudbe smo v celoti razvili tudi mobilnem krmiljenju senčil in bo primeren za proizvajalce programsko opremo v Sloveniji. To nam je ključno, da imamo senčil. možnost razvijanja in posodabljanja programske opreme – Glavna omejitev prispevka bo najti podjetje, ki bo želelo aplikacij, kar nam prinaša še dodatno konkurenčno prednost. sodelovati in odgovarjati na vprašanja, ki jih večina Hitro odzivnost na potrebe tržišča, vsa navodila in aplikacije v proizvajalcev senčil ne želi javno razkriti, ker to smatrajo za slovenskem jeziku. poslovno skrivnost. Kot omejitev pa lahko izpostavimo obseg ter zapletenost implementacije ADC krmilnika v obstoječe sisteme senčil. 2 METODOLOGIJA 2.4 Predvidene metode raziskovanja 2.1 Opredelitev problema Pregledali bomo literature po različnih svetovnih bazah kot so Svet v katerem živimo se hitro spreminja s temu pa tudi naše Web of Science, Scopus, Google Scholar in Research Gate. navade, postopki, vrednote, okolje, ljudje itd. Tehnologija je v Literaturo bomo iskali z ključnimi besedami skill acquisition: vseh segmentih našega življenja. Način življenja, ki smog a IoT, Controller, blinds; ter z različnimi kombinacijami uporabljali še do nedavnega je zastarel in ne daje več željenih omenjenih ključnih besed. rezultatov. Spremembe, ki smo jim priča iz dneva v dan so Kontaktirali bomo proizvajalca senčil Roltek d.o.o., kjer usmerjene v sodobno tehnologijo in avtomatizacijo posameznih bomo z njimi opravili intervju in preučili sisteme senčil, ki jih procesov. Ljudje se vse bolj zanašamo na tehnologijo. imajo proizvajalci. Na podlagi kritičnega pregleda sekundarnih virov bomo ugotovili, katere zahteve in potrebe imajo 475 proizvajalci senčil in katere zahteve in potrebe imajo potrošniki, Z delujočim prototipom in strežnikom smo se sedaj obrnili k da bodo kar se da enostavno upravljali senčila in imeli popolni razvoju aplikacije, s katero bi končni uporabnik lahko krmilil nadzro nad sistemov. naše naprave. Iz dosedanjih raziskav ostalih rešitev, smo V praktičnem delu raziskave bomo nalogo razdelili na dva ugotovili, da aplikacije drugih ponudnikov niso vedno najbolj dela in sicer: enostavne za uporabo. Torej je bil naš cilj dobro razumljen, 1. praktični prikaz implementacije ADC krmilnika na razviti bi morali aplikacijo, ki je enostavna za uporabo vendar v obstoječi sistem senčil podjetja Roltek; ta namen ne zanemari funkcionalnosti. 2. postaviti model z ADC krmilniki, ki bo podpora informacijskim sistemom senčil z namenom ustvariti nov tehnološki ekosistem na področju upravljanja senčil. 3 REZULTATI Z majhno ekipo iz različnih področji, od strojne do programske opreme, smo leta 2017 začeli z razvijanjem rešitve za krmiljenje senčili. Po nekaj mesecih preučevanja obstoječih rešitev smo bili pripravljeni, da naredimo pomembne odločitve glede izbire tehnologij. Odločili smo se, da bo naša rešitev delovala preko WiFi-ja, saj bo le tako lahko naprava res povezana s celotnim internetom in jo bomo lahko krmilili iz kjerkoli, dokler bomo imeli internetno povezavo [2] [3] [4]. S to izbiro smo se prav tako odrešili potrebe po dragem zvezdišču (ang. hub), ki predstavlja dodatni strošek, kar je bila v naših očeh velika prednost. Prav tako nas je ta odločitev pripeljala do zelo enostavnega procesa konfiguracije; napravi je potrebno le omogočiti dostop do brezžičnega omrežja z internetnim dostopom, nato pa lahko za vso nadaljnjo konfiguracijo poskrbi naprava sama oziroma celoten proces je avtomatiziran. Po tem smo se odločili zgraditi prvi prototip. Tekom razvoja programske opreme, ki teče na mikro kontrolerju smo naleteli na mnoge težave in nova vprašanja, na katera prej nismo pomislili: • Kako komunicirati z napravami, ki niso v dosegu mreže? • Kako omejiti dostop do posameznih naprav? • Kako overiti uporabnika in mu omogočiti dostop do naprav, saj so naprave imele povezavo do interneta, vendar je bilo do njih, brez njihovega ip naslova težko dostopati? • Kako zagotoviti zanesljivost in varnost sistema? • Kako povezati mikro krmilnik z obstoječimi sistemi senčenja? Vprašanja so nas vodila k ustvarjanju centralnega strežnika, s katerim bi komunicirale vse naprave. Tako bi lahko vedno imeli Slika 1: Seznam senčil v aplikaciji ADC povezavo do vsake naprave in omejili dostop do njih, saj bi morali vsi ukazi potovati preko strežnika, ki bi uporabnike overil Tekom razvoja aplikacije (slika 1) smo po večih revizijah in avtoriziral. S to odločitvjo je sicer lokalno krmiljenje preko izpopolnili fizično napravo in program, ki je tekel na njej. brezžične mreže postalo nemogoče, saj nismo mogli neposredno Naprava je sedaj imela mnoge funkcionalosti, nekatere si na komunicirati s krmilnikom, a je bila dodana varnost več kot začetku, sploh nismo mogli zamisliti. Napravam smo dodali vredna te izgube. Postavitev strežnika je bila prav tako zahteven zmožnost širjenja WiFi omrežja in se tako rešili problemov z podvig, saj nihče v ekipi ni dobro poznal strežniške tehnologije. napravami, ki niso bile v dosegu obstoječega WiFi omrežja. Po nekaj tednih je bil postavljen naš prvi strežnik in razvoj se je Napravam smo prav tako, dodali urnik, s pomočjo katerega so lahko nadaljeval. Z nadaljnjim razvojem pa so prišli novi lahko, ob v naprej določenih časih, same odprle oziroma zaprle problemi, naša naprava je bila namreč popolnoma neoperabilna, senčila. Iz urnika smo prav tako razvili naključno premikanje, ki kadar ni imela internetnega dostopa. Našemu produktu smo lahko odvrne morebitne vlomilce, kadar se za daljši čas ne dodali možnost krmiljenja s stikalom, kar se je izkazalo za zelo zadržujemo v bližini stanovanja. Vsako napravo lahko dvignemo zaželeno funkcionalnost pri bodočih kupcih. na željeno pozicijo, ki je prikazana grafično v obliki senčila in v odstotkih (slika 2). 476 Naš strežnik, ki je bil prvotno zasnovan le za kontrolo naprav, nepridiprave pred vlomom). Vse to je možno upravljati tudi je moral z aplikacijo prav tako rasti. Kasneje je postala aplikacija preko našega spletnega portala, ki je dostopen na naši spletni tako zahtevna, da se je začel razvoj novega strežnika, ki bi skrbel strani. Tako lahko naš sistem upravljamo z: le za komunikacijo med strežnikom za naprave ter aplikacijo. Z 1. pametnim telefonom, novim strežnikom, pa so prišle nove priložnosti. Iz dosedanjega 2. tablico, razvoja smo se namreč veliko naučili. Na novem strežniku smo zelo izboljšali varnost, poenostavili notranjo uporabo in 3. spletni portal, omogočili dostop do uporabnikovih naprav tudi drugim 4. fizično stikalo. storitvam, ki jih pooblasti uporabnik. Tako bo v prihodnosti mogoče naprave krmiliti tudi z glasovnimi ukazi preko sistemov kot so Google Assistant, Siri, Neo, Eon, Alexa . . in jih vključiti v mnoge druge storitve. Danes, 3 leta od začetka razvoja rešitve, rešitev še vedno ni popolna. Vedno se najde nova funkcionalnost, ki jo uporabniki želijo, vendar rešitev stoji na močnih temeljih, kar nam omogoča njeno širitev v skoraj katero koli smer. Brez daljšega obdobja razvoja, bi rešitev morda prav tako obstajala, vendar bi bila njena prihodnost nejasna. Zmožnost širjenja rešitve, sledenje najnovejšim razvojem in obvladovanje že obstoječe tehnologije, nas privedejo do zelo močnega produkta. Zelo pomembna pa je tudi ekipa in medsebojni odnosi, ki se razvijajta tekom razvoja. Zavedamo se, da je danes vedno bolj pomembna komponenta čas, čas je denar. Kar v praksi največkrat pomeni manj je več, manj kompleksni stvari, več razumljivosti. S tem duhom tudi gradimo celotni koncept ADC sistemov, na razumljivosti in enostavnosti. Modul je majhnih dimenzij z namenom vgradnje v ozadje električne doze, kar stranki omogoča hitri priklop brez dodatnih gradbenih del. Kdor že uporablja stikala za upravljanje senčil se enostavno v ozadje električne doze namesti še modul in je stvar urejena. Modul je enostaven za priklop v električno omrežje, saj priklopimo napajanje modula, priklopimo senčilo in stvar deluje. Prav tako lahko priklopimo tudi fizično tipalo oziroma stikalo . Na modulu so slikovna navodila v standardni obliki kar vsak mojster, ki se spozna na električna omrežja lahko priklopi brez dodatnih navodil. Seveda smo navodila tudi pripravili, ki zajemajo manj kot 1 stran in še to v slikovni obliki z dodanim tekstom. Aplikacija je v celoti v Slovenskem jeziku omogoča pa tudi svetovne jezike (Angleščino, Nemščino, Italijanščino, Srbščino, Hrvaščino). V aplikaciji so slikovni prikazi narejeni tako, da že iz slike razločimo roleto ali žaluzijo in tudi senčenost žaluzije. V ozadju pa opazujemo tudi vreme, ki ga napoveduje OpenWeather API. Aplikacija se naloži na pametni telefon na način kot večina aplikacij. Možnih je več poti do aplikacije, najbolj priporočamo, da obiščete našo spletno stran (www.adcsistemi.si) kjer se nahaja povezava do aplikacije. Lahko pa aplikacijo naložite tudi preko Trgovina Play ali App Store. Ko je aplikacija naložena nas tako Slika 2: Krmiljene posameznega senčila imenovani čarovnik vodi skozi prijavo računa v ADC sistemu, kar lahko opravi vsak, ki je vešč telefonov. Ko imamo kreiran V podjetju ADC sistemi se zavedamo, da je za uspešno uporabniški račun lahko pričnemo z dodajanjem modulov na zgodbo o uspehu potrebno sodelovanje s trgom, zato tudi obstoječi sistem senčil. Aplikacija nas vodi skozi postopek sodelujemo z monterji senčil. Za njih imamo pripravljeno spoznavanja, lahko pa prepustimo mojstrom - monterjem senčil, predstavitev izdelkov in izobraževanje priklopa sistema. Ker je da opravijo inštalacijo v celoti. Po opravljenem procesu priklop modula enostaven, ne potrebujemo dolgih izobraževanj dodajanja naprave se zabava začne. Senčila upravljamo s za monterje, v večini primerov samo predstavitev. Razumljivost telefonom. Poleg klasičnih uporabniških funkciji, kot so dvig, in enostavnost aplikacije pa tudi omogoča izvedbo kratkega spust, delni spust senčil imamo možnost ustvariti si različne izpopolnjevanja znanja. Vse skupaj je tako enostavno, da temu scenarije, časovni zamik premika senčil, funkcija dvig senčil ob ne moremo niti reči izobraževanje, bolj izpopolnjevanje znanja sončnem vzhodu, kar aplikacija sama zazna, kdaj je to na lokaciji na drugačnost. hiše, spust ob sončnem zahodu, ali pa naključno premikanje senčil (s tem vtis, da je nekdo doma - namen, da odvrnemo 477 4 DISKUSIJA Na DHCP-ju moramo urediti IP naslove, saj ob daljšem Ob implementaciji ADC krmilnikov so se pojavile določene izpadu elektrike seja poteče in se IP naslovi med seboj lahko težave, ki jih nismo predvideli v začetku razvoja. Pri idejnem zamenjajo, tako da v sistemu dobijo druga imena. Za rešitev razvoju ADC krmilnika so se oprli predvsem na teorijo, vendar enostavno nastavimo statične IP-je in nimamo nobenih smo ob implementaciji ugotovili, da se teorija in praksa problemov s tem. razlikujeta in nekaterih težav ob sami implementaciji v teoriji Podjetje Roltek d.o.o. [1] nam je omogočilo celoten vpogled nismo zasledili. v sisteme senčil. Kot največji proizvajalec senčil smo od njih Ob priklopu ADC krmilnika smo natelteli na težavo, saj je dobili informacije iz prve roke. Velikokrat so nam pomagali tako bilo premalo priključkov in nismo mogli prikklopiti motor z nasveti, opremo, sistemi in pa tudi pri razvoju krmilnika. senčila in pa fizično stikalo. Nato smo z podjetjem Wurth Predstavili so nam sodobne rešitve za krmiljenje senčil, ki so Elektronika našli terminal, ki ima dovolj priključkov za priklop trenutno na trgu. Z njihovo pomočjo se je razvil ADC krmilnik celotnega sistema. do te mere, da je danes najsodobnejši krmilnik za krmiljenje Pri določitvi položaja senčila smo imeli ogromno problemov, senčil, kjer strankam zagotavlja varnost in enostavnost [5]. saj nismo mogli določiti natančnega položaja. Prvotno smo merili celoten čas dviga in spusta senčil in glede na čas določili 5 ZAKLJUČEK natančen položaj. Vendar ta čas se je zaokroževal in vsaka nadaljna akcija je bila napačna in ta odstopanja so bila vedno Z napredkom tehnologije se je izboljaša tudi IoT tehnologija ki večja in večja. Problem smo rešili tako, da smo v vezje vgradili je postala boljša in cenovno dostopnejša večjemu številu ljudi. senzor toka, ki nadzira premik senčila. In dokler se senčilo IoT nas spremlja na vsakem koraku npr. v službi, v trgovini, premika senzor toka zazna električni tok in na podlagi našega domofonih, šolah, letališčih in tudi doma. algoritma določi točnen položaj senčila. Prav tako lahko z Poznamo več vrst krmilnikov. Ko smo prebrskali nekaj pomočjo senzorja toka ugotovimo, ali je senčilo spuščeno ali različne strokovne literature, smo ugotovili, da je krmilnikov dvignjeno in pri uporabi fizičnega stikala lahko ugotovimo, kdaj izredno veliko in se med seboj razlikujejo po ceni, velikosti, je fizično stikalo prenehalo upravljati senčilo. zmogljivosti, tehnologiji itd. Pri določenih krmilnikih smo naleteli na težavo z omrežno Najboljša podjetja na področju senčil nam ponujajo veliko povezavo. Povezava med krmilnikom in domačo mrežo je bila sistemo za krmiljenje senčil od klasičnih sistemov, do sistemov izredno slaba. Več kot 20 krmilnikov smo testirali in pri vseh so z daljinskim upravljanjem in mobilnimi sistemi, kjer so krmilniki bile neke skrite napake. Nakar smo kontaktirali proizvajalca preko radijskega signala povezavni v dodatno centralno enoto. krmilnikov in jih opozorili na napake in jim posredovali naše Naš model je postavljen sodobno in poleg interneta za delovanje rezultate. Proizvajalec je preučil naše rezultate in nam sporočil, ne potrebujemo ničesar. da so skoraj vsi krmilniki bile kopije in da niso to njihovi ADC krmilniki so v Sloveniji za potrebe upravljanja senčil krmilniki ampak kopije ostalih kitajskih podjetij. Poslali so nam relativno novi, kljub temu pa se že nezadržano pričenjajo njihove prave krmilnike in takrat se je kar nekaj napak odpravilo. uveljavljati, največkrat v kombinaciji z senčili, ki se upravljajo Tudi povezave z mrežo so se same odpravile. preko fizičnih stikal. Ugotovili smo tudi pomankljivost, in sicer ko je sistem že Iz predpostavljene realizacije ADC sistema za potrebe deloval, smo našli “mrtve kote”, ki jih naš krmilnik ni pokril, pa krmiljenja senčil je razvidno, da omenjena tehnologija poleg čeprav smo predvidevali da jih bo. Torej v teh kotih ni bila dovolj svoje praktične vrednosti, ki se izraža predvsem v bistveno močna povezava domačega omrežja in našega krmilnika. kakovostnejšemu WIFI signal, v sodobni izvedvi strojne opreme, Problem smo rešili z postavitvijo pametnega WIFI-ja. Vsak ADC z možnostjo dostopa do nastavitev omrežnih naprav na daljavo krmilnik je lahko tudi dostopna točka in deli internetni signal ter v prihranku instalacij, saj za svoje delovanje internetno naprej. To pomeni, da ni več mrtvih točk in stranki ni potrebno povezavo brez vsakršnih dodatnih centralnih enot ali zvezdišč. kupiti dodatnega ojačevalca WIFI signala. Vsak dodatni krmilnik posledično povzroči povečanje REFERENCE količine prenosa podatkov. Več krmilnikov zagotavlja več API klicev. Zato smo skupaj z podjetjem DHH d.o.o. postavili [1] Roltek d.o.o. (2020). Pridobljeno dne 1. september na strežnik in hitrost internetne povezave tako, da zadovoljimo vse https://www.roltek.si/. potrebe in želje naših strank. [2] Srivastava, A., Gupta, S., Quamara, M., Chaudhary, P., Fizična zaščita ADC krmilnika je zelo pomembna. Dostop Aski, V. J. (2020). Future IoT-enabled threats and mora biti omogočen samo določenim osebam, ki imajo znanje iz vulnerabilities: State of the art, challenges, and future elektrotehnike. prospects. International Journal of Communication Med testiranjem ADC krmilnika je prišlo do padca internetne Systems. Vol. 33. povezave in tako do celotnega izpada ADC sistema. Kasneje smo [3] Li, L., Chen, S., Chen, Z., Quek. T.Q.S. (2020). Massive ugotovili, da so bila kriva vzdrževalna dela, ki jih opravljalo IoT Connections. Wiley 5G Ref: The Essenital 5G podjetje Telekom d.d. Če ADC krmilniki komunicirajo v oblaku Reference Online. preko internetne povezave, potem je v tistem času, ko se [4] Souri, A., Hussein, A., Hoseyninezhad, M., Norouzi, M. opravljajo vzdrževalna Telekomova dela, sistem praktično mrtev. (2019). A systematic review of IoT communication Še vedno pa senčila lahko upravljamo preko fizičnih stikal, saj strategies for an efficient smart environment. Transactions za upravljanje le teh ne potrebujemo internetne povezave. on Emerging Telecommunications Technologies. 478 [5] Naylor, D., Shahid, H., Harrison, S.J., Oosthuizen, P.H. blinds on window thermal performance. International (2005). A simplified method for modelling the effect of Journal of Energy Research. Vol 30, Iss. 7. 479 Šolsko delo na daljavo v osnovni šoli Distance learning in primary school Radmila Drvarič Osnovna šola Draga Kobala Maribor Tolstojeva ulica 3 2000 Maribor, Slovenija radmila@osdk.si POVZETEK whole work method had to be changed and adapted. But the results are not very encouraging. It was hard work for the Sredi marca 2020 so osnovne šole zaprle šolska vrata in nihče ni teachers as well as for the students and their parents. Distance vedel za kako dolgo. Občutki vsakega izmed nas so bili različni, learning is a relatively good solution in times of need, but not for a zaskrbljenost je naraščala. Kako sedaj? Vrženi smo bili iz cone long periods of time. Differences in the students’ knowledge and udobja v neznano. Občutek varnosti je zamenjal občutek their social differences are increasing. Teaching is not only about negotovosti. Postavljeni smo bili pred dejstvo, da bo pouk gaining knowledge. The students’ are lacking in social potekal zelo drugače. Spoprijeti smo se morali z novim načinom interactions. Despite all the difficulties we encountered in dela, ki je marsikomu povzročal velike težave. Če smo do sedaj working remotely, we learned a lot, and we developed digital imeli odpor do računalnika, smo ga lahko zdaj imeli še bolj, saj competencies that are a means of lifelong learning. se nihče ni zavedal, kaj bo to potegnilo za seboj. Ure in ure sedenja pred računalnikom, ure in ure dela z računalnikom. KEYWORDS Celotno delo je bilo treba spremeniti in prilagoditi. A rezultati niso nič kaj vzpodbudni. To je bilo težko delo za učitelje kot za Computer, distance learning, knowledge, social interactions, učence in njihove starše. Pouk na daljavo je relativno dobra digital competency rešitev v stiski, a ne za daljše obdobje. Povečujejo se razlike v znanju in socialne razlike. A pouk ni le pridobivanje znanja. 1 UVOD Primanjkljaj se je čutil prav tako v socialnih interakcijah. Kljub vsem težavam, ki smo jih pri delu na daljavo imeli, smo se Ko smo 13. marca 2020 poslali učence domov, si niti v sanjah marsikaj naučili, saj smo razvijali digitalne kompetence, ki so nismo predstavljali, kaj nas je doletelo. Zadnji dan so prišli le sredstvo za vseživljenjsko izobraževanje. tisti, ki niso imeli varstva ali so želeli še zadnji dan videti sošolce. Tudi učitelji in drugi delavci šole nismo vedeli, kaj nas čaka. KLJUČNE BESEDE Naše življenje in delo se je zelo spremenilo. Znašli smo se doma Računalnik, pouk na daljavo, znanje, socialne interakcije, sami ali v krogu družine in za računalnikom. Kolikokrat smo digitalne kompetence ostali brez internetne povezave? Brez računalnika in interneta učitelji nismo mogli delati. Nihče ni pričakoval, da se bo šolsko ABSTRACT leto odvijalo brez šolskih klopi in učilnic. Začeli smo delati od In mid-March 2020, schools closed their doors, and nobody knew doma, na svojih računalnikih. Redki so tisti učitelji na naši šoli, how long they would have to stay closed. Everyone’s feelings ki so dobili službene računalnike. Kako težko je šele bilo were different, but the feeling of concern kept growing. What družinam doma z več otroki. Koliko je bilo takih, ki so imeli now? We were taken out of our comfort zone into the unknown. doma samo en računalnik. Kako so zmogli delo tisti starši, ki so The feeling of safety was replaced by the feeling of uncertainty. imeli enega ali dva otroka na 1. vzgojno izobraževalnem obdobju We were faced with the fact that classes would need to take on a in drugega ali tretjega otroka na 2. ali 3. obdobju. Koliko otrok very different format. We had to deal with a new way of working, je bilo takih, ki so mislili, da so to zanje počitnice? Koliko je bilo which caused problems for many. If any of us had had an takih, ki jim starši niso zmogli ali znali pomagati? Starši so aversion to using computers before, this aversion became even postali podaljšana roka učitelja. Prav gotovo je bilo lažje tistim more prominent now, since no one was aware of what this učencem, kjer so starši izobraženi in je socialna slika dobra. situation would entail; hours and hours of sitting in front of a Ker sem zaposlena kot knjižničarka, sem za nekaj ur hodila v službo in vnašala knjige v sistem Cobiss. Ko sem prišla domov, computer, and hours and hours of working on a computer. Our pa se je začelo še delo za slovenščino. Poučevala sem eno heterogeno skupino v 9. razredu. Po dveh tednih in več, ko sem se pogovarjala s sodelavkami, nisem mogla razumeti, zakaj si želijo nazaj v šolo. Seveda, sama hodila sem vsak dan v službo, Permission to make digital or hard copies of part or all of this work for personal or one ne. Imela sem samo eno skupino, sodelavke, ki so učile classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full slovenski jezik od 6. do 9. razreda in s tem po sto in več učencev. citation on the first page. Copyrights for third-party components of this work must Naši računalniki so pregorevali. Za devetošolce je bilo lažje, ko be honored. For all other uses, contact the owner/author(s). so se konec maja vrnili v šolo. Tudi učiteljice so prišle za eno Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). uro pouka v šolo in nato za ostale delale naprej od doma. 480 2 DELO NA SPLETU poskusim. Seveda smo se prej vedno dogovorile, kaj bo obravnavana snov in katera bo naložila za posamezni razred. Ker Naše delo se je preselilo na splet. Goethe je nekoč zapisal: » Le sem učila le 9. razred, sem se ob pomoči kolegice hitro naučila, dve poti vodita do pomembnega cilja in do izvajanja velikih kako naložiti snov oziroma mapo, v kateri so navodila, naloge stvari: moč in vztrajnost…« Postali smo močni in vztrajni, da za utrjevanje in rešitve. Po nekaj tednih slovnice smo želele smo lahko z nepopustljivo in strogo voljo peljali stvari naprej. razbiti monotono delo z delovnikom in začele razmišljati o Naša šola uporablja Arnesove storitve: Arnes pošto, Arnes splet, branju knjige za domače branje. Imele smo težavo, saj si učenci Arnes spletne učilnice. Naše delo na spletu ne bi mogli dobro niso pravi čas izposodili knjigo. Ta tehnični problem smo rešile opravljati brez naših računalničark, ki sta z nami delili, kar so tako, da sem knjigo optično prebrala. Druga kolegica je nam na Arnesu pripravili za lažje delo s spletnimi učilnicami. To pripravila navodila. Poslala mi je navodila in mi naročila, naj so uporabniški vodiči in video vodiči. Učiteljica računalništva je dodam še kakšno sliko. Tako sem prvič priložila tudi sliko. Tako pripravila podrobna navodila, kako učenci dostopajo do spletne smo na nov, izviren način pripravile domače branje. učilnice in kako oddajo nalogo v spletni učilnici. Tako so učenci prejemali gradivo v spletnih učilnicah, v stiku z učitelji pa so bili S pomočjo računalničarke sem pripravila tudi spletno preko elektronske pošte, telefona, eAsistenta, video konferenc. učilnico za knjižnico, ki je prej še nisem imela. Vanjo so lahko V pomoč pri delu na daljavo smo se obračali na sodelavce, učenci od 6. do 9. razreda nalagali svoje zapise o prebranih vodstvo šole in na računalničarki. Tako je tekla interakcija med knjigah za bralno značko. Veliko učencev je vsaj vstopilo vanjo učiteljem, učenci in tudi s starši. Viden problem, ki se je pojavil, in malo pogledalo, kako deluje. Pogumnejši so vanjo pridno so bile različne video konference. Učitelji, ki so jih uporabljali nalagali svoje zapise o prebranem. za stik z učenci, so uporabljali vsak svojo (Teams, CiscoWebex, Google Meets, … ), kar je lahko bilo za starše stresno. Na naši šoli smo se pred več kot desetimi leti 3 KOMUNIKACIJA Z UČENCI začeli ukvarjati s spletnimi učilnicami. Vsak predmet je izdelal Gospod ravnatelj nas je v soboto, 14. 3. 2020 prebudil z svojo spletno učilnico in vanjo naložil nekaj snovi za pouk. vzpodbudnim mailom, da v ponedeljek začenjamo z Učiteljice od 1. do 5. razreda so pripravile učilnice za svoj razred. izobraževanjem na daljavo. Med drugim je zapisal, da se na Za pouk slovenskega jezika se je s tem podrobneje ukvarjala takšno izobraževanje nismo pripravljali, ampak naj vseeno sodelavka, ki je ob pomoči druge sodelavke (ta je prišla začasno poskusimo biti fleksibilni, kreativni in da se bomo učili sproti. iz druge šole) uspešno naložila nekaj učnih snovi za pomoč pri To bomo učili tudi naše učence, kot na primer fleksibilnost, izvajanju pouka. Pripravili sta učilnice od 6. do 9. razreda. Ko odgovornost, kreativnost, kritično razmišljanje, sodelovanje in še nas je začasna sodelavka zapustila, je kolegica slavistka, že vse kaj. Prosil nas je, naj v začetku ne pretiravamo z nalogami. Prvi obvladala in nadaljevala z začetim delom. Tako smo lahko tudi teden naj bo namenjen spoznavanju z novim okoljem. Naj ostale slovenistke s pridom uporabile snovi, ki so bile naložene. normalno zadihajo tudi učenci. V prvem tednu nam je dal za Drugi dve slovenistki sta s spletnimi učilnicami bolj malo nalogo, naj preverimo, koliko učencev dostopa do učilnic, kje so ukvarjali. Sama se tudi nisem, saj sem zaposlena v knjižnici. težave pri tistih, ki se ne oglašajo in kako jim lahko pomagamo. Moje delo v tem času je potekalo vsak dan po nekaj ur v šoli, Svetoval nam je naj uporabljamo elektronsko pošto kot kjer sem vnašala knjige v sistem Cobiss. komunikacijsko orodje. Imajo jo vsi učenci od 4. razreda naprej. V času dela na daljavo smo bile vse štiri postavljene pred Pri ostalih naj učitelji uporabljajo eAsistent kot orodje za dejstvo, da bo treba drugače delati. S sodelavkami smo se komunikacijo s starši. Svetoval nam je, naj bo prvi teden tak poenotile in strinjale, da naložimo tedensko delo. Za prvi teden spoznavni teden, kjer se bomo tudi mi spoprijateljili z novim je kolegica – začetnica spletnih učilnic uporabila že naloženo načinom dela. snov Power Pointu – Ponovitev književnih obdobij za 9. razred. Tako so prvi dnevi potekali v iskanju kontaktov Ker ostale učijo še 6. ,7. in 8. razred, so morale tudi za njih z učenci in njihovi starši in vstopanju v spletne učilnice. Z pripraviti delo. Začelo se je brskanje, iskanje, izbiranje delom na daljavo smo začeli razvijati tudi digitalne kompetence, informacij ter hkrati shranjevanje in priklic informacij [2]. Vsak in sicer interakcijo prek tehnologij, izmenjavo informacij in razred so posebej nagovorile z vzpodbudnimi besedami. Vedele vsebin [2]. Tu sta bili v veliko pomoč naši računalničarki. Starši smo, da bodo učenci potrebovali prvi teden za vpis v spletne so pri mlajših učencih potrebovali tehnično pomoč. Tu smo se učilnice več časa in navodil. Seveda so hitri in vestni učenci to še enkrat srečali z varovanjem osebnih podatkov oziroma hitro osvojili in se redno prijavljali ter delali. Drugi, spet so si digitalno identiteto. Ne smemo pozabiti na razlike v vzeli nekaj časa in počasi prihajali vanje. In tretji so bili taki, ki izobrazbenih, kulturnih in drugih ozadjih učencev. Prav tako so so zelo poredkoma vstopali v učilnice in zelo malo delali. Tudi imeli razredniki dodatno obremenitev, kajti morali so vstopiti v za naslednji teden je kolegica naložila delo - reševanje NPZ-ja. kontakt s starši, katerih učenci se niso odzivali. Sodelavka je na Tu so se vsaj nekateri učenci lotili reševanja in preverili svoje zadnji konferenci v svojem poročilu izjavila dobro misel: » usvojeno znanje. V tretjem tednu smo se dogovorile, da začnemo Učitelj ne postaneš le zato, da učiš, ampak skozi učenje vzgajam tam, kjer se je končala snov v šoli, torej pri priredno zloženi še marsikaj drugega, vsega ostalega za življenje. « povedi [3]. To snov so učenci usvajali preko Rokusovega delovnega zvezka. Začele smo torej ustvarjati vsebine, ki so Kakšen je bil odziv učencev moje skupine? učencem olajšale delo. Dobili so natančna in jasna navodila, da Prvi teden sem jih pustila čisto na miru in samo opazovala so lahko razumeli posamezno snov pri jezikovnem pouku. njihove prijave v spletne učilnice. Že v prvih 14 dneh smo s Potem so po navodilih zapisali novo snov v zvezek, si pri tem strani računalničarke dobili tabelo v Onedrivu po razredih, za pomagali z delovnim zvezkom in nadaljevali z reševanjem vse predmete, v katero smo vnašali učenčeve odzive. Učenci so podobnih nalog. v navodilih dobili navodila, da svoje delo poslikajo in nam Tako smo postopoma začele nalagati novo snov. Pazile pošljejo na mail. Delovni in marljivi učenci so to storili včasih smo, da dela ni bilo preveč. Ker so kolegice učile več razredov, že prvi dan. Ostali pa v teku tedna. Nekaj je bilo takih, ki niso so se naučile prej nalagati snov kot jaz. Tudi mene je čakalo, da redno pošiljali svojega dela. Imela sem tudi primer učenca, ki je ostal neodziven. Odziven pa je bil pri zgodovini, ker ga je zelo 481 zanimala. Poseben je bil tudi učenec, ki tudi pri rednih urah ni veliko naredil. Svoje delo je znal strniti v dve povedi. Na začetku se nekaj tednov ni oglasil, potem pa je imel izgovor, da mi ne more poslikati svojega dela, ker mu na telefonu ne dela fotoaparat. Ker poznam njegovega dve leti starejšega brata, sem mu svetovala, naj poskusi z bratovim. Potem se nekaj tednov spet ni oglasil. Učenka Romkinja je prav tako ostala neodzivna. Ona ni znala niti uporabljati maila. Za pomoč sem prosila njeno sošolko, naj ji pomaga. Proti koncu ji je uspelo prijaviti se v spletno učilnico in mi napisati kratek mail, da nekaj dela. Ker je že prej imela učne težave, ji je to, da je ostala doma zelo odgovarjalo. Razredniki so spremljali odzivnost učencev in o neodzivnosti obveščali ali klicali starše. Ko se je začelo pošiljanje dela učencem na mail, se je začel drugi del našega dela. Ta del se je raztegnil čez cel dan in tudi v večerne ure in te prisilil, da si bil učencem ves čas na razpolago. Pregledati je bilo treba naloge, ki so jih rešili in jim poslati povratne informacije. Pri odgovarjanju na njihovo pošto sem vsakega vljudno ogovorila, zapisala nekaj spodbudnih povedi ali besed in dala informacije o njihovem delu. Učenci, ki niso redno oddajali nalog, so bili po navadi tisti, ki imajo tudi težave s Slika 2. Primer dela učenca komunikacijo. To sem opazila pri njihovih sporočilih, ki so bila kratka in jedrnata (slika 1). Na srečo niso poslali sporočil, kot si jih pišejo med seboj in so slovnično nepravilna. Pri učencih, ki so sproti oddajali, so bili takšni, ki so v množici podatkov znali izluščiti ključne informacije (slika 2), jih sintetizirati in uporabiti v novih pomenih. Opazila sem, da so taki bili vztrajni pri vseh predmetih in so si znali delo razporediti, da jim je delo lepo teklo (slika 3). Niso spali do 12.00, ampak so začeli z delom zjutraj, kot bi bili v šoli. Popoldne so lahko bili prosti. Učenci, ki si takšnega urnika niso zastavili in niso sproti oddajali nalog, se jim je delo nabiralo, tudi za več tednov. Takšni bi potrebovali nadzor staršev. Če je bilo v družini več otrok, so starši morali pomagati in delati z mlajšim in zato so od starejšega pričakovali, da zmore sam. Tako so morali prevzeti odgovornost za svoje znanje in se pri tem svobodno odločali. Vendar vsi tega ne znajo oziroma ne zmorejo. S tem, ko smo bili učencem ves čas na razpolago za odgovarjanje na njihove poslane naloge, se je naš delovnik zelo zelo raztegnil. Zavedamo se, da je bilo veliko individualnega pristopa – telefon, elektronska pošta, eAsistent, video konference. Ker vsega o učencih v tem času ne vemo, smo jim dajali spodbude, jih tolažili. Ne vemo ali imajo vsi varno okolje, so morda lačni? Veliko srčnosti, topline bi potrebovali takšni učenci. Slika 3. Primer dela učenca Tako se je tudi vso njihovo delo preselilo na računalnik. Koliko smo jih prej odvračali od tega, so sedaj bili primorani sedeti pri računalniku in delati vse predmete. Ne vem, če so po nekaj urnem sedenju še imeli voljo do njihovih računalniških igric. Predvidevam, da je bilo tega sedaj manj. Za tiste, ki niso imeli preveč nadzora svojih staršev, so verjetno izkoristili in namesto šolskega dela igrali igrice. Taki so tudi neredno ali zelo malo oddajali svoje delo. A učenci so pogrešali stik s sošolci, prijatelji, razlago snovi, debato, tudi učitelje, razredničarko. Primanjkljaj se je kazal v socialnih interakcijah (topli, iskreni medosebni odnosi so manjkali vsem). Vsi vemo, da je opremljenost z Slika 1. Primer dela učenca računalniki premalo. Potrebno je računalnik znati t udi upora bljati. 482 4 DAN DEJAVNOSTI PREKO SPLETA omogoča napredek, a je lahko tudi past. Sprašujem se ali bo računalnik postal učenčev obvezen pripomoček? Da smo vsaj malce razbili naporne delovne tedne, smo razmislili o dnevih dejavnosti. Stališče vodstva šole glede tega je bilo, da In kakšni so rezultati? Ker so to bili devetošolci, kjer je bilo je najbolj smiselno izvesti kulturni dan, zato nam je poslalo nekaj prej veliko ponavljanja snovi pred epidemijo, utrjevanja in delno idej in tem. Znotraj aktivov smo se pogovorili, izbrali tematiko, že nekaj priprav na NPZ-je, velikih vrzeli v znanju slovenskega pripravili dejavnosti. Kulturni dan smo izvedli 23. 4. 2020. Za jezika ne bo. Nova snov, ki so jo predelali na daljavo je bila vsako izobraževalno obdobje je bil določen vodja, ki si je izbral priredno zložena poved, ki ni preveč zahtevna. Prav tako ne gre ožji tim in skupaj pripravil navodila za učence in učitelje. Izbrali le za znanje in kritično razmišljanje, ampak tudi za oblikovanje so ustrezne vsebine, gradiva, vse to naložili v spletne učilnice, se mlade osebnosti kot celote. Znanje je res pomembno, a v dogovorili o načinu analize dneva in podajanja povratnih življenju so pomembne še druge sposobnosti, veščine, informacij učencev. Nabor vsebin za učence od 6. do 9. razreda interakcije. je zajemal: ogled filma (po lastni izbiri, slovenskega filma ali Pay it Forward) ali ogled predstav Lutkovnega gledališča Ljubljana Zaključila bi z pomembno mislijo sodelavke, da učitelj ni Vihar v glavi, Tajno društvo PGC) ali ogled virtualnih razstav, le podajalec učne snovi, je tudi vzgojitelj, svetovalec, mentor, učne ure, dokumentarnih filmov. Pri vsaki vsebini so bile opora v stiski in še marsikaj, in da je še kako pomembna gradnja navedeni tudi predlogi za dejavnosti, ki si jo izbere učenec sam. odnosov. A jeseni bo slika lahko spet drugačna. Zato se bomo Dejavnosti je lahko zapisal, posnel avdio ali video, izdelal PPT nanjo bolje pripravili z novimi spletnimi izobraževanji. predstavitev, narisal strip… Izbrano dejavnost so naložili v Dogovorili se bomo, da poenotimo video konference in da vsi spletno učilnico dan dejavnosti pod svoj razred do določenega uporabljamo isto. Slovenistke smo prišle do spoznanja, da bo datuma. Drugi njihove naloge je obsegal izpolnjevanje ankete treba razmisliti, kako bodo učenci še kaj prebrali. Vsi se kulturnega dne. Razredniki so v oddaji nalog za svoj razred zavedamo, da je pomen tehnologije v našem vsakdanjiku vse prebrali in pregledali njihovo delo, zapisali komentarje in ocenili večji in večji, zato tudi digitalne spretnosti postajajo z opravil ali ni opravil. Kot sorazrednik sem imela vpogled v vse bolj prisotne in pomembnejše. oddajo nalog 9. c, komentarje in ocene je opravila razredničarka. Tudi tu smo z reševanjem problema ustvarjalno rabili tehnologijo [2]. VIRI 5 ZAKLJUČEK [1] Medveš Z. 2020. Normatvna logika manesto pedagoškega razmisleka. Delo. DOI= To šolsko leto je bilo zelo naporno tako za učitelje na eni strani https://www.delo.si/sobotna-priloga/normativna- in učence ter njihove starše na drugi strani. Vsi učitelji se logika-namesto-pedagoskega-razmisleka- zavedamo, da smo delali veliko več kot kdajkoli. Obremenitve 296463.html so bile tako velike, da so si učitelji želeli nazaj v učilnice. Čeprav [2] Ala-Mutka K. 2011. Mapping Digital Competence: smo trdo delali, vemo, da to obdobje lahko z visoko oceno Towards a Conceptual Understanding. Expo. c/ Inca ovrednotimo le po svojem vloženem trudu, trudu staršev in otrok, Garcilaso Spain. verjetno pa ne tudi po usvojenem znanju učencev. Zavedamo se, DOI=ftp://jrc.es/pub/EURdoc/JRC67075_TN.pdf da vrzeli v znanju bodo. Na mestu je izjava dr. Zdenka Medveša, [3] Različni avtorji. 2018. Učni načrti za osnovno šolo. da izobraževanje na daljavo ne more doseči tempa, širine in Ministrstvo za izobraževanje, znanost in šport, Zavod globine rednega izobraževanja [1]. RS za šolstvo. Psihoterapevt Miha Kramli, ki je strokovnjak za DOI=http://www.mizs.gov.si/si/delovna_podrocja/dir kemične in nekemične odvisnosti, predvsem za odvisnosti od ektorat_za_predsolsko_vzgojo_in_osnovno_solstvo/o novih tehnologij, poudarja, da je internet koristna stvar, ki snovno_solstvo/ucni_nacrti/ 483 Poustvarjanje Povodnega moža z animacijo The re-creation of The Water Man (Povodni mož) with animation Barbara Gabrijelčič Osnovna šola Solkan Šolska ulica 25 5250 Solkan, Slovenija barbarag@sola-solkan.si POVZETEK Danes živimo v dobi, kjer se dnevno srečujemo z animacijo, saj 2 ANIMIRANI FILM PRI POUKU je ta narejena tako, da privabi. Njena vabljivost je lahko odlično sredstvo za izobraževanje. V prispevku predstavljam, kako smo Že od nekdaj me je svet animiranega filma privlačil. se je lotili v tretjem razredu na temo Prešernovega Povodnega Pri pouku sem sprva uporabljala animirani film le kot moža. Zgodba je posneta v stop motion tehniki, postopku, pri motivacijsko sredstvo. Z razvojem, dostopnostjo ter s pravim katerem se s serijo fotografij posname film. Scena in liki so izborom kvalitetnega materiala pa vedno pogosteje tudi v učne izdelani iz kock Lego, kar še dodatno spodbudi mlajše otroke za namene. ogled posnetega filma. Uporabna je kot didaktični material v šoli. Na področje ustvarjanja animiranih filmov se nisem nikoli spustila, saj nisem imela dovolj potrebnega znanja, zato sem se KLJUČNE BESEDE vključila v delavnico ustvarjanja animiranega filma v okviru Art kino mreže Slovenije. V njenem sklopu sem dobila osnovna Animirani film, stop motion, lego animacija, balada Povodni znanja o ustvarjanju animiranega filma. Pridobljeno zanje o mož tovrstni tematiki sem poglobila s prebiranjem priročnikov in ABSTRACT literature. To mi je dalo zagon, da poskusim predstaviti animirani film učencem tudi z vidika lastnega ustvarjanja. We live in an age where we encounter animation on a daily basis due to its wide appeal. This also makes it an excellent means for education. This article presents the use of animation in the third 3 NASTAJANJE ANIMIRANEGA FILMA grade of primary school. The theme that is presented is France Prešeren’s poem The Water Man (Povodni mož). The story was 3. 1 Idejna zasnova in izbor tehnike filmed in the stop motion technique, a procedure in which a film Na začetku so bili učenci seznanjeni z osnovami animiranega is recorded with the aid of a series of photographs. The scene and filma. Učenci so že poznali slikofrc ali listanko. Pogledali smo the characters are built from Lego bricks, which further se nekaj kvalitetnih kratkih animiranih filmov z različnimi motivates young children to watch the movie that was recorded. tehnikami. Z razgovorom in ogledovanjem gradiva o različnih The story is wholly useful as didactic material in school. vrstah animacije sem želela vzpodbuditi in usmerjati učence na poti kakovostnega sprejemanja filmske umetnosti, da o njej KEYWORDS razmišljajo in so tudi sami ustvarjalni. Animated film, stop motion, Lego animation, ballad The Water Učenci so se navdušili in se želeli z mojo pomočjo preizkusiti v Man (Povodni mož) animiranju. Najprej je bilo treba določiti zgodbo, ki bi jo animirali. Po razgovoru z učenci je bila izbrana zgodba o prevzetni Urški iz 1 UVOD Prešernove balade Povodni mož. Tej odločitvi je botrovalo več Z animiranimi filmi se v današnjem času otroci srečajo že zelo dejavnikov. Prvi je bil prihajajoči kulturni praznik, 8. februar, in zgodaj. Njihov svet jim pogosto predstavlja del preživljanja priprava proslave. Menili smo, da bi jo lahko popestrili s prostega časa. Naloga nas odraslih je, da jih v ta svet navideznega poustvarjanjem Povodnega moža v obliki animacije. Za to oživljanja lutk, predmetov ali risanih figur vpeljemo čimbolj besedilo so se učenci poenotili, ker so ga že natančno poznali iz načrtno in premišljeno. 2. razreda. Najprej sem z učenci obnovila vsebine v okviru pouka slovenščine in pesnitev spremenila v prozno besedilo. To je potekalo frontalno z razgovorom. Naslednji korak je bila delitev zgodbe po delčkih. Ob listanju Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed slikanice smo zgodbo povzemali po delih. Nastajali so prizori, ki for profit or commercial advantage and that copies bear this notice and the full so kasneje služili pri animaciji. Pri tem smo zapisovali besedilo, citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). kaj se v posameznem prizoru dogaja. Zgodbo smo razdelili na Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia štirinajst kratkih delov. © 2020 Copyright held by the owner/author(s). 484 Učenci so se dogovorili, kdo bo bral posamezen del. tudi nevaren, saj bi se lahko kdo od animatorjev pri dotiku spekel. Sledil je izbor tehnike. Na srečo takšnih incidentov ni bilo. Ker sem se z ustvarjanjem animacije srečala prvič, nisem Zajem fotografij smo opravili s prenosnim računalnikom. vedela, katero tehniko bi izbrali. Ob iskanju različnih posnetkov Pomembna lastnost, ki je pogojevala izbiro tega prenosnika je s spleta so mi učenci pokazali svoje priljubljene videoposnetke. bila vgrajena kamera. Ta je omogočala fotografiranje spredaj in Ogromno jih je bilo narejenih v Lego stop motion animaciji. Ta zadaj. Prenosnik je bilo lažje pritrditi kot tablični računalnik ali sodi v kategorijo tako imenovanih »brickfilmov«. telefon. Pri tem so plastični gradniki ali kocke lego sredstvo za izdelavo likov in scene. Od tu dalje izbira tehnike ni bila več pod vprašajem. Prednost kock Lego, kot osnovnega pripomočka za izdelavo posameznih situacij, je bila logična izbira zaradi njihove dostopnosti. Otroci so jih imeli doma ogromno, pa tudi v moji domači hiši se jih je našlo kar nekaj primernih za izdelavo likov in postavitev scene. 3.2 Postavitev scene Postavitev scene je zahtevala veliko organizacijskega dela. Učenci so bili precej neučakani, saj so vsi želeli pri tem sodelovati. Tako smo si za ustvarjanje vzeli več časa, kot sem ga sprva načrtovala. Učenci so ustvarili več možnih prizorišč, nato pa smo združili posamezne izvirne ideje. Vendar so bile omejitve s številom kock in velikostjo snemalnega prostora, zato smo sceno zelo poenostavili, saj ni bila bistvena za razumevanje Slika 1. Priprava prostora za snemanje. dogajanja. (Vir: B. Gabrijelčič) Kasneje smo ugotovili, da je zelo pomembno, da je scena stabilna in da se sredi snemanja ne premika. V določenih delih 3.5 Animiranje s pomočjo računalnika pozornemu opazovalcu ne uide premikanje objektov, ki bi morali Animirali smo v tehniki stop animacije, snemanje sličice za biti pri miru iz kadra v kader. sličico. Snemali smo do 15 sličic na sekundo. (slika 2) Gib, za Postaviti smo jo morali tako, da smo lahko snemali s katerega smo želeli, da ga naš lik naredi v filmu, smo razdelili v fotoaparatom. več majhnih premikov. Vsak takšen premik smo fotografirali. Ozadje trga, kjer se je odvijala osrednja zgodba, smo prelepili Figure smo premikali počasi, sliko za sliko in sproti preverjali z nevtralnim modrim papirjem. Dogajanje se vrti le na enem njihovo postavitev v dogajanju. Nekatere prizore smo morali prizorišču, kar je izvedbo olajšalo. zaradi napak večkrat ponoviti in ponovno posneti. Zaradi 3.3 Priprava likov omejitev s časom in neizkušenostjo smo nekatere prizore iz scenarija sproti dopolnili in poenostavili. Z učenci smo poiskali med lego figurami take, ki so ustrezale glavnim in stranskim osebam zgodbe. Na srečo so v industriji pred nedavnim izšle lego kocke takšne serije, ki smo jih lahko uporabili. Vendar pa so karakteristike figur lego omejene z izražanjem čustev in na to je bilo treba biti pozoren pri snemanju. Objekti nudijo nekoliko okornejše animiranje, saj se je potrebno prilagajati njihov konstrukciji. Izbira likov je pogojevala tudi izbiro raznih dodatkov za figure, ki bi dodatno prikazovala avtentičnost zgodbe, seveda pa je bil nabor omejen. 3.4 Prostor za zajem slike in oprema Priprava prostora za snemanje: sestavila sem preprosto mizo za animacijo in jo osvetlila. (slika 1) Vso tehnično opremo sem dobro pritrdila, da bi se svetloba čim manj spreminjala. Uporabila sem dva reflektorja in osebni računalnik. Slika 2. Zajem fotografij. (Vir: B. Gabrijelčič) Zajem fotografij je potrebno opraviti v čim krajšem možnem času, da bi se svetloba čim manj spreminjala. Popolne zatemnitve Učence sem razdelila v manjše skupine, da so animirali v razredu namreč ni mogoče doseči. Iskanje pravih reflektorjev Premike likov smo določili na podlagi zgodbe. Pri animiranju za osvetljevanje scenskega prostora mi je predstavljal enega sem učence spodbujala k ustvarjalnosti, iskanju rešitev in sledila večjih problemov in popolne rešitve kljub popravkom do konca njihovim idejam pri prikazu dogodkov. Pri tem je bila potrebna nisem našla. V drugem delu sem pri zajemu dodala močan uskladitev in dobro timsko delo udeležencev. Pri snemanju so si reflektor, ki je sicer svetlobo prostora izboljšal, hkrati pa je bil učenci v skupini, ki je bila na vrsti, razdelili vloge. Dva v skupini 485 sta animirala in skrbela za opremo, tretji je opravljal zajem slike preko prenosnega računalnika. Sama sem skrbela za koordinacijo. Vsak del so se skupine menjale, ker se vsi učenci želeli priti na vrsto. Učenci so spoznali, da je samo snemanje zamudno in lahko zahteva veliko časa. Ob zaključku snemanja smo bili že vsi pošteno izmučeni. Učence sem vključila še v izbiro glasbe, v izdelavo uvodnega dela ter vmesnega dela z nevihto. S posamezniki je bilo potrebno posneti pripovedni del. To smo storili kar preko diktafona na prenosnem računalniku. Uporabili smo slušalke z mikrofonom, da je bil zvok čistejši. To smo opravili v naslednjih dneh. Uvodni del in del z nevihto je posnet s telefonom in z drugačne perspektive. (slika 3) Slika 4. Predvajanje animiranega filma. (Vir: B. Pritrjen je bil med dvema reflektorjema s tlorisnim pogledom. Gabrijelčič) Slike so zajete postopoma, z dodajanjem kock. Ob neprekinjenem predvajanju zaporedja fotografij se je ustvarila iluzija gibanja. 5 ZAKLJUČEK Učenci so se z ustvarjanjem lastnega animiranega filma zelo zabavali, hkrati pa so bili tudi presenečeni nad tem, koliko časa vzame snemanje posameznih prizorov. Sam projekt je bil tudi zame velik izziv, saj pred tem še nisem opravila celotnega postopka od začetnega načrtovanja do končnega produkta filma. Potrebnega je bilo veliko sprotnega reševanja situacij in iznajdljivosti – pomanjkanje opreme, omejeno tehnično znanje povprečne uporabnice IKT opreme. Ob snemanju sem dobila največ znanja prav s prakso. Končni izdelek še zdaleč ni vrhunsko delo, je pa odličen izdelek za učence na tej starostni stopnji. Nekatere prizore bi lahko ob izboljšani svetlobi ali premiku Slika 3. Nastajanje uvodnega dela. (Vir: B. Gabrijelčič) scene posneli ponovno, vendar zaradi napornosti snemanja in pomanjkanju časa tega nisem želela narediti. 3.6 Montaža Sicer pa cilj ni bil izdelati popoln animirani film, temveč Ustvarjanje animacije, ki ga je bilo treba zaključiti z obdelavo in doživeti izkušnjo lastne animacije, ki je bila močna in nepozabna. dodajanjem zvoka, sem opravila sama. Zajete sličice sem izvozila iz programa Stop motion Studio. Pri izbiri programa za VIRI IN LITERATURA montažo sem se odločila za program Animotica. To je enostaven, brezplačen program. Z majhnim doplačilom sem pridobila [1] Animirajmo! Priročnik za animirani film v vrtcih in šolah, dodatne možnosti in izbris njihovega logotipa na končnem Ljubljana, Zavod RS za šolstvo, 2016: Dostopno na naslovu: izdelku. www.zrss.si/digitalnaknjiznica/animirajmo/ (pridobljeno Pri združevanju zajetih sličic in posameznega prebranega 14. 8. 2020) odseka sem morala slediti času trajanja prebranega. Če je bil prebrani del daljši in je sličic primanjkovalo, sem jih podvojila. [2] Učni načrt, Slovenščina. Ljubljana: Ministrstvo za šolstvo in šport, Zavod Republike Slovenije za šolstvo: Dostopno Paziti je bilo treba na popolno ujemanje prebranega in animacije. na Uvodna špica je trajala 14, vmesni del z nevihto pa 7 sekund. naslovu:http://www.mizs.gov.si/fileadmin/mizs.gov.si/pag Končni izdelek je tako dolg 2 minuti in 21 sekund. euploads/podrocje/os/prenovljeni_UN/UN_slovenscina_O S.pdf (pridobljeno 14. 8. 2020) ( 2011) 4 OGLED FILMA OB KULTURNEM [3] Stop motion studio. Dostop: https://www.cateater.com/. PRAZNIKU (14. 8. 2020). [4] Izdelava stop motion animacije; Zgodba Veronike Animirani film je bil prikazan kot del proslave ob kulturnem Deseniške in Friderika II: Dostopno na naslovu: prazniku za učence prve triade. (slika 4) Odziv je bil pozitiven. https://www.knjiznica- Tako učitelji kot učenci so pohvalili animacijo, predvsem pa to, celje.si/raziskovalne/4201903217.pdf (pridobljeno 14. 8. da so ga delali mlajši učenci. Učencem je bila všeč predvsem 2020) animacija iz lego gradnikov in figuric. Učitelji so opazili [5] Animirani film v izobraževanju, Društvo za razvoj filmske podrobnosti, npr. pomežik Prešerna v uvodnem delu, plapolanje kulture, 2012: dostopno na naslovu: ogrinjala pri Povodnem možu in skok ribe v reko v zaključku. http://www.solafilma.si/sl/objava/animirani-film-v- izobrazevanju (pridobljeno 14. 8. 2020) 486 [6] Povodni mož v animaciji. Dostopno na naslovu: https:/ youtu.be/44zybX8gTaI (pridobljeno 14. 8. 2020) 487 Z IKT in dnevom dejavnosti do animiranega filma With ICT and activity day to animated film Vesna Gulin Osnovna šola Solkan Šolska ulica 25 5250 Solkan, Slovenija vesnag@sola-solkan.si POVZETEK V šoli nam kronično primankuje časa za dejavnosti, kjer so 1 UVOD učenci bolj aktivni, motivirani in kjer izkazujejo svojo kreativnost. Nekoliko več časa imamo, ko organiziramo dneve Učenci si skozi osnovnošolsko izobrazbo pridobivajo temeljna dejavnosti. Namen prispevka je prikazati primer dneva znanja, spretnosti in izkušnje na najrazličnejših področjih. dejavnosti v 2. razredu (kulturnega dneva - pustovanje) z Učitelj je v tem obdoblju zelo pomemben. Učencem mora uporabo IKT tehnologije in učencem pripraviti zanimivejši in vsebine približati, jih zanje motivirati, pouk pa organizirati tako, bolj ustvarjalen pouk. da so učenci čimbolj aktivni. Skozi pestro, zanimivo izkušnjo si Delo z IKT tehnologijo in ustvarjanje animiranega filma se je učenci snov lažje zapomnijo. Take oblike dela zahtevajo od izkazalo kot zanimiva popestritev klasičnega pouka. Vloga učitelja veliko priprav, zato se pri tradicionalnem pouku aktivnih učitelja je bila spremenjena, saj je deloval kot svetovalec in dejavnosti manj poslužujejo. Tudi uporaba IKT tehnologije v usmerjevalec. Učenci so bili aktivni, za delo motivirani, uporaba prevem in drugem razredu je za učitelja izziv. Učenci se sicer s IKT pa je pripomogla k bolj dinamičnemu učenju in k sodobno tehnologijo srečujejo, a so pri uporabljanju manj trajnejšemu ter kvalitetnejšemu znanju. samostojni. Pri uporabi IKT tehnologije v šoli potrebujejo učitelja, da jih usmerja, jim pomaga. Ker je učencev veliko, KLJUČNE BESEDE učitelj pa en sam, morajo biti učenci potrpežljivi, učitelj pa Osnovna šola, dnevi dejavnosti, kulturni dan, pustovanje, potrebuje več časa, da pomaga vsem, ki potrebujejo pomoč. animirani film, IKT Pri dnevih dejavnostih imamo več časa. Prav zaradi tega razloga sem se odločila, da bom v kulturni dan vključila uporabo ABSTRACT IKT tehnologije. Poleg tega pa je pri dnevih dejavnosti več At school, we chronically lack time for activities during which izkustvenega učenja, učenci so bolj motivirani in aktivni. students are more active, motivated and where they show their creativity. We have somewhat more time when we organize activity days. The purpose of this paper is to show an example of 2 DNEVI DEJAVNOSTI V OSNOVNI ŠOLI an activity day in the 2nd grade (cultural day - carnival) using Dnevi dejavnosti so del obveznega programa osnovne šole, ki ICT technology and to prepare more interesting and creative medpredmetno povezujejo discipline in predmetna področja, lessons for students. vključena v predmetnik osnovne šole. Potekajo v skladu z letnem delovnem načrtu šole, ki določa njihovo vsebino in Working with ICT technology and creating an animated film was organizacijsko izvedbo (Ministerstvo za šolstvo in špor, 2011). proved to be an interesting enrichment of classical lessons. The Dnevi dejavnosti spodbujajo učenčevo ustvarjalnost, role of the teacher was changed because he only acted as a radovednost, samoiniciativnost ter jih usmerjajo v samostojno counsellor and a facilitator. Students were active, motivated for reševanje problemov tako, da jih usposabljajo za samostojno work, and the use of ICT contributed to more dynamic learning, opazovanje in pridobivanje izkušenj ter znanja (prav tam). longer lasting and better knowledge. Učenci ob teh dejavnostih znanje različnih področij med seboj povezujejo v celoto. KEYWORDS Med dneve dejavnosti spadajo : Elementary school, activity days, cultural day, carnival, • kulturni dnevi, animated film, ICT • naravoslovni dnevi, • tehniški dnevi, • športni dnevi. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed V šolskem letu je 15 dni dejavnosti. Posamezni dan dejavnosti se for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must izvede v obsegu 5 pedagoških ur. Deleži posameznih sklopov be honored. For all other uses, contact the owner/author(s). dejavnosti se spreminja na podlagi upoštevanja razvoja otrok ter Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia zastopanosti predmetnega področja v predmetniku osnovne šole. © 2020 Copyright held by the owner/author(s). 488 V 1. in 2. razredu imamo 3 naravoslovne dneve, 3 tehniške dneve, in sicer z glasbo, matematiko, slovenščino, športom, 5 športnih dnevov in 4 kulturne dneve. spoznavanjem okolja. . S filmom učenci pridobijo marsikatero znanje na bolj 2.1 CILJI DNI DEJAVNOSTI dinamičen, zanimiv in s tem bolj obstojen način, učenci pa se ob Clji dni dejavnosti so predvsem omogočiti učencem: tem zabavajo in sprostijo. Filmska vzgoja je pomembna za • utrjevanje in povezovanje znanja, pridobljenega pri izobrazbo mladih v teh časih, ko prevladujejo vizualne posameznih predmetih in predmetnih področjih, informacije. [1] • uporabljanje tega znanja, • nadgrajevanje znanja s praktičnim učenjem v 4 Z IKT IN DNEVOM DEJAVNOSTI DO kontekstu medsebojnega sodelovanja in odzivanja na aktualne dogodke v ožjem in širšem družbenem okolju. ANIMIRANEGA FILMA Cilji naravoslovnih dni Tako IKT kot dnevi dejavnosti kot animirani film zahtevajo od Pri naravoslovnih dneh prevladujejo aktivnosti z učitelja več priprave, časa za dejavnot ter dobro organizacijo pri naravoslovnega področja, tako da učenci dopolnjujejo in samem procesu dela. Pri organizaciji kulturnega dne z naslovom poglabljajo že pridobljeno znanje iz rednega pouka in ga Pustovanje se mi je zdela idealna priložnost, da povežem vsa tri povezujejo v nove kombinacije. Medtem razvijajo svoje kritično področja. mišljejenje in spoznavajo metode in tehnike raziskovalnega dela (ternsko delo, laboratorijsko itd.). Poudarek je tudi na doživljanju 4.1 PRIPRAVA KULTURNEGA DNE – narave, spoznavanju sestavin okolja, razumevanju sobivanja PUSTOVANJE človeka in narave ter zavedanje pomena varovanja okolja. [2] Dnevi dejavnosti so del obveznega programa osnovne šole. Cilji tehniški dni Potekajo po letnem delovnem načrtu (LDN), ki določa njihov Ob tehniških dnevih učenci izdelujejo različne izdelke in ob vsebino in organizacijsko izvedbo. V aktivih jih načrtujemo že tem razvijajo še mnoge druge spretnosti in sposobnosti. Iščejo na začetku šolskega leta. Organizacija teh dni tehniške probleme v svojem okolju in oblikujejo rešitve. Razvija zahteva dogovarjanje in usklajevanje tudi z morebitnimi se pozitiven odnos do tehniških dosežkov, ob oblikovanju zunanjimi izvajalci, organizacijo prevoza, določitev ustreznega razstav pa učenci izmenjujejo ideje in skušajo ob uporabi normativnega števila spremljevalcev, pripravo varnostnega informacijske tehnologije izboljšati obstoječe tehniške rešitve. načrta, pripravo dejavnosti, potek dneva. . [2] Učenci se pustovanja zelo veselijo. V šolo pridejo oblečeni v Cilji športnih dni pustno masko in se v njihovo masko vživijo. Na naši šoli damo Športni dnevi zadovoljujejo potrebe in interese po gibanju, povdarek na ta slovenski običaj, zato načrtujemo pustovanje kot ustvarjalnosti, sprostitvi in razvedrilu. Ob tem se krepi dan dejavnosti - kulturni dan. V šolskem letu 2018/19 smo se medsebojno sodelovanje, razvija se spoštovanje do tujih in učiteljice v aktivu 2. razreda odločile, da bomo v sklopu lastnih dosežkov, učvrstijo pa se tudi športne navade, kar je za kulturnega dne ustvarili animirani film, saj sam proces razvoj človega zelo pomembno. Prav tako se seznanijo z ustvarjanja vzame veliko časa in si ga pri klasičnem pouku ne različnimi športnimi dejavnostmi in z oblikami športa v protem vzamemo. času. [2] Cilji kulturnih dni 4.2 PRIPRAVA ANIMIRANEGA FILMA IN Kulturni dnevi se povezujejo s kulturnimi dogodki in DELA Z IKT vsebinami s kulturnega področja, pa tudi vrednote človeške družbe. Učenci se ob izvajanju kulturnih dni izražajo, so aktivni, Pred samo izvedbo kulturnega dne sem morala razmisliti, s dejavnost načrtujejo in jo sprejemajo. Ob tem razvijajo lastno kakšno tehniko animiranega filma bomo ustvarjali. Ker bodo ustvarjalnost in sposobnost dojemanja na področju družbenih učenci oblečeni v pustne maske, sem se odločila, da bomo ved in jezikoslovja, razvijajo lastno doživljanje umetniške uporabili tehniko stop animacija - ''piksilacija''. besede, barve, oblike, zvoka ali giba. [2] 4.2.1 STOP ANIMACIJA ANIMACIJA ZAUSTAVLJENIH GIBOV – »STOP MOTION« ANIMACIJA 3 ANIMIRANI FILM Stop animacija je tehnika animacije, ki prikazuje nežive Otroci se z animiranimi filmi srečujejo že zelo zgodaj in predmete v gibanju. Ob neprekinjenem predvajanju zaporedja vsepovsod, tako v domačem kot v šolskem okolju. Zaradi fotografij, se ustvari iluzija gibanja. Predmete za vsak posnetek celostne čutne, čustvene in miselne podobe ter predvsem zaradi posebej previdno premikamo v želene položaje, ki jih, privlačnosti animiranega filma za otroke je lahko domiseln in predvajane v zaporedju, vidimo kot gibajoče. Pomembno je, da učinkovit učni pripomoček. Filmska vzgoja je vključena tudi v si pri montaži slike sledijo v pravilnem sosledju. To gibanje v učni načrt. Je močno motivacijsko sredstvo, s katerim dosežemo realnosti ne obstaja zares in ga dojemamo kot popolno fikcijo. veliko učnih ciljev iz učnega načrta za različne predmete. Proces nastajanja stop motion animacije je počasen in zahteva Animacija je tisto področje, ki pokriva in povezuje vsa ogromno mero potrpežljivosti in energije. likovna področja, opredeljena v učnem načrtu za likovno vzgojo Poznamo več tipov stop animacij. Običajno jih delimo glede v osnovni šoli: risbo, slikarstvo, grafiko, kiparstvo, prostorsko na material iz katerega so izdelani liki in scena. Ti predmeti so oblikovanje. Širok je tudi razpon medpredmetnega povezovanja, lahko izdelani iz gline, plastelina, lesa, žice, tkanine itd. Velikokrat so liki lutke ali marionete, gre za takoimenovano 489 lutkovno animacijo. Tehnika z glino in plastelinom se imenuje Med snemanjem je bilo na sceni manjša skupina ' clay animation'', stop motion iz lego kock ''brickfilm''. Kadar pa učencev. Ostali učenci so dobili zaposlitve, ki so jih zmogli sami gre za posnetke živih objektov-ljudi in animiranje neživih; torej opraviti. Učenci so pokazali zanimanje za fotografiranje in so da za vsak majhen premik posnemamo fotografijo in potem v lahko tudi sami posneli fotografije. (Slika 2, 3 in 4) videu dobimo učinek nadrealističnega gibanja, imenjujemo ' 5. šolska ura: Pustni sprevod po kraju. pixilation ' . [3] 4.2.2 PRIPRAVA NA USTVARJANJE ANIMIRANEGA FILMA PRIPRAVA SCENARIJA IN SCENE Pred nastajanjem animiranega filma je potrebno razmišljati tudi o korakih izdelave. Izbrati moramo zgodbo. Odločila sem se, da si bodo zgodbo – scenarij učenci sami izmilsli že nekaj dni pred kulturnim dnem, saj je bilo treba razmisliti o sceni, ki se jo običajno izdela ročno in je potrebno pripraviti materiale ter orodja. Sceno so učenci pripravili pri likovni umetnosti. PRIPRAVA SNEMANJA Slika 1. »Scena«. Foto: V. Gulin, 2019. Za snemanje potrebujemo dovolj velik prostor, zato je bila učilnica primerna, le nekoliko jo je bilo preurediti. Razmisiti je bilo treba tudi o osvetlitvi, saj snemanje potrebuje tudi primerno luč, katere svetloba bo ves čas enaka, da se tekom filma ne spreminja. Seveda je bilo potrebno razmišljati o potrebni IKT tehnologiji, ki smo jo potrebovali za snemanje in montažo animiranega filma. Za snemanje smo imeli digitalni fotoaparat. Del nujne opreme je bil tudi stativ, saj se med snemanjem kamera ni smela premikati. Učenci stari 7 let še nimajo veliko izkušenj s tako obliko dela. Učitelj se mora pred dajsvnostjo dobro organizacijsko pripraviti. Predvidevala sem, da bodo učenci imeli nekaj težav s premiki in Slika 2. »Snemanje«. Foto: V. Gulin, 2019. bom sama morala biti usmerjevalec pri premikih živih objektov - učencev, zato sem za pomoč pri snemanju prosila dijakinjo likovne gimnazije. PRIPRAVA MONTAŽE Slikovne posnetke in zvok v določeno zaporedje poveže montaža. Montaža je ustvarjalni, tehnični in miselni proces, ki film poveže v celoto. Sama montaža bi zahtevala večjo organizacijsko težavo, zato sem za pomoč prosila dijaka računalniške srednje šole. Za montažo animacijskega filma je potreboval računalnik, posnetke - fotografije in program Movie maker. 4.3 IZVEDBA KULTURNEGA DNE Slika 3. »Snemanje«. Foto: V. Gulin, 2019. Posamezni dan dejavnosti se izvede v obsegu 5 pedagoških ur, zato je tudi kulturni dan trajal 5 šolskih ur. Potek dneva dejavnosti: 1. šolska ura: Predstavitev pustnih mask in pogovor. Učenci so se ob prihodu v šolo najprej predstavili kot pustne maske. Nato smo se pogovorili o nastajanju animiranega filma in poteku kulturnega dne. Sledil je še pogovor o zgodbi animiranega filma. 2. šolska ura: Priprava scene. Učenci so pripravli sceno, ki so jo imeli že izdelano. Rekvizite so usmerili v učilnico. (Slika 1) Sledila je malica. 3. in 4. šolska ura: Snemanje. Slika 4. »Snemanje«. Foto: V. Gulin, 2019. 490 4.4 MONTAŽA ta sredstva potrebujejo, potem bodo IKT, film lahko odlično učno Posnete fotografije smo prenesli na računalnik, na katerem se je sredstvo, da bo pouk bolj dinamičen in zanimiv. delala montaža. S programom Movie maker smo sličice združili v video zapis, dodali smo zvočni zapis – glasbo, uvodno in VIRI IN LITERATURA zaključno špico. [1] Goetz, dr. M. Krajnc, S. Krušič, T. Leder, mag. M. Peštaj, I. Prassel, mag. H. Repše, K. Saksida, M. Šturm: Animirajmo! 5 ZAKLJUČEK PRIROČNIK ZA ANIMIRANI FILM V VRTCIH IN Sodobno učenje zahteva uporabo informacijsko-komunikacijske ŠOLAH. Ljubljana: Zavod RS za šolstvo, 2016. tehnologije (IKT) v vseh fazah vzgojno-izobraževalnega [2] Učni načrt, Ljubljana: Ministrstvo za šolstvo in šport, Zavod procesa, tudi pri najmljaših učencih. Eden izmed pomembnih Republike Slovenije za šolstvo, 2011. DOI= razlogov za uvajanje IKT v pouk, je zagotovo ta, da smo del http://www.mizs.gov.si/si/delovna_podrocja/direktorat_za_ informacijske družbe, otroci pa so sve bolj izpostavljeni IKT predsolsko_vzgojo_in_osnovno_solstvo/osnovno_solstvo/u vplivom. Glavni namen uporabe IKT pri pouku je motiviranje cni_nacrti/ (pridobljeno 15. 8. 2020) učencev za učenje in delo pri pouku. [3] L. Penov. Animacija zaustavljenih gibov – “stop motion” Koliko bodo IKT, film in podobna učna sredstva prisotni v animacija. Pedagoška fakulteta, ma-te, 4. letnik, 2015/2016. šoli je v veliki meri odvisno od učitelja. Če bo imel učtelj željo, Dostop: https://sites.google.com/site/tp4fotografija/e- voljo, domišljijo, da se loteva novosti, da bo dobil »čas«, ki jih skripta/animacija-zaustavljenih-gibov-stop-motion- animacija (14. 8. 2020) 491 Mednarodni tabori računalništva in komunikacije za slepe in slabovidne (ICC) International camps on computers and communication for visually impaired (ICC) Grega Hribar Center IRIS Langusova 8 1000 Ljubljana, Slovenija grega.hribar@center-iris.si POVZETEK ladostnikov najnovejši IK tehnologiji. Kot eksperimentiranje predpostavimo udeležbo na taboru – metoda dela je torej Tabori računalništva in komunikacije za slepe in slabovidne opazovanje z udeležbo. (ICC), ki jih po celi Evropi organizira Univerza v Linzu skupaj z Po 100 letih šolanja slepih in slabovidnih v Sloveniji [2], le- lokalnim organizatorjem, so zelo dobra mešanica učenja, ti vsekakor niso več tako zapostavljeni kot v preteklih stoletjih, druženja in zabave. Tekom let me je zanimalo, kako udeležba vseeno pa jih na njihovi življenjski poti čaka še kar nekaj ovir. vpliva na naše slepe in slabovidne mladostnike ter zakaj tabori Mogoče sta dve izmed ključnih – družabno življenje in sledenje tako dobro delujejo že 25 let. hitro napredujoči tehnologiji. KLJUČNE BESEDE Vsako poletje v drugi evropski državi že 25 let potekajo desetdnevni mednarodni tabori računalništva in komunikacije Dostopnost/podporna tehnologija, slepi in slabovidni, (ICC camps), ki se trudijo, da mladim ravno na teh dveh socializacija, mednarodni tabori področjih ponudijo čim več. Tabori so domiseln kolaž ABSTRACT počitnikovanja, računalniških in socialnih delavnic, prostočasnih aktivnosti in druženja. The international camps on communication and computers for the blind and partially sighted (ICC), organized all over Europe by the University of Linz together with a local organizer, are a 2 DOSTOPNOST ZA SLEPE IN very good mix of learning, socializing and having fun. SLABOVIDNE IN ICC TABORI Over the years, I have been interested in how participation affects Louis Braille je pisavo za slepe izumil v 20. letih 19. stol. in s our visually impaired adolescents and why camps have been tem omogočil integracijo slepih otrok v šolski sistem. V 20. stol. doing so well for the last 25 years. so bile že po celem svetu razvite posebne šole, zavodi, ki so v enakovrednih ali prilagojenih programih izobraževale slepe in KEYWORDS slabovidne učence. Accesibility/assistive technology, visually impaired, social contact, international camps 1 UVOD Članek ni strogo znanstveno zasnovan, saj ne sledi povsem znanstveni shemi problem–hipoteza–eksperimentiranje– potrditev / ovržba hipoteze, prav tako so rezultati pogojno kvantitativno merljivi (opravljeni so bili intervjuji). Kot problem članka lahko vidimo predvsem socialno vključenost slepih in slabovidnih v vsakdanjem življenju (". . raziskave pa so pokazale, da je prisotnost okvare vida pomemben napovednik težav v socialnih odnosih . ." [1]), prav tako pa sledenje Slika 17. Zaključna slika udeležencev v Zadru S hitrim razvojem osebnih računalnikov v zadnji četrtini 20. Permission to make digital or hard copies of part or all of this work for personal or stol. so bili šolarji z okvaro vidne funkcije zopet v težkem classroom use is granted without fee provided that copies are not made or distributed položaju, saj prve tehnološke rešitve niso bile prijazne za for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must uporabnike s posebnimi potrebami. Konec 80. let so se že be honored. For all other uses, contact the owner/author(s). razvijali prvi bralniki zaslona, npr. JAWS v Ameriki. Vzporedno Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia so se vzpostavljali tudi povečevalniki zaslonske slike in druga © 2020 Copyright held by the owner/author(s). 492 podporna tehnologija. Da bi omogočili stik z najnovejšo • obvladovanje osnovnih računalniških programov tehnologijo tudi mladim z okvaro vidne funkcije, so na univerzi (pisanje življenjepisa, MS Office, delo s pdf v Linzu že leta 1993 organizirali prvi tabor računalništva in dokumenti ...); komunikacije (ICC camp) [3]. • osnove različnih programskih jezikov. Od takrat se je v 18 evropskih državah zvrstilo že 26 taborov (samo dvakrat, leta 2008 in 2020, je bil tabor odpovedan) za Občasno delavnice pripravijo tudi lokalni mlade med 16 in 20 letom. Tabora se udeležujejo mladostniki iz tehnologi/znanstveniki. Tako so bili npr. v Angliji gostje vse Evrope, občasno pa se pridejo tudi posamezne skupine iz razvijalci Microsoft-a, na univerzi v Dresdnu so slepi lahko drugih kontinentov (npr. zadnja leta prihaja ekipa iz Japonske). prizkusili robota - psa vodiča, podobne dodatne vsebine so na sporedu skoraj vsako leto. 3 STRUKTURA TABORA 3.3 Druženje, zabava, prosti čas, vsakdanje veščine 3.1 Glavni noti tabora Čez skoraj 3 desetletja prakse se je na taborih potrdila preprosta Če je bil tabor vzpostavljen z idejo, da slepi in slabovidni mladi "zdravo-razumska" misel, da je IKT seveda sijajno orodje, potrebujejo hiter stik s podporno tehnologijo za njihove potrebe, vendar le-to. pa se je kmalu izkazalo, da tako kot večinski populaciji v šolah, O odnosu tehnologoje in vsakdanjega življenja razmišlja npr. tudi njim primankuje predvsem zdravo druženje, izmenjava Gorazd Kocijančič: "Znanstveno pojmovanje stvarnosti in izkušenj s sovrstniki iz drugih držav, urjenje povsem tehnološko obvladovanje sveta nam v tej sferi [vrednot] ne more vsakodnevnih veščin, preprosta zabava. pomagati, ker gre pri njej za območje našega primarnega Shema tabora se je glede na potrebe, želje, mladostnikov življenjskega sveta in prvotnih danosti naših čutov in doživetij. prilagajala in usklajevala tekom let, danes je urnik Znanost iz tega sveta vedno izrašča kot nekaj drugotnega, kot desetdnevnega tabora približno tak, kot ga prikazuje slika 2. koristna abstrakcija in osiromašitev. Pozivi k temu, naj znova Seveda se urnik in predvsem vsebine iz leta v leto dopolnjujejo, uveljavimo etiko in vrednote, so prazni, ker etika ni projekt, ni si nadgrajujejo, spreminjajo. je mogoče izmisliti kot kakšne nove mode." [4]. Ljudje smo poklicani predvsem v odnos (npr. dr. Urša Zabukovec: ". . kazen doživljamo že zdaj za naše neizpolnjevanje tega, k čemur smo poklicani, se pravi, za neudejanjanje dejavne ljubezni, odnosov . ." [5]), kar danes občasno ob poudarjanju znanstvenega napredka pozabljamo. Udeleževanje organiziranih prireditev prav gotovo še ni odnos, je pa stopnica pri pridobivanju socialnih veščin, ki lahko pripeljejo na začetek nekega odnosa. ("Največja učitelja na tem področju [socialnih veščin] sta številnost in kvaliteta izkušenj v družbi ..."[6]) Mladi med poletnimi počitnicami uživajo predvsem v druženju. Tekom let so tudi šolski sistemi posameznih držav ujeli korak z novimi podpornimi tehnologijami, tako da je trenutno Slika 18. Urnik 10-dnevnega tabora glavna vrednost taborov predvsem človeško druženje. Nekaj časa je tem temam namenjeno že v dnevnih delavnicah (nacionalne kuhinje, pogovorne skupine, filozofski krožki, predstavljanje 3.2 IKT vsebine sebe, učenje tujih jezikov, ženske teme, orientacija, skrb za pse Stik z najnovejšo podporno tehnologijo, spletno dostopnostjo, vodiče . .), ostalo pa v večernih aktivnostih (jam sessions, obvladovanjem računalniških orodij . . je še vedno ena od dveh zmenkarije, športne igre, ogledi mesta . .), večerni zabavi, prioritet taborov. Najpomembnejše IKT vsebine so: celodnevni ekskurziji in spontanemu druženju prek celega tabora. Dodatna vrednost za udeležece je tudi angleščina, ki je uradni • bralniki zaslona in sintetizatorji govora (JAWS, jezik vseh taborov. Marsikateri mladostnik ima tu prvo priliko, SuperNova, NVDA, Orca, podpora v i-phonih, da večdnevno temeljito preizkusi svoje znanje angleščine in androidih . .): drugih tujih jezikov v sproščenem vzdušju, brez pritiska • povečevalniki zaslona (ZoomText, SuperNova, morebitnega ocenjevanja. Po učilnici, hodnikih in v okolici stavb Windows-ove nastavitve, nastavitve pametnih vse dni žubori deset in več jezikov. telefonov ...); Prednost taborov ICC je tudi njegova organizacija. Razvili so • spletna dostopnost; se na pobudo posameznih ozaveščenih posameznikov, vsako leto • socialna omrežja; na novo pa nastaja kot preplet mladih, učiteljev, tehničnih • dostopen software na računalnikih, tablicah in poklicev, psihologov, sorodnikov. pametnih telefonih (mešalniki zvoka, pretvorniki med različnimi oblikami datotek, aplikacije za prepozanvanje predmetov, slik, barv . ., aplikacije za lažji vsakdan, igre ...); 493 4 ICC SLOVENIJA 2021 V Sloveniji smo ICC tabor organizirali že leta 2001 v Škofji Loki, sedaj pa je vrsta spet prišla na nas. Naslednje leto naj bi od 14. do 23. julija v Kranju gostili približno 70 slepih in slabovidnih mladostnikov ter njihovih spremljevalcev. Organizacija taborov je že utečena, veliko priprav, proračuna pa pade na lokalnega organizatorja. Tabor je tudi priložnost, da se lokalna in državna javnost dodatno ozavesti o posebnih potrebah, s katerimi se soočajo posamezniki. Inkluzivni proces (vključevanje vseh posameznikov s posebnimi potrebami, motnjami) ni vezan samo na leta šolanja ali državne ustanove. Koliko bomo vključujoča družba, bo odvisno predvsem od tega, kako se bomo povezovali izven sistemov, v vsakdanjem življenju. Slika 19: Slovenska ekipa v Nemčiji, 2016 Letos je bil tabor na Portugalskem po 12 letih prvič odpovedan zaradi pandemije, seveda je veliko vprašajev zaradi 6 ZAKLJUČEK le-tega tudi za naslednje leto, vendar se že dogovarjamo, da bi v primeru ponovne odpovedi vsaj del tabora izvedli na daljavo. Vsekakor so tabori ICC po četrt stoletja že dobro utečen projekt Eden od namenov članka je tudi povabiti morebitne partnerje izrazito povezovalne narave. Tehnološki, pedagoški in s kakršnimikoli idejami, da se pridružijo projektu. Tudi iz socializacijski aspekti se prijetno združujejo in dopolnjujejo, organizacijskega vidika so tabori zelo raznovrsten mozaik - pomembni pa so tudi drugi vidiki tabora. turizma, pedagogike, podpornih strategij, tehnologije, športnih Upamo, da bomo lahko mladim iz vse Evrope ponudili lepo dejavnosti . . Pri organizaciji bomo sodelovali z občino Kranj, izkušnjo tudi naslednje leto v Sloveniji. Društvom slepih in slabovidnih Slovenije, različnimi podjetji, TIC Kranj, Gimnazijo Kranj, Javnim zavodom Ratitiovec, Slovensko filantropijo, veseli pa bomo tudi vseh drugih. VIRI [1] Stanimirov K., Jablan B., Anđelković M. in Vučinić V..: Socialna vključenost kot izziv za otroke in mlade z okvaro 5 PRVOOSEBNE IZKUŠNJE vida (str. 409-414), Zbornik Celostna obravnava, vseživljenjsko učenje in socialna vključenost oseb z Slovenske dijake in študente spremljam po Evropi že od leta okvaro vida, Ljubljana, 2019 2013 (Latvija, Nizizemska, Nemčija, Belgija, Hrvaška, Velika Britanija). Čeprav so tabori mišljeni za enkraten obisk, se večina [2] Auer, J.: Zgodovinski razvoj Zavoda za slepo in udeležencev pri nas in po Evropi vrača po večkrat - dvakrat, slabovidno mladino do nastanka Centra IRIS (str. 23-29), Zbornik Celostna obravnava, vseživljenjsko učenje in trikrat ali celo štirikrat, nekateri ponovno prihajajo tudi kot socialna vključenost oseb z okvaro vida, Ljubljana, 2019 soorganizatorji, pripravljajo svoje delavnice ali samo obiščejo stare prijatelje. Ravno neposredne prvoosebne izkušnje in [3] A Short History: From the Idea to the Programme zgodbe so najboljši dokaz, da tabori zares delujejo, tako v smislu Internetni vir: https://www.icc-camp.info/about/history [Pridobljeno 3. 9. 2020] učenja kot druženja. Slovenski študent se je na ICC taboru spoznal s poljskim dekletom; ko je končal magistrski študij, se je [4] Kocijančič, G.: Etike si ni mogoče izmisliti kot nove mode preselil v Varšavo, se poročil in dela v podružnici Apple-a za Internetni vir: https://www.rtvslo.si/velikih-5/kocijancic- dostopnost njihovih storitev. etike-si-ni-mogoce-izmisliti-kot-nove-mode/301800 [Pridobljeno 2. 9. 2020] Ne bom navajal še drugih "novičarskih" zgodb, naj ena zadošča za poduarek, da tabori v malem in velikem spreminjajo [5] Zabukovec, U.: Ta avtor je izzivalen in prav je tako, ker s življenja udeležencev. tem sproži globlji teološki razmislek, Internetni vir: https://www.rtvslo.si/kultura/intervju/ta-avtor-je-izzivalen- in-prav-je-tako-ker-s-tem-sprozi-globlji-teoloski- razmislek/531234 [Pridobljeno 3. 9. 2020] [6] Strnad N.: Socialne spretnosti slepih in slabovidnih (str. 421–425), Zbornik Celostna obravnava, vseživljenjsko učenje in socialna vključenost oseb z okvaro vida, Ljubljana, 2019 494 Osebna eRedovalnica Personal electronic grade book Bojan Jeram Dijaški dom Vič Gerbičeva ulica 51a 1000 Ljubljana, Slovenija bojan.jeram@guest.arnes.si POVZETEK Vzgojitelj v dijaškem domu mora biti pri svojem delu seznanjen 1 UVOD tudi s šolskimi ocenami svojih dijakov. Večina šol ima v ta Prvi začetki uvajanja eRedovalnice v šole segajo v leto 2001, namen vzpostavljen sistem eRedovalnice. Uporaba tega sistema storitev eRedovalnice sta šolam in staršem ponudili kar dve pa je žal v večini primerov tudi plačljiva. Zamisel o uvedbi podjetji [1]. Vendar takrat za eRedovalnico (razen v treh pri osebne eRedovalnice je tako nastala iz potrebe po spremljanju razvoju storitve sodelujočih šolah) še ni bilo veliko zanimanja. ocen in v izogib plačljivi uporabi šolskih eRedovalnic. Za Politika in stroka sta bili pripravljeni v skrbi, da starši ne bi izvedbo osebne eRedovalnice sem uporabil aplikacijo Mahara na preveč nadzirali svojega otroka, onemogočiti tudi nekaj kar je portalu Listovnik.sio.si. Z uvedbo osebne eRedovalnice sem pozitivno [2]. poleg dijakov seznanil tudi njihove starše, ki sem jih povabil, da Šolsko leto 2007/2008 je tako prvo leto uspešne uporabe pri spremljanju ocen s pomočjo osebne eRedovalnice tudi sami eRedovalnice. V tem letu je eRedovalnico uporabljala skoraj sodelujejo. Uvedba osebne eRedovalnice se je izkazala zelo četrtina slovenskih šol in več kot 5.000 staršev [3]. pozitivno, saj mi je zelo olajšala in poenostavila delo pri Danes si težko predstavljamo šolo brez ustreznega spremljanju ocen. informacijskega sistema, ki podpira interne pedagoške in administrativne procese in olajša vodenje šolske dokumentacije. KLJUČNE BESEDE Ko pa so razni podatki (ocene, izostanki od pouka, itd.) zapisani Izobraževanje, vzgoja, učni uspeh, ocene, elektronska v digitalno zbirko podatkov, je eRedovalnica zgolj logično redovalnica izkoriščanje možnosti, ki jih ponuja informacijska tehnologija. Čeprav danes že zelo veliko staršev izkorišča možnost ABSTRACT spremljanja ocen s pomočjo eRedovalnice, pa nekateri to še The educator in the boarding school must be at his work notified vedno zavračajo saj menijo, da zmanjšuje zaupanje med staršem with the school grades of his students. For this purpose most in otrokom. Menijo tudi, da bo zaradi nenehnega nadzora, otrok schools have an electronic grades book. Unfortunately, in most postal nesamostojen in nezmožen reševati nastale probleme [4]. cases the use of this system is chargeable. The idea of introducing Vzgojitelj v dijaškem domu vodi skupino 28 dijakov in je a personal electronic grades book is arose from the need to seznanjenost z njihovimi ocenami pri njegovem delu zelo monitor grades and to avoid the paid use of school electronic pomembna. Ker pa možnost spremljanja ocen s pomočjo šolskih grades book. For implement a personal electronic grades book I eRedovalnic ni brezplačna, naš dijaški dom tega ne uporablja. Za used the Mahara application on the Listovnik.sio.si. With the potrebe spremljanja ocen si vzgojitelj tako pripravi svojo introduce of personal electronic grades book I acquainted a evidenco (v obliki zvezka ali ocenjevalnih listov) v katero nato students and their parents. I invited the parents to participate in dijaki vpisujejo svoje ocene. monitoring the grades with the help of a personal electronic Prva težava pri tem načinu spremljanje ocen je, da dijaki zelo grades book. The introduction of the personal electronic grades neredno prihajajo k vzgojitelju vpisovat svoje ocene, druga pa, book proved to be very positive, it is greatly facilitated and da Pravilnik o bivanju v dijaškem domu [5] v dokumentaciji simplified my work in monitoring grades. dijaškega doma ne predvideva tudi vodenja evidence ocen. KEYWORDS Education, learning success, grades, electronic grade book 2 PRIPRAVA USTREZNE REŠITVE Zadal sem si cilj, da poiščem drug način seznanjanja z ocenami in vodenja evidence, ki bo enostavnejši tako za dijake kot tudi za vzgojitelja. Predvsem pa sem želel doseči bolj sprotno sporočanje ocen s strani dijakov. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed Odločil sem se, da v ta namen uporabim aplikacijo Mahara na for profit or commercial advantage and that copies bear this notice and the full portalu Listovnik.sio.si (e-Listovnik). Vsak dijak si bo v e- citation on the first page. Copyrights for third-party components of this work must Listovniku v obliki dnevnika ustvaril svojo osebno eRedovalnico. be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Nato bo ustvaril še pogled v katerega bo vključil osebno © 2020 Copyright held by the owner/author(s). eRedovalnico in za ta pogled dodelil dovoljenje vzgojitelju, 495 lahko pa tudi svojim staršem. Dijaki bodo nato v osebno Pri ustvarjanju osebne eRedovalnice sem dijakom delo eRedovalnico, ki je v obliki spletnega dnevnika le še sproti poenostavil tudi tako, da sem za posamezne letnike vnaprej vpisovali svoje ocene. pripravil predloge osebnih eRedovalnic z že oblikovano Ker so nekateri dijaki že prej vodili svoje lastne evidence preglednico in vnesenimi učnimi predmeti. Na ta način sem ocen v obliki preglednice na papirju ali pa v svoji mobilni napravi, dosegel tudi enoten izgled vseh osebnih eRedovalnic (slika 1). sem smatral, da jim vodenje evidence ocen v e-Listovniku ne bo predstavljalo dodatnega odvečnega dela. S to rešitvijo pa je odpravljen tudi problem glede spornosti [5] vodenja evidence ocen s strani vzgojitelja oziroma dijaškega doma. S to rešitvijo je evidenca ocen v lasti dijaka, ki vzgojitelju le omogoči vpogled v evidenco. 3 PREDSTAVITEV REŠITVE STARŠEM Pred začetkom šolskega leta sem staršem posredoval spletni vprašalnik v katerem sem jih vprašal ali so v preteklem šolskem letu uporabljali šolsko eRedovalnico, o razlogih zakaj jo oziroma je ne uporabljajo, ter ali jo nameravajo še naprej uporabljati. Slika 1. Osebna eRedovalnica Starše sem ločil na tiste katerih otroci so v preteklem letu že obiskovali srednjo šolo in na tiste katerih otroci so obiskovali še osnovno šolo. Tabela 1. Uporaba eRedovalnice Tisti dijaki, pri katerih nekateri učni predmeti v predlogi niso Da Ne Skupaj bili ustrezni, pa so morali po iz predloge ustvarjeni eRedovalnici, le še spremeniti, dodati ali odstraniti neustrezne učne predmete. Srednja Na voljo pa jim je bila tudi predloga z oblikovano preglednico šola 2 9 11 brez vnesenih učnih predmetov. Med uporabo osebne eRedovalnice sem dijake spodbujal k Osnovna sprotnemu vpisovanju ocen. Vpisovanje ocen sem vsakodnevno šola 4 2 6 redno spremljal. Pri tem mi je bil v veliko pomoč sistem, ki me Skupaj 6 11 17 je seznanjal o novih vpisih ocen, tako sem vpogledal le v osebne eRedovalnice v katerih so bile narejene spremembe (slika 2). O vsaki na novo vpisani oceni sem se z dijaki pogovoril in jih tudi Od 17 prejetih odgovorov je bilo le 6 takih, ki so uporabljali pohvalil za dosledno vpisovanje ocen. eRedovalnico (tabela 1). Na vprašanje zakaj eRedovalnice ne uporabljajo, pa je bila večina odgovorov, da svojemu otroku zaupajo, da jim ocene sporoča sam. Na prvem roditeljskem sestanku sem vsem staršem predstavil rezultate ankete in svojo zamisel uvedbe osebne eRedovalnice. Starše sem tudi pozval, da v kolikor želijo spremljati ocene svojega otroka preko eRedovalnice, da v tem šolskem letu v ta namen uporabijo osebno eRedovalnico. Za starše sem pripravil tudi nazorna navodila kako se prijavijo na portal Listovnik.sio.si in si uredijo pogled v osebno eRedovalnico svojega otroka. 4 UVEDBA REŠITVE Dijakom sem osebno eRedovalnico predstavil na prvem sestanku skupine. Pojasnil sem jim namen novega načina sporočanja njihovih ocen vzgojitelju ter moja pričakovanja glede doslednosti. Ker večina dijakov ni imela AAI uporabniške Slika 2. Seznam pogledov, kot ga vidi vzgojitelj identitete, sem jim pripravil navodila za prijavo na portal Listovnik.sio.si in ureditev uporabniškega profila. Sledile so vodene delavnice v računalniški učilnici. Na delavnicah sem jim V prvi polovici meseca decembra sem obiskal vse razrednike najprej predstavil spletno aplikacijo Mahara (Listovnik.sio.si), in preveril v osebnih eRedovalnicah vpisane ocene z dejanskim nato pa je sledilo: stanjem na šoli: − ustvarjanje osebne eRedovalnice − ustvarjanje pogleda in dodeljevanje pravic vpogleda − skoraj polovica (11 od 23) dijakov je imela vpisane vse (vzgojitelj, starši) ocene − ureditev nadzorne plošče – prikaz osebne − petini (5 od 23) so manjkale ena ali dve oceni eRedovalnice na osnovni strani − slabi tretjini (7 od 23) pa je manjkalo več ocen 496 Ob zaključku prvega ocenjevalnega obdobja sem dijake seznanil z rezultati preverbe, pohvalil vse tiste, ki so dosledno vpisovali ocene v svoje osebne eRedovalnice, tisto slabo tretjino, pri katerih je manjkalo več ocen, pa spodbudil k bolj odgovornemu vpisovanju ocen. 5 IZOBRAŽEVANJE NA DALJAVO Ko sem se odločil za uvedbo osebne eRedovalnice nisem vedel, da bo to šolsko leto potekalo nekoliko drugače kot smo bili do sedaj navajeni. Ko se je 16. marca začelo izobraževanje na daljavo, so se zaprli tudi dijaški domovi in dijaki so odšli domov. n = 13 Z začetkom ocenjevanja na daljavo, pa je prvi dijak svojo tako Slika 4. Stališče staršev do eRedovalnice pridobljeno oceno samoiniciativno vpisal že 31. marca. K vpisovanju na daljavo pridobljenih ocen sem nato pozval tudi vse ostale dijake skupine. Tudi v tem času sem redno spremljal Vpisovanje ocen v osebno eRedovalnico je bilo s strani njihove vpise ocen in jih s povratnim odzivom po elektronski več ine dijakov sprejeto pozitivno (slika 3) in so ocene tudi sproti pošti pohvalil ali kako drugače spodbujal k delu in izobraževanju vpisovali. Seveda pa je bilo tudi pri tem nekaj dijakov, ki jim je na daljavo. bilo to odveč, kot bi jim bil oziroma jim je odveč tudi kakršen Z njihovim odzivom in vpisovanjem ocen v osebno koli drug način sporočanja ocen vzgojitelju. eRedovalnico sem bil zelo zadovoljen vse do zaključka pouka. Zelo pa me veseli tudi pozitivno stališče staršev glede Osebna eRedovalnica je tako predstavljala pomemben del uporabe osebne eRedovalnice (slika 4). mojega dela na daljavo s skupino v času zaprtja šol in dijaškega Aplikacija Mahara za poglede vodi tudi seštevek vseh doma. vpogledov, tako mi je bil na voljo tudi podatek koliko vpogledov v osebno eRedovalnico posameznega dijaka sem opravil. Število vpogledov je bilo seveda odvisno od učnega uspeha 6 EVALVACIJA posameznega dijaka, predvsem pa od njihovega doslednega in sprotnega vpisovanja ocen. Osebne eRedovalnice dijakov, ki so Ob koncu pouka sem izvedel evalvacijo dela v minulem šolskem bolj sprotno vpisovali svoje ocene imajo tako več vpogledov. letu. K evalvaciji sem povabil dijake in njihove starše. Med drugim sem jih vprašal tudi o njihovem stališču do osebne eRedovalnice. − Najmanjše število vpogledov 12 Dijaki: Kako si sprejel vpisovanje ocen v eRedovalnico? − Največje število vpogledov 163 − Povprečno število vpogledov 52 Če iz izračuna povprečja izvzamem tri najmanjša in tri največja števila, pa je povprečno število vpogledov 45. 7 DISKUSIJA Spremljanje ocen s pomočjo osebne eRedovalnice se je izkazalo kot veliko bolj učinkovito in enostavnejše. Na novo vpisanim ocenam je vedno sledil pogovor o pridobljeni oceni. Če kot n = 17 vzgojitelj od dijakov pričakujem odgovorno in sprotno sporočanje ocen, je prav, da tudi dijaki od mene dobijo sprotni povratni odziv. Slika 3. Stališče dijakov do eRedovalnice Mnenje ene od dijakinj: "Drugače pa super, da nas takole spodbujate tako v domu (ko smo še bili tam) in sedaj ko smo Starši: Kakšno je vaše stališče glede uporabe osebne doma in pohvalite ob dobri oceni. Sem prepričana, da vsaki eR edovalnice za sporočanje ocen vzgojitelju (in staršem)? dijakinji dvigne samozavest in pa je bolj ponosna nase ter se želi zaradi tega še dodatno potruditi." Sporočanje ocen vzgojitelju s pomočjo osebne eRedovalnice pa je tudi s pedagoškega vidika bolj vzgojno. Za sporočanje ocen je odgovoren dijak in ne razrednik preko informacijskega sistema šole. Osebna eRedovalnica temelji na zaupanju in gradi odnos med dijakom in vzgojiteljem. Informacijsko-komunikacijska tehnologija pri tem služi zgolj kot sredstvo, ki sistem naredi pregleden in učinkovit. Za izvedbo osebne eRedovalnice sem izbral spletno aplikacijo Mahara. Sistem ponuja vse kar sem za uspešno 497 izvedbo in uporabo potreboval, vendar pa bi si vseeno želel dve bom pri dijakih gradil odnos na zaupanju in odgovornosti. Pri dopolnitvi: nadaljnji uporabi osebne eRedovalnice pa si želim, da bi bila − gradnik "Pogledi, ki jih spremljam" (prikaže poglede, pozitivno sprejeta s strani velike večine vseh dijakov, ter da bi ki so pripeti v nadzorni seznam) bi moral imeti vsi starši, ki želijo spremljati ocene svojih otrok preko možnost razvrstitve prikazanih pogledov glede na eRedovalnice, le te spremljali preko osebnih eRedovalnic. naslov pogleda ali glede na priimek in ime avtorja pogleda. Trenutno so pogledi razvrščeni izključno le po datumu, ko so bili ustvarjeni. LITERATURA − gradnik "Zadnje spremembe" pa naj prikazuje le poglede, ki so pripeti v nadzorni seznam. Trenutno [1] Šolski razgledi. 2001. S klikom do šolskih ocen. prikazuje vse poglede do katerih imam dostop, torej (September 2001). Pridobljeno 18. 08. 2020 iz tudi tiste, ki so definirani kot javni in me ne zanimajo. http://www.solski-razgledi.com/14-2001/2.html. Pri postavitvi gradnika na nadzorno ploščo bi bilo [2] Moj mikro. 2007. E-redovalnica: Nedoslednost. (Oktober potrebno dodati filter v katerem določimo katero 2007).Pridobljeno iz skupino pogledov želimo spremljati na seznamu. http://www.mojmikro.si/center/povem_naglas/e- redovalnica_nedoslednost. 8 ZAKLJUČEK [3] Moj mikro. 2008. Uspešno prvo leto elektronske redovalnice. (Avgust 2008). Pridobljeno iz S spremljanjem ocen dijakov s pomočjo njihovih osebnih http://www.mojmikro.si/news/uspesno_prvo_leto_elektron eRedovalnic se je spremenil tudi način mojega dela. Dijakov ske_redovalnice. nisem več vedno znova spraševal ali imajo kakšno novo oceno, [4] Tina Deu. 2016. Nadzor nad otroki: zakaj ne maram e- ampak sem se z nimi, ko so oceno vpisali o tem pogovoril. Zaradi redovalnice?. (September 2016). Pridobljeno 18. 08. 2020 uporabe osebne eRedovalnice sem se z dijaki pogosteje in bolj iz https://siol.net/siol-plus/kolumne/nadzor-nad-otroki- usmerjeno pogovarjal o njihovih ocenah. Večina dijakov je zakaj-ne-maram-e-redovalnice-426458. sporočanje ocen vzgojitelju s pomočjo oebne eRedovalnice [5] Pravno-informacijski sistem RS, 2019. Pravilnik o bivanju sprejela pozitivno in tudi odgovorno. v dijaških domovih. (Januar 2019). Pridobljeno 19. 08. Neglede na (ne)dostopnost (plačljiva storitev) šolskih 2020 iz eRedovalnic, bo moje spremljanje ocen še naprej potekalo s http://www.pisrs.si/Pis.web/pregledPredpisa?id=PRAV134 pomočjo osebnih eRedovalnic. Z uporabo osebne eRedovalnice 29. 498 Raba IKT kot predmet filmske upodobitve The use of ICT as a subject of film depiction Robert Jereb Osnovna šola Idrija Lapajnetova ulica 50 5280 Idrija, Slovenija robert.jereb@guest.arnes.si POVZETEK using the brainstorming method. It is important that individual events (shots) and their connections are formed with the film Kratki film učencev OŠ Idrija predstavlja primer, ko IKT nastopa editing and the final product in mind. Most of the filming was kot predmet filmske obravnave in sredstvo za delo (namenski performed by the students themselves and the editing was taken programi za montažo). Filmski medij ima pri učencih precejšen over by the mentor. The basic idea of the film is the tension motivacijski in ustvarjalni potencial, zato ga je smiselno between the technological domination (ICT) of our lives and the uporabiti v vlogi sredstva za pridobivanje digitalnih kompetenc. fundamental human pursuit of freedom. Moreover, it draws Medij tako ponuja obilo možnosti za delo na taksonomski stopnji attention to the difference between the technical characteristics vrednotenja. Pri izdelavi kratkega osnovnošolskega filma smo of devices and their social uses. The film can also be useful as a poenostavili nekatere faze ustvarjanja. Poseben poudarek smo teaching (motivational) material when making a general namenili oblikovanju izvirne in jasno določene ideje ter čim bolj reflection on the role of ICT (mostly smartphones) in our lives. natančnemu zapisu dogajanja (zaporedje kadrov), kar smo snovali s pomočjo metode brainstorming. Pomembno je, da se KEYWORDS posamezne dogodke (kadre) in njihove povezave oblikuje že z mislijo na montažo in končni izdelek. Snemali so večinoma Primary school film, social use of technology, ideology, digital učenci sami, montažo pa je prevzel mentor. Osnovna ideja filma competences je napetost med tehnološko nadvlado (IKT) našega življenja in temeljnim človeškim stremljenjem po svobodi. Poleg tega tudi 1 UVOD opozarja na razliko med tehničnimi značilnostmi naprav in njenimi družbenimi rabami. Film je uporaben tudi kot učno Predstavljena bosta proces ustvarjanja in sporočilo kratkega (motivacijsko) gradivo za šolsko rabo za splošen premislek o filma, v katerem je tema vloga IKT v šolskem prostoru in vlogi IKT, predvsem pametnih telefonov, v našem življenju. posledično tudi v širši družbi. Način, kako je prikazan vpliv družbene rabe tehnologije, pa omogoča izhodišče za KLJUČNE BESEDE prevrednotenje vloge IKT v današnji socialni stvarnosti, zlasti z Osnovnošolski film, družbena raba tehnologije, ideologija, vidika mlajših uporabnikov (osnovnošolcev). Filmski medij je za digitalne veščine prikaz te tematike zelo primeren, saj omogoča prepričljivo vizualizacijo učinkov rabe komunikacijskih naprav. Podobe, ABSTRACT fotografije, posnetki imajo pri mladih precejšnjo vlogo pri The short film created by the students of Idrija Primary School is dojemanju, gradnji razumevanja in delovanju v družbi, zato jim an example of ICT appearing as the subject of film treatment and je film privlačen kot ustvarjalno sredstvo in so za delo zelo a means of work (dedicated editing programs). The film medium motivirani. has considerable motivational and creative potential for the Na OŠ Idrija že nekaj let deluje filmski krožek, katerega students, therefore it makes sense to use it as a means of namen je bil sprva seznanjanje s kakovostnimi filmi in zatem tudi acquiring digital competences. The medium thus offers plenty of ustvarjanje lastnih kratkih filmov. Film Generacija Z: Ne al᾽ ja?, opportunities to work at the taxonomic level of evaluation. We ki bo predstavljen v nadaljevanju, je bil gotovo zaradi svoje have simplified some stages in the making of the short primary drugačne tematizacije komunikacijskih sredstev v letu 2019 school film. Special emphasis has been placed on the formation uvrščen na več festivalov in osvojil nekaj nagrad: zmaga na of an original and clearly defined idea and the most accurate filmskem natečaju KoRaketa (tema je bila Korak v prihodnost), record of events (sequence of shots) possible. That was devised sodelovanje v tekmovalnem programu 13. mednarodnega filmskega festivala ZOOM.13 v Ljubljani, na filmskem festivalu MEET – Movies for European Education and Training, ki je potekal v Rimu, je prejel nagrado Menzione speciale in nazadnje Permission to make digital or hard copies of part or all of this work for personal or je film v Izoli na 55. srečanju najmlajših filmskih in video classroom use is granted without fee provided that copies are not made or distributed ustvarjalcev Slovenije, ki poteka pod okriljem JSKD, prejel zlato for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must priznanje in najpomembnejšo nagrado – priznanje za najboljši be honored. For all other uses, contact the owner/author(s). film, ki ga podeljuje otroška žirija. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 499 1.1 Povzetek filma v začetek filma oz. z njim določiti ritem, čutno in čustveno Skupina otrok, oblečenih v črna (temna) oblačila se počasi naravnanost v filmu (za prvi del), ki je moral biti temačen, premika proti šoli. Njihovi gibi so mehanični, podobni, ves čas utesnjujoč, da bi dosegli čim bolj učinkovito nasprotje z drugim pa gledajo zgolj v ekrane pametnih telefonov oz. tablic. Tudi delom filma. njihova hoja po šoli je podobna: kolona, uniformni gibi, slepa zazrtost v zaslone. Najbolj se to pokaže pri pouku, ko otroci hkrati dvigujejo roke in kosilu, ko imajo spet vsi enake gibe in hkrati zajemajo hrano. A že od začetka je ena učenka drugačna: njena oblačila so svetla, hoja in gibanje sta spontana, nima elektronske naprave. Drugi jo seveda izločajo, končno pa se najde učenka, ki jo sprejme, vendar še naprej so njene oči uprte le v zaslon naprave. Drugačna deklica ji nazadnje vzame pametni telefon in ji pokaže, da lahko sebe in okolico dojema na nov način. Tudi ostale odvrneta od elektronskih naprav in vsi skupaj se razposajeno gibajo, igrajo z žogo in drugimi rekviziti, ter Slika 20: Učenci korakajo proti šoli zroč v pametne telefone nazadnje stečejo v naravo. (Trajanje 5:50.) oz. tablice 2.2 Zapis poteka dogajanja 2 USTVARJANJE FILMA Običajno se idejo za film razvija naprej v obliki scenarija, vendar Delo je potekalo po naslednjih korakih: oblikovanje ideje, zapis smo za šolsko rabo zaradi časovne omejenosti ter predvidene poteka dogajanja (namesto scenarija), snemanje in montaža. V kratke forme izdelka pisanje pravega scenarija opustili, mdr. tudi prvih dveh korakih smo delali tudi že z mislijo na samo zato, ker v filmu ni dialogov. Namesto tega smo oblikovali potek snemanje: predvsem za prvi del filma smo izbrali lokacije dogajanja, ki je bil na koncu zapisan kot zaporedje dogodkov oz. snemanja, scenografijo in oblačila – kolikor je bilo potrebno, da kadrov, hkrati s tem pa so potekale še druge priprave na snemanje se je poenotil videz nastopajočih (glavnih igralcev in statistov), (npr. izbira lokacij). Nekaj sprememb in dopolnitev je bilo nismo pa se pri teh vidikih posebej ustavljali. Z didaktičnega kasneje še med samim snemanjem (prehod iz »mračnega« prvega vidika je bilo pri ustvarjanju morda preveč spontanosti, vendar bi dela filma v drugi, radostni del). Praviloma v tej fazi ugotovimo, po drugi strani pretirano načrtovanje, ki je sicer pri daljših kaj v filmu dejansko deluje oz. ima neko vlogo. Prav tako filmskih izdelkih nujno, lahko zaviralo motivacijo in elan za pravočasno izločimo preveč ambiciozne prizore, ki presegajo ustvarjanje. naše tehnične zmožnosti, predvsem pa zmožnosti učencev, saj lahko to kasneje ob spoznanju, da nečesa ni možno posneti tako, 2.1 Oblikovanje ideje kot so si zamislili, hitro vodi v upad zanimanja in motivacije. Začetna faza je zelo pomembna, kajti govori o tem, kaj želimo Za oblikovanje razvoja zgodbe in gradnjo filma po prikazati, povedati. Vsebinsko je bilo oblikovanje ideje vezano posameznih prizorih (kadrih) smo uporabili isto metodo kot pri na natečaj KoRaketa 2019 z nosilno temo Korak v prihodnost, oblikovanju ideje. Pri tem je lahko v veliko pomoč zgodboris [1], kar je bilo vodilo ustvarjanju, naša osnovna ideja pa je bila vendar te tehnike nismo uporabili, temveč smo se o posameznih predstaviti vizijo šolskega prostora v prihodnosti in določen prizorih in estetskih vidikih (npr. prazni prostori, temne barve, aspekt funkcije IKT v njem. uniformno gibanje v prvem delu filma, v drugem delu pa ravno Po začrtanju osnovne usmeritve so vsi naslednji koraki lažje obratno) ustno dogovorili, kako bodo izgledali. konkretno določljivi. Treba pa je bilo neprestano misliti na uresničljivost ideje v danih pogojih šolske interesne dejavnosti, 2.3 Snemanje in montaža kajti nima smisla pretiravati s kompleksnostjo ideje in zgodbe s Snemanje je trajalo približno teden dni v februarju 2019 kompliciranim potekom dogajanja. Pomembno je, da učenci ves predvsem v času pouka, organizacijo snemanja pa so praktično čas razumejo, kaj delamo (vsebina) in kako bomo kaj posneli in ves čas vodile devetošolke (izbira sodelujočih igralcev in kasneje montirali (tehnično-izvedbeni vidik). podajanje navodil za oblačila, rekviziti, izbiranje dodatnih Idejo smo oblikovali predvsem z metodo brainstorming in lokacij snemanja itd.), prav tako so posnele večino materiala. V tako, da je najprej ideje zapisal vsak posameznik, potem v dveh tej fazi se nam je pridružil učitelj David Stegu, ki je film sproti skupinah, nazadnje pa smo skupaj pretresli uporabnost zapisanih montiral in ga opremil z glasbo, tako da so učenci lahko delo predlogov. Skupaj smo ocenili primernost idej, tj. njihovo prejšnjega dne pogledali pred poukom v šolski predavalnici, kar uresničljivost v filmskem mediju. Vsebinsko pa smo izhajali iz jih je še dodatno motiviralo. Želeli bi si sicer aktivnejšega same izkušnje otrok, ki jim je komunikacijska naprava zelo sodelovanja učencev pri montaži, predvsem kar zadeva uporabo pomemben del življenja oz. delovanja v družbi. Namesto programa, vendar smo morali tak pristop zaradi časovne stiske in analitične pripovedi smo izbrali enostavnejši pristop, ki je tehničnih omejitev opustiti – v šoli namreč nismo imeli na predstavil določeno stanje stvarnosti, je pa zahteval preobrat v razpolago dovolj zmogljivega računalnika. Po drugi strani pa mišljenju, dojemanju stvarnosti in vedenju. tudi drži, da so učenci posredno film sestavljali že med pripravo Vizualno izhodišče za estetiko prvega dela filma so bili na snemanje ter med snemanjem, saj se obe fazi načrtuje in uvodni kadri iz znanstvenofantastične klasike Metropolis oblikuje z mislijo na montažo filma in končni izdelek. Lahko režiserja Fritza Langa, ko delavci monotono, uniformno in tako zatrdimo, da je zaradi predhodno dovolj določenega poteka apatično korakajo po hodniku. To vzdušje smo poskušali vnesti dogajanja umanjkal dejansko le tehnični vidik uporabe programa 500 za montiranje filma. Montaža je sicer zanimiva in poučna faza, saj je moč učencem pokazati, da je mogoče iz istih posnetkov sestaviti različne zgodbe, kar vodi v spoznanje o konstruirani realnosti vsakdana [2], ki v dobršni meri poteka prek sodobnih komunikacijskih sredstev (v filmu so to pametni telefoni in tablice). 2.4 Vloga mentorja Mentorjeva vloga v fazi oblikovanja ideje in gradnje poteka dogajanja je bila predvsem v tem, da se ni preveč oddaljilo od osnovne zamisli in teme (o čem film govori), da smo ohranili funkcijsko ustrezne prizore in opustili tiste, ki za osnoven tok Slika 21: Uniformna motorika otrok pri kosilu zgodbe niso bili pomembni, ter da smo izbirali bolj enostavne in V filmu je dejansko v ospredju funkcija komunikacijske s snemalnega vidika uresničljive in prepričljive prizore. Seveda tehnologije v skupnosti – informacije in komunikacija potekata je bilo potrebno upoštevati tudi osnove filmskega jezika [3]. V praktično samo prek tehničnega pripomočka. Ta raba je tako primeru, da ima mentor na začetku izoblikovano zamisel o obsežna in totalna, da vključuje skorajda celotno komunikacijo vsebini in poteku dogajanja, je treba delo voditi tako, da učenci subjekta z okoljem. Čuti so tako (vsaj deloma) izključeni, čim bolj samostojno pridejo do želenega cilja – da se jim ne nadomešča jih tehnologija kot posrednik med okoljem in telesom. posreduje domala izdelan potek dogajanja – in pri tem dodajo Impulze posameznik ne sprejema več neposredno iz okolja, čim več predlogov za izboljšave. Pri tem filmu je bila za mentorja temveč prek tehnološkega vmesnika – tudi povsem enostavno še zanimiva naloga: pripraviti učence, da spremenijo pogled na opravilo, kot je hoja po stopnicah, kar je vidno v enem kadru vlogo pametnih telefonov, in sicer tako, da jih ne dojemajo kot filma. Ta vmesnik/posrednik (pametni telefon) pa dejansko ni nekaj dobrega, kar omogoča številne socialne možnosti, temveč več individualiziran, temveč uniformiran in enak za vse, kar je nasprotno kot nekaj negativnega, nekaj, kar omejuje svobodo in prikazano z enako motoriko otrok (npr. pri kosilu). S tem film individualnost. nakazuje vpliv pametnih naprav v resničnem svetu, kajti skozi navidezno pestrost, raznolikost, prilagodljivost in možnostjo neizmerne personalizacije dajejo videz individualnosti – a 3 IDEOLOŠKI IN DRUŽBENI VIDIKI vendar gre za razlike znotraj enake prakse, v resnici pa Šolsko polje in medijski prostor sodita v okvir t. i. ideoloških reproducirajo istost oz. enako delovanje, želje, mišljenje. aparatov države (IAD), s pomočjo katerih se vzpostavlja, Film seveda ne zajame problematike celostno, a opozarja na obnavlja oz. reproducira družbena razmerja oz. družbene tveganje, ki smo mu izpostavljeni v družbi totalnega dostopa formacije. Pomembni način oz. sredstva, s pomočjo katerih se to informacijsko-komunikacijskih sredstev – da dejansko izgubimo dosega, so vsakokratna komunikacijska sredstva, v sodobnem nadzor. Gre za možnost distopične prihodnosti, v kateri je času torej tudi, kar sodi na področje IKT, pri čemer posebej skupnost prikazana kot neke vrste totalitarna, kar je v opoziciji z izpostavljamo komunikacijski aparat, ki ga imamo vedno s sabo današnjim pojmovanjem svobodne, demokratične in raznolike in funkcionira že kot jedro posameznikove komunikacijske skupnosti, saj tak družbeni ustroj razumemo kot pravilen in kot strukture. Mehanizem IAD deluje tako, da ideologija »naravno danost«. Prvi (totalitarni) del filma pa ima močan posameznika interpelira v subjekt [4], tj. v pripadnika skupnosti učinek zaradi popolnega obrata, ko se učenci odrečejo in kulture. Dandanes se to zelo učinkovito izvršuje prek IKT – komunikacijskim napravam in dejansko zaživijo, se veselijo – so osamitev skorajda ni mogoča, naprava je vedno z nami. otroci in niso skupina odtujenih in uniformnih posameznikov. Omenimo še koncept družbene rabe tehnologije, ki dodatno Kaže opozoriti še na eno pomembno dejstvo. Znotraj fikcijskega osvetli sporočilo filma. Kot je na primeru radia pokazal že B. sistema je za pripadnike totalitarne družbene formacije taka Brecht [5], jo je potrebno ločevati od same zmožnosti aparata, ureditev lahko dojeta kot normalna, naravna in nujna danost. V zavzemal se je namreč, da bi bil radio naprava za komunikacijo, filmu je to prikazano s tem, da skupina zavrača drugačno učenko, ne le za distribucijo načrtovanega programa. Film pa nakazuje, a se potem po preobratu sistem spremeni, nastopi nova da smo nemara že pri obratu: pametni telefon morda ni več normalnost, s čimer je pokazano, da prejšnje stanje ni naravno in komunikacijski aparat, kot ga »naravno« dojemamo (razen samoumevno, temveč je vzpostavljeno kot tako. In seveda, ne le govora in besedilnih sporočil), temveč je postal predvsem v fikciji, to isto velja tudi za našo stvarnost – tudi ta realnost je distribucijski. Posreduje nam namreč določen vnaprej (ideološko) konstruirana prek IAD oz. družbenih institucij. pripravljen paket: modus vivendi, način razmišljanja, usmerja delovanje ipd. – skratka je izvrsten medij ideološke distribucije. Nekateri aspekti naštetega so v filmu pokazani dovolj 4 UPORABNOST ZA ŠOLSKO POLJE neposredno in skrajno, da imajo učinek na gledalca. Pri ustvarjanju filma izpostavljamo štiri dosežene cilje. Najprej gre za vlogo IKT kot predmeta obravnave in kot sredstva izdelavo filma. Zatem so pomembni snovanje, snemanje in montaža filma kot umetniškega, izdelka (tvorbna, estetska funkcija). Nadalje je končni izdelek izraz vrednotenja družbene rabe IKT, tako s strani članov filmske ekipe kot vsakokratnih gledalcev (vrednotenje kot višja taksonomska stopnja). Nazadnje 501 pa je film lahko učno gradivo in motivacijsko sredstvo za učence v čim bolj produktivno rabo IKT, konkretno pametnih premislek omenjene rabe komunikacijske tehnologije in naprav, telefonov, s čimer jih usmerjamo v to, da jih razumejo kot in to ne le na področju humanistike v OŠ (družboslovni predmeti sredstvo za ustvarjalno delo. in interesne dejavnosti) in tudi ne le za omejeno starostno skupino. VIRI 5 ZAKLJUČEK [1] Goetz, A. 2016. Animirajmo! Ljubljana, MIZŠ. [2] Vogrinc, J. 1998. Medijsko strukturiranje vsakdana. V Produkcija filma Generacija Z: Ne al᾽ ja? je pri učencih Družboslovne razprave. Let. 14, št. 2728 (1998). Str. 48– filmskega krožka OŠ Idrija spodbudila precej ustvarjalne 54. energije in pokazala na potencial, ki ga ima raba IKT pri [3] Pelko, S. 2005. Filmski pojmovnik za mlade. Maribor, osmišljanju njihovega prostora v šolski in širši skupnosti. Aristej. Opozorili so tudi na nevarnosti tehnologije pri njeni (napačni) družbeni rabi. Predvsem je film tisti medij, ki jih zelo pritegne, [4] Althusser, L. 2000. Izbrani spisi. Ljubljana, /*cf. tako v vlogi konzumentov kot ustvarjalcev. Motivacijski [5] Brecht, B. 1983. Radio kot komunikacijski aparat. V potencial je zato smiselno uporabiti tudi za učenje namenskih Problemi: revija za kulturo in družbena vprašanja. Let. 21, programov za obdelavo filmov (in fotografij) ter usmerjati št. 6/8 (1983). Str. 124–125. 502 S spletnimi zemljevidi raziskujem svoj domači kraj Exploring the hometown with web maps Barbara Jevšnik I. OŠ Žalec Šilihova ulica 1 3310 Žalec, Slovenija barbarajevsnik@gmail.com POVZETEK photos of their trips and some plans for cycling and hiking trails. The final product is a colourful palette of educational trips, as Učenci so s pomočjo raziskovalne metode raziskovali svoj seen through the eyes of 5th graders. domači kraj ter kolesarske in pešpoti znotraj občine Žalec ter izdelali svoj predlog družinskega izleta, ki so ga opremili z KEYWORDS zemljevidom ter ga s pomočjo Windows orodij predstavili ostalim učencem. Pri tem so si pomagali z različnimi spletnimi Maps, web tools, orientation, cycling trails, hiking trails zemljevidi (Google zemljevidi, Najdi.si - zemljevid…), ki so jim bili v veliko pomoč pri samem izračunu dolžine poti, določanju 1 UVOD premagane višinske razlike izbrane kolesarke poti, spoznavanju krajevnih znamenitosti, ki ležijo ob poti ter izdelavi preprostega Danes živimo v digitalni dobi, kjer se na vsakem koraku zemljevida. Pridobljeno znanje so učenci samostojno ob pomoči srečujemo z različnimi oblikami tehnologije. Po podatkih IKT nadgrajevali s pomočjo praktičnega in teoretičnega Statističnega urada Slovenije ima dostop do interneta kar 89 % raziskovanja kolesarskih in pešpoti doma ter okolice. Končni gospodinjstev v Sloveniji. Večina nas ima dostop do interneta, rezultat pa so v obliki govornega nastopa predstavili v razredu. različnih spletnih orodij ter pametnih telefonov, pa vendar Njihovi izdelki so se zrcalili v obliki turističnih knjižic, odmeva podatek komisarke za digitalno gospodarstvo in družbo PowerPoint predstavitev, fotografij izletov, načrtov kolesarskih EU Gabrielove, da 44 % Evropejcev še vedno nima osnovnih in pešpoti. Skratka nastala je pestra paleta poučnih izletov skozi digitalnih spretnosti. oči petošolcev. Učenci dandanes na spletu preživijo večji del prostega časa, obožujejo novo tehnologijo, njihovo navdušenje pa raste, če s KLJUČNE BESEDE pomočjo le-teh raziskujejo in pridobivajo nova znanja. Zemljevidi, spletna orodja, orientacija, kolesarske poti, peš poti Pomembno je, da že zgodaj spoznajo, da različne spletne strani niso namenjene samo zabavi in kratkočasenju, ampak lahko s ABSTRACT pomočjo le-teh odkrivajo in spoznavajo pomembne podatke. Pri Students explored their hometown using the research method. tem je zelo pomembno, da njihovo navdušenje, željo po novih They explored the cycling and hiking trails in the municipality of znanjih ter uporabi računalnika pri šolskem delu čim prej Žalec, designed their own idea for a family trip and added a map vpeljemo v izobraževalni proces. Učenci naj bi že v zgodnjem to it. Using the Windows programs, they presented the idea to učnem obdobju pridobili čim večji spekter tehnološkega znanja. their schoolfriends. They used various web maps, for example Zelo veliko strokovnjakov je mnenja, da se digitalne pismenosti Google Maps or Najdi.si map. Those maps helped them to začnemo učiti čim bolj zgodaj, že na prehodu iz vrtca v šole, ko determine the length of the trail, the elevation changes along the smo za to najbolj dovzetni [1]. cycling trail and the local tourist sights that we can visit along Učenci se s spoznavanjem svoje domače pokrajine seznanijo the trails. Using those maps, they created their own basic map. že v predšolskem obdobju. Svoje znanje v višjih razredih Students upgraded their acquired knowledge by practical and poglobijo in se v 4. razredu srečajo z orientacijo ter izdelavo theoretical research of cycling and hiking trails in their local area preprostega zemljevida domače pokrajine. Pri pouku družbe v 4. with its surroundings and they used information and in 5. razredu je tudi v učnem načrtu zapisano, da učenec zna communications technology (ICT) independently. The result of poiskati različne vire za pridobivanje informacij ter zbrati their research work was a presentation in their classroom. podatke tudi s pomočjo informacijske tehnologije [2]. Students created tourist brochures, Power Point presentations, 2 METODE DELA Delo petošolcev je potekalo v šolskem in domačem okolju. Permission to make digital or hard copies of part or all of this work for personal or Zaradi varstva osebnih podatkov bomo v prispevku uporabljali classroom use is granted without fee provided that copies are not made or distributed samo moško obliko učenca. for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must Najprej je bilo potrebno ugotoviti, kako vešči so že be honored. For all other uses, contact the owner/author(s). desetletniki z računalnikom ter kakšno je njihovo poznavanje Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). domače pokrajine. Ugotovili smo, da imajo v razredu skoraj vsi 503 učenci pametne telefone ter da vsakodnevno dostopajo do spleta, Na podlagi teh podatkov, natisnjenega zemljevida in bodisi zaradi komunikacije s sošolci ali pa zaradi igranja igric. praktičnih izkušenj z izleta, so naredili še lasten zemljevid. Svoje Brez pametnega telefona je bila le ena deklica, ki pa do spleta raziskovalno delo so zaključili z govorno predstavitvijo svojega skoraj vsakodnevno dostopa preko domačega računalnika. Vsi predloga izleta. učenci v razredu vedo, kaj je Google, kako se do njega dostopa in kako z njegovo pomočjo iščemo pomembne podatke. V razredu smo si ogledali tudi aplikacijo Google zemljevidi ter se 3 REZULTATI učili, čemu služi in kako jo lahko uporabimo. Učenci so Učenci so v zaključku predstavili svoje končne izdelke. Nekateri omenjeno aplikacijo zelo hitro usvojili, najbolj všeč jim je bilo so jih pripravili v Power pointu, brušuri, drugi so izdelali iskanje doma in znanih znamenitosti kraja s pomočjo možnosti samostojni zemljevid (slika 2 in 3). pogleda - Street View. V okviru pouka, v običajnih razmerah, smo skupaj s pomočjo spletnih brskalnikov poiskali naravne in kulturne znamenitosti domačega šolskega okoliša posameznega učenca. Ključne znamenitosti smo zbrali in izdelali preprost miselni vzorec s programom X-mind. Sledil je skupen pregled in preučevanje zemljevida o že obstoječih kolesarskih poteh občine Žalec. Sledilo je samostojno delo s pomočjo IKT v domačem okolju. Pri iskanju informacij o posameznih znamenitosti kraja so si Slika 2. Brošure Slika 3. Predstavitev brošur pomagali z brskanjem po spletu. Dobljene podatke so uporabili kot fotografije in podatke pri končnih predstavitvah. Pri tem je pomembno, da so bili aktivni vsi učenci. V oddelku Primer slike 1 prikazuje znamenitost Jame Pekel, kjer je imamo kar četrtino učencev, ki imajo težave z razumevanjem učenec na spletu poiskal fotografijo in jo opremil z ustreznimi jezika. Ker ni bilo nujno, da izdelajo svojo predstavitev v Power podatki. Point obliki, so izdelali svoj zemljevid. Pri tem v ospredju niso bile njihove težave z jezikom, zato so bili zelo motivirani za delo in so se zelo izkazali pri sami izdelavi končnega izdelka in pri tem pokazali veliko ustvarjalnost. Učenci so najprej predstavili osnovne podatke o dolžini poti, višinski razliki, ki jo pri tem opravijo, kar je prikazano na sliki 4. Slika 1. Opis naravne znamenitosti V tej fazi raziskovanja so učenci lahko pokazali svojo ustvarjalnost, inovativnost in na podlagi zemljevida poiskali nove kolesarske poti na spletnih zemljevidih, ki še niso vrisane Slika 4. Žalec, kolesarka pot, dolžina 8, 2km, višinska na zemljevidu kolesarskih poti občine Žalec, vendar so jim bile razlika 55 m všeč, bodisi zaradi dolžine ali zaradi kulturnih in naravnih V nadaljevanju so nam eni prikazali le del poti z vmesnim znamenitosti na poti. Svoje zamisli so vnesli v predstavitve postankom, kar nam prikazuje slika 5. Power Point, tako, da je sledilo sprotno poročanje o napredku Učenci so si pomagali na različne načine ter le-to vključili v učenca. V šoli so nam ob predstavitvah poročali, kako napreduje končne predstavitve. Učenec je v navodila za pot vključil tudi njihov projekt. Učiteljica jih je po potrebi usmerjala in možnost funkcije Street view (slika 6) ter podal podroben opis spodbujala. V oddelku je četrtina tujcev, razumevanje jezika je poti. Pri tem je izkazal dobro poznavanje možnosti uporabe IKT slabo. Pri tem projektu so lahko podatke iskali na spletu tudi v (street view, slika zaslona, vnašanje slike v predstavitev). svojem jeziku. Na podlagi zbranih podatkov o kulturnih in naravnih znamenitosti kraja ter učencu izbrano kolesarsko potjo so se lotili praktičnega dela. Najprej so na spletnih zemljevidih vrisali posamezne postojanke in označili svojo kolesarsko traso. Te obstoječe zemljevide so natisnili in jih preizkusili v praksi. 504 Z učenci smo na koncu opravili analizo posameznih predlogov. Osredotočili smo se na orise poti, zemljevide, jih med sabo primerjali in ugotavljali, kje se lažje znajdemo. Ugotovila sem, da so učenci pri analizi dokaj kritični, podajali so zanimive ter konstruktivne predloge. Opazila sem, kako so napredovali v sami orientaciji, predvsem pa v poznavanju svojega lastnega kraja. Vsem učencem smo s pomočjo odprtih možnosti ponudili različne načine predstavitve, kjer so lahko izkazali svoje znanje, pridobili nove spretnosti in izkušnje. Tako, so vsi učenci, ne glede na učne ali govorne težave izdelali svoj končni izdelek. 4 DISKUSIJA Slika 5. Postanek Savinova hiša in del opisa poti Uporaba omenjenih programov, aplikacij omogoča, da učenci razvijajo digitalno pismenosti, ki jim omogoča lažje doseganje želenih ciljev. Učencem uporaba spletnih orodij kot npr. Google zemljevidov pri pouku omogoča hitri vpogled v celotno pot, ki jo bodo opravili sami ali njihovi sošolci, znamenitosti, ki ležijo ob poti. Učenci se pri tem preizkušajo in urijo v sami orientaciji preko spletnih zemljevidov in v praksi. Učenci so v raziskovalno delo vložili veliko truda in časa. Pri tem je nastala res cela paleta izdelkov, opremljena s pomočjo IKT-ja z zelo dobrimi primeri kratkih družinskih izletov. Za samo izvedbo takšnega projekta je pomembno, da učitelj sam skrbi za razvijanje digitalnih kompetenc. Učitelj mora sam raziskovati in iskati različne aplikacije, ki so enostavne za uporabo, mora jih zelo dobro poznati, da jih lahko prenese v sam pouk in pri tem izkoristi visoko motivacijo učencev za delo. Tovrstni projekti so učencem zanimivi zaradi večje uporabe IKT pri pouku in v domačem okolju in raziskovanju domačega okolja in drugačnega načina dela pri pouku. Slika 6. Opis poti in slike satelita Poleg zgoraj omenjenega Google zemljevida so se učenci 5 ZAKLJUČKI posluževali še z drugimi prikazovalniki razdalj, kar vidimo Znanje je velika vrednota in moč. Učenci bodo lahko uporabljene prikazano na sliki 7. aplikacije in programe uporabljali in nadgrajevali tudi v prihodnje, bodisi pri pouku kot v vsakdanjem življenju. Nastali so zelo dobri izdelki, ki bi celo lahko dopolnili že obstoječe kolesarske trase v občini Žalec. Predvsem pa so dober pokazatelj ustvarjalnosti petošolcev. Prav v času karantene smo zelo dobro občutili, kako je digitalna pismenost pomembna tako za učitelja kot za učence. Prav to nam je dalo misliti, da klasični pouk ni dovolj, ampak je treba čim hitreje učence digitalno opismeniti ter jih seznaniti z različnimi računalniškimi orodji, ki jim bodo v pomoč pri premagovanju ovir. VIRI [1] Železnik, R. (2018). Uvajanje digitalnih tehnologij in spoznavanje računalniške pismenosti pri osnovnošolskih Slika 7. Celotna pot otrocih v Sloveniji. Magistrsko delo. Ljubljana: Pedagoška fakulteta. Svojo predstavitev so zaključili z različnimi hudomušnimi [2] Budnar, M. (2011). Učni načrt. Program osnovna šola. slogani, kot so »Ko dolgčas ti je, sedi na kolo in razmigaj svoje Družba. Ljubljana: Ministrstvo za šolstvo in šport: Zavod telo. S kolesom v naravo po zdravje in razgled. Sedi na kolo, pa RS za za šolstvo. boš videl, kako je v naši dolini kolesariti lepo«. [3] Javrh, P., Možina, E., Bider, K., Kragelj, K., Volčjak, D., Sepaher, G., Gjerek, L., Matavž, H., Rejec, P., Babič 505 Ivaniš, N. in Brecelj, V. (2018). Digitalna pismenost. Na DOI=https://ec.europa.eu/commission/presscorner/detail/sl poti do življenjske uspešnosti. Ljubljana: Andragoški /IP_18_102 center Slovenije.https://pismenost.acs.si/wp- [7] Sonck, N., Livingstone, S., Kuiper, E., in de Haan, J. content/uploads/2018/09/Digitalna-pismenost-e- (2011). Digitalna pismenost in veščine varne rabe verzija.pdf. interneta . [4] Jurišič, M. (1999). Samopodoba šolskega otroka. DOI=https://safe.si/sites/default/files/digitalskillsreport- Ljubljana: Pedagoška fakulteta. eukidsonlineprevod_0.pdf. [5] Marentič Požarnik, B. , Magajna, L. , Peklaj, C. (1995). [8] Statistični urad Republike Slovenije [SURS]. 2018. Izziv raznolikosti : stili spoznavanja, učenja, mišljenja. Osnovnošolsko izobraževanje. Psihologija učenja in pouka. Nova Gorica: Educa. DOI=http://www.stat.si/StatWeb/Field/Index/9/71 [6] Novi ukrepi za spodbujanje ključnih kompetenc in digitalnih spretnosti ter evropske razsežnosti izobraževanja. (2018) EU. IP/18/102. 506 Geografija in izobraževanje na daljavo Geography and distance education Vesna Jurač Osnovna šola Antona Martina Slomška Vrhnika Pod Hruševco 33 1360 Vrhnika, Slovenija vesna.jurac@gmail.com POVZETEK način poučevanja ima poleg prednosti tudi slabosti, zahteva pa tudi nekatere prilagoditve in določeno mero iznajdljivosti. Šolsko leto 2019/2020 je bilo nekoliko drugačno od preteklih Napovedi nakazujejo možnost, da se lahko podobna situacija šolskih let. Pandemija koronavirusa covid-19 je namreč na vseh ponovi tudi v prihodnje, zato moramo biti pripravljeni tudi na ravneh, od vrtca do univerze, narekovala vzgojno-izobraževalno takšno obliko izobraževanja. Pri tem pa se lahko opremo na delo na daljavo, ki je zaradi nekaterih omejitev zahtevalo izkušnje iz preteklega šolskega leta: ognemo se narejenim določene prilagoditve. V prispevku se osredotočamo na izveden napakam ter se zgledujemo po primerih dobre prakse, ki jih lahko praktičen primer poučevanja geografije na daljavo v šestem tudi nadgradimo. razredu osnovne šole. Izpostavljamo dobre in slabe strani takšne V prispevku je predstavljen primer izobraževanja na daljavo oblike vzgojno-izobraževalnega dela ter podajamo nekatere ideje pri geografiji v šestem razredu na Osnovni šoli Antona Martina za njegovo nadgradnjo v primeru, da bi bilo poučevanje na takšen Slomška Vrhnika. Prikazane so prednosti in slabosti takšnega način potrebno izvesti tudi v prihodnje. načina vzgojno-izobraževalnega dela ter izzivi, s katerimi smo se KLJUČNE BESEDE spopadali. Podanih pa je tudi nekaj idej za izboljšanje. Geografija, vzgojno-izobraževalno delo na daljavo 2 GEOGRAFIJA V OSNOVNI ŠOLI IN ABSTRACT POUČEVANJE NA DALJAVO The school year 2019/2020 was slightly different from previous Cilj geografije je, da učenci postanejo geografsko pismeni. To school years. The pandemic of the Corona virus Covid-19 hit us pomeni, da deklarativno znanje (poznavanje temeljnih at all levels, from kindergarten to university, leading to distance geografskih pojmov in procesov) nadgradijo s proceduralnim education, which required several adjustments due to certain znanjem (razvijanje sposobnosti in spretnosti, ki so povezane z limitations. In this paper, we focus on a practical example of učnimi metodami in delovnimi postopki (npr. terensko delo, distance geography teaching in the sixth grade of primary school. ekskurzije, eksperimentalno delo, iskanje in analiza virov, We highlight the pros and cons of distance educational process načrtovanje ipd.)). [1] and provide some ideas for its upgrade in case distance teaching Za pouk geografije v osnovni šoli so najprimernejši tematski would again be necessary in the future. učni projekti s prvinami raziskovalnih vprašanj, geografsko in KEYWORDS kritično mišljenje na podlagi problemskega pristopa (študija primerov, problemska razprava, učne simulacije, igra vlog ipd.), Geography, distance education izvedba terenskega dela in ekskurzije. [1] Geografija je šolski predmet, ki je že v osnovi naravnan tako, da učenci informacije o geografskem okolju oziroma zaznave 1 UVOD pridobivajo z vsemi čutili. Zato mora učitelj različnim Šolsko leto 2019/2020 je bilo prav posebno in drugačno od zaznavnim tipom učencev (motorični, vizualni, slušni) omogočiti preteklih šolskih let. Soočili smo se s pandemijo koronavirusa raznovrstno učno gradivo za prehajanje od konkretnih zaznav k covid-19, ki je onemogočila običajno poučevanje z neposrednim zahtevnejši abstrakciji. Pri tem pa mora upoštevati tudi nazornost, kontaktom učiteljev in učencev. Potrebna je bila sorazmerno da lahko učenci svoje (čutne in čustvene) zaznave povežejo z hitra prilagoditev na drugačen način vzgojno-izobraževalnega racionalnimi. Poučevanje geografije torej od učitelja zahteva dela na vseh ravneh, od vrtca do univerze. Le-to je potekalo na ustrezno izbiro in uporabo učnih pripomočkov ter nenehno daljavo preko informacijsko komunikacijske tehnologije. Takšen interakcijo učenca in učitelja. Skozi pouk geografije učenci razvijajo celostno geografsko mišljenje, ki temelji na nenehnem medpredmetnem povezovanju. Permission to make digital or hard copies of part or all of this work for personal or Težnja po čim boljšem znanju učencev zajema tudi classroom use is granted without fee provided that copies are not made or distributed preverjanje in ocenjevanje znanja, ki je odvisen tako od učenja for profit or commercial advantage and that copies bear this notice and the full kot tudi od poučevanja. Sprotno preverjanje spodbuja k citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). samonadzoru, sprotnemu utrjevanju ter informiranju o napredku. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Poleg tradicionalnega pisnega in ustnega ocenjevanja se © 2020 Copyright held by the owner/author(s). 507 ocenjujejo tudi geografski izdelki (npr. plakati, prospekti ipd.), Na naši šoli je pouk geografije naravnan tako, da oblikujemo dejavnost (npr. učni eksperiment, terensko delo ipd.) in pristne raziskovalna vprašanja, ki učence motivirajo k raziskovanju in naloge (npr. učne simulacije, življenjske, praktične in uporabne samostojnemu odkrivanju geografskih vsebin. Velik del pouka naloge). namenimo tudi problemskemu pristopu, kjer učeneci preko igre Vse našteto pa postane prav poseben izziv, ko gre za vlog, problemske razprave ipd. odgovorijo na zastavljena poučevanje na daljavo. Vse aktivnosti morajo biti prilagojene geografska vprašanja, sodelujejo pri terenskem delu ipd. ter tako dani situaciji. Takrat še bolj kot običajno pride v ospredje v veliki meri sami raziščejo neko geografsko temo. Učitelj pa jim uporaba informacijsko kumunikacijske tehnologije (IKT). IKT je pri tem ves čas v podporo. Seveda pa je učence na takšen način sestavljajo informacijske tehnologije, telefonija, elektronski dela pri geografiji potrebno navajati že od samega začetka, torej mediji, vse vrste obdelave in prenosa avdio in video signalov ter že v šestem razredu. vse funkcije nadzora in spremljanja, ki temeljijo na tehnologiji Tukaj je potrebno omeniti, da smo imeli pri tem v letošnjem omrežja. [2] Delo s pomočjo IKT pri pouku geografije je delno šolskem letu precej omejitev. Pred pričetkom izobraževanja na že prisotno tudi v času običajnega pouka, kadar je to smiselno in daljavo so bila izvedena le tri srečanja v živo (blok ure), torej šest potrebno. šolskih ur, saj je v šolskem letu 2019/2020 pouk geografije v Delo na daljavo na nekatere geografske aktivnosti nima šestem razredu potekal po fleksibilnem predmetnuku v drugi večjega vpliva, nekatere aktivnosti so na takšen način lahko polovici šolskega leta. Šest šolskih ur, ki so bile izvedene v živo, izvedene delno, drugih pa sploh ni mogoče izvesti. predstavljajo le 17 % od vseh 35 ur (100 %), ki so po učnem načrtu namenjene geografiji v šestem razredu. Učenci morajo v šestem razredu usvojiti temeljna geografska znanja, ki jih nato 3 IZOBRAŽEVANJE NA DALJAVO NA nadgrajujejo v višjih razredih. Učenci so bili pred začetkom OSNOVNI ŠOLI ANTONA MARTINA šolanja na daljavo seznanjeni z uvodnimi informacijami, SLOMŠKA VRHNIKA spoznali so tudi vesolje oziroma naše Osončje, preostali del učne Na Osnovni šoli Antona Martina Slomška Vrhnika je pouk na snovi pa je bilo potrebno obravnavati na daljavo. daljavo potekal med marcem in junijem leta 2020, ko je bil na Zaradi vsega omenjenega smo način dela tokrat morali precej državni ravni zaradi pandemije koronavirusa covid-19 izdan prilagoditi. V skladu z navodili vodstva šole smo na šolski spletni Odlok o začasni prepovedi zbiranja ljudi v zavodih s področja strani tedensko objavljali navodila za šolsko delo, ki so ga morali vzgoje in izobraževanja. V razmeroma kratkem času se je bilo učenci sami opraviti doma in po obsegu ni smelo presegati časa, potrebno prilagoditi na nov način vzgojno-izobraževalnega dela, ki je namenjen običajnemu pouku geografije. Potrebno je bilo ki je od vseh akterjev (učiteljev, učencev in njihovih staršev) tudi prilagajanje glede obsega in izbora učnih vsebin. zahteval tudi nekatere prilagoditve in tudi dobro mero iznajdljivosti. Pri tem pa je bilo potrebno upoštevati štiri pomembne vidike takšnega poučevanja: tehnični, didaktični, organizacijski in psihološki vidik. Zaradi nenadne izdaje odloka ni bilo možno izvesti posebnih priprav oziroma izobraževanj za izvedbo pouka na daljavo. Tega smo se na Osnovni šoli Antona Martina Slomška Vrhnika lotili nekoliko manj sistematično kot to počnemo sicer. V začetni fazi je pouk na daljavo potekal s pomočjo objave navodil za delo na šolski spletni strani. Ta način dela smo dopolnili z uporabo elektronske pošte, spletnih učilnic, različnih spletnih orodij in okolij, z video konferencami ipd. Uporabili smo tudi elektronska Slika 1: Primer tedenskih navodil za učence na šolski spletni gradiva številnih institucij (založb, zavodov ipd.), ki so se dokaj strani. hitro odzvale na takšen način dela (s ponudbo spletnih izobraževanj, prostih dostopov do učnih gradiv, izobraževalnih Za poučevanje geografije na daljavo smo uporabljali vsebin ipd). Vsak izmed učiteljev naše šole pa se je nato na izključno komunikacijo preko šolske spletne strani in podlagi lastne presoje odločil, kakšne oblike in metoda dela ter elektronske pošte, saj se je izkazalo, da vsi učenci (vsaj na (spletna) orodja in okolja za poučevanje na daljavo bo uporabil začetku izobraževanja na daljavo) niso opremljeni z ustrezno pri predmetu, ki ga poučuje. računalniško opremo oziroma niso vešči dela z drugimi spletnimi orodji. 4 GEOGRAFIJA NA DALJAVO V ŠESTEM V začetni fazi dela na daljavo smo se osredotočili na ponavljanje in utrjevanje snovi s pomočjo učbenika in delovnega RAZREDU zvezka. Nadaljevali pa smo z obravnavo nove učne snovi. Tudi vzgojno-izobraževalno delo na daljavo pri geografiji v Informacije so učenci samostojno pridobivali s pomočjo šestem razredu na Osnovni šoli Antona Martina Slomška različnih virov in literature (učbenik, atlas, video posnetki na Vrhnika je sledilo potrjenemu učnemu načrtu. Vsebina je bila spletu ipd.). Raziskovalna vprašanja na delovnih listih so torej znana, prilagoditi pa je bilo potrebno oblike dela, saj je delo spodbudila njihovo geografsko in kritično razmišljanje. Ob na daljavo v času pandemije virusa koronavirusa covid-19 za oblikovanju povzetkov snovi v zvezke so urili sposobnost učence in učitelje postalo obvezni del izobraževanja. ločevanje bistvenega od nebistvenega. S sprotnim preverjanjem ob koncu vsakega obravnavanega učnega sklopa pa so bili učenci 508 usmerjeni k samonadzoru, sprotnemu utrjevanju ter informiranju pa jim je običajno vzelo ogromno časa (samo iskanje primernega o napredku. Zaradi posebnih okoliščin je ocenjevanje potekalo spletnega gradiva in aplikacij, ki ustrezajo pouku). drugače od običajnega, in sicer so učenci na podlagi Vsa navodila za delo so bila učencem posredovana preko pridobljenega znanja za oceno izdelali geografski izdelek, šolske spletne strani. Zaradi velike obremenjenosti le-te povezan z učno snovjo. (običajno v določenem delu dneva), je večkrat prihajalo do Delo je potekalo tako, da so učenci v skladu z učiteljevimi motenj (npr. onemogočeno ali dlje časa trajajoče dostopanje do tedenskimi navodili na šolski spletni strani morali prebrati spletne strani oziroma vsebin kot običajno ipd.). Na tem mestu določeno poglavje v učbeniku in razmisliti o njegovi vsebini. vidimo rešitev v delu preko spletnih učilnic, ki predstavljajo Učitelj jim je za lažje razumevanje obravnavane učne snovi posebej pripravljene spletne strani oziroma portale, ki podpirajo posredoval tudi nekaj povzetkov snovi, slikovnih prikazov pa elektronsko izobraževanje. tudi spletnih povezav do video gradiv. Nato so učenci morali Vsak učitelj se je po lastni presoji odločil za spletna orodja oblikovati ustrezen zapis snovi v zvezek in v geografski oziroma okolja, ki jih je uporabljal za izvajanje pouka. Izkazalo slovarček dodati razlago tipičnih geografskih pojmov, s katerimi se je, da vsi učenci šestega razreda (vsaj na začetku izobraževanja so se srečali pri obravnavi snovi. Pomagali pa so si lahko tudi z na daljavo) niso bili opremljeni z (ustrezno) informacijsko atlasom. Pri delu jim je bil ves čas v oporo in pomoč učitelj, s komunikacijsko opremo ali pa niso imeli možnosti dostopa do katerim je potekala komunikacija preko elektronske pošte. spleta od doma. Opaziti je bilo tudi težave z inštaliranjem Ob zaključku vsakega učnega sklopa je učitelj učencem oziroma operiranjem z različnimi spletnimi orodji oziroma okolji. posredoval tudi vprašanja za preverjanje znanja. Svoje odgovore Zato smo se odločili, da pri geografiji v šestem razredu za so učenci lahko preverili s pomočjo dodanih rešitev. poučevanje na daljavo uporabljamo zgolj šolsko spletno stran in V mesecu maju je potekalo tudi ocenjevanje znanja, ki smo elektronsko pošto. Na podlagi tega se je za nujno izkazalo, da ga zaradi posebnih okoliščin morali precej prilagoditi. Namesto učenci že v šoli pridobijo temeljne digitalne kompetence. običajnega pisnega in ustnega ocenjevanja so učenci po Za uspešno delo na daljavo je velikega pomena tudi dobra navodilih na šolski spletni strani izdelali ustrezen geografski organizacija samega dela. Potrebno je vzpostaviti delovni red izdelek (križanko, pesem, plakat, didaktično igro ali model), oziroma osebni načrt učenja z rednim spremljanjem podanih povezan z eno od tem, ki smo jih obravnavali v času šolanja na informacij, saj se v nasprotnem primeru le-te hitro spregledajo in daljavo. Podana so bila natančna navodila oziroma kriteriji, po izgubijo, posledično pa prihaja do neizpolnjenih nalog ali katerih je izdelek bil tudi ocenjen. zamujenih rokov za oddajo. Učenci in učitelji so si morali Omejeno pa je bilo tudi izvajanje terenskega dela. Učenci pogosto deliti delovno opremo (računalnik, tablica) z ostalimi naše šole se v šestem razredu običajno udeležijo dveh šolskih družinskimi člani, zato je delo potekalo v različnih delih dneva, ekskurzij, kjer je poudarek prav na tej obliki šolskega dela. tudi izven predvidenega časa. Posledično je prišlo do brisanja Zaradi odpovedi obeh ekskurzij pa tokrat učenci te izkušnje niso meja med zasebnim in službenim časom oziroma časom, dobili. namenjenim delu za šolo. Kot pomanjkjivost šolanja na daljavo je potrebno izpostaviti tudi fizično in časovno ločenost učiteljev, ki lahko vodi tudi v 5 PREDNOSTI IN SLABOSTI manjšo odzivnost. Pomanjkanje osebnega stika povzroči težji IZOBRAŽEVANJA NA DALJAVO TER vpogled v samo šolsko delo posameznega učenca, težave pri IDEJE ZA IZBOLJŠAVE razumevanju snovi ipd. Učiteljevo razlago, ki je vsekakor boljša Z delom na daljavo smo se na osnovni šoli Antona Martina in nazornejša, pri delu na daljavo zamenja pisanje navodil, Slomška Vrhnika tokrat srečali prvič. To je bil obvezen način komunikacija po elektronski pošti, pošiljanje video gradiv ipd. dela, ki je bil vzpostavljen na državni ravni, in na katerega se je Zelo pomembna pri takšnem načinu dela je tudi ustrezna bilo potrebno prilagoditi v razmeroma kratkem času. Vzgojno- povratna informacija, ki je pogoj za spremljanje učnega napredka izobraževalno delo je potekalo s pomočjo informacijsko posameznika. komunikacijske tehnologije. Ker ni bilo časa za pripravo na takšno obliko pouka, smo delo prilagajali sproti glede na 6 ZAKLJUČEK zmožnosti in potrebe. Učitelji so vsebine, ki jih obravnavajo pri pouku, učencem Delo na daljavo, ki je zaznamovalo letošnje šolsko leto, je izziv morali posredovati preko različnih spletnih orodij in okolij na za vse, tako učence kot učitelje. Zahteva nekoliko drugačen način takšen način, da so bile le-te jasne, nazorne in so učenca postavile dela in uporabo IKT. Zavedamo se, da izobraževanja na daljavo v aktivno vlogo. nikakor ne moremo enačiti z običajnim izobraževanjem v živo. Aktivno učenje predstavlja kognitivno, emocionalno in Ima določene prednosti in tudi slabosti. Zahteva veliko mero socialno akcijo učenca, je osebno pomembno in vpeto v resnične prilagajanja, vse to pa s ciljem, da bi učenci obravnavano učno življenjske okoliščine. Takšen pristop procesu učenja omogoča snov čim bolje razumeli. Za takšno obliko dela so potrebna ustvarjanje kakovostnega ponotranjanja in globljega določena znanja in veščine ter ustrezna oprema. Dobra razumevanje tistega, kar se uči. [3] Učenci so v procesu organiziranost in sprotno delo pripomoreta k dobrim učnim izobraževanja na daljavo dobili aktivnejšo vlogo predvsem z rezultatom. Ker je geografija veda, ki poleg dela z IKT zahteva evalvacijo svojega znanja, zbiranjem dokazov in pridobivanjem veliko osebnega stika in tudi ostale učne metode (npr. terensko povratnih informacij. delo), so z delom na daljavo določene dejavnosti omejene ali jih Učitelji so bili tudi spodbujevalci inovativnosti, predvsem z celo ni možno izvesti. oblikovanjem in posredovanjem vidnega (učnega) gradiva, kar 509 VIRI IN LITERATURA Otvoreno društvo za razmjenu ideja (ODRAZI). http://www.itdesk.info/slo/prirocnik/prirocnik_osnovni_po [1] Učni načrt za geografijo v osnovni šoli. Ljubljana : jmi_informacijske_tehnologije.pdf (20. 8. 2020)(2012) Ministrstvo za šolstvo in šport : Zavod RS za šolstvo: https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/O [3] Licardo, M. 2015. Kognitivne, emocionalne in snovna-sola/Ucni-nacrti/obvezni/UN_geografija.pdf organizacijske kcompetence ki vplivajo na šolski uspeh in (6. 8. 2020) (2011). odnos do izobraževanja. Univerza na Primorskem, Znanstveno-raziskovalno središče, Univerzitetna založba [2] Čelebić, G., Rendulić, D. I. ITdesk.info – načrtovanje Annales, http://www.zrs.upr.si/monografije (20. 8. 2020) računalniškega e-izobraževanja s prostim dostopom – (2015). Priročnik za digitalne pismenosti. Osnovni pojmi informacijsko in komunikacijske tehnologije. Zagreb: 510 Učinkoviti načini učenja rabe spletnih orodij Efficient ways of learning how to use on-line applications Blanka Karanjac Osnovna šola Stična Cesta občine Hirschaid 1 1295 Ivančna Gorica, Slovenija blanka.karanjac@os-sticna.si POVZETEK načini dela na daljavo.[1] Za konkurenčnost bodočih generacij, bo potrebno učinkovito prilagajati klasične metode dela, jih V tem prispevku obravnavam težave klasičnega pouka, ki so s kombinirati z digitalnimi orodji, nadgraditi, nekatere celo pomočjo spletnih orodij lahko premagljive in nekatere metode opustiti. Največja ovira je bila slabo znanje uporabe dela na daljavo s pomočjo IKT, ki bi lahko nadomestile klasične. računalniških orodij, ki pa smo jo zelo uspešno premostili. Zato Hkrati opisujem nekaj ovir, ki smo jih imeli pri šolanju na je nujno, da na predznanju gradimo ne glede na način šolanja, ki daljavo in primere dobrih praks, s katerimi smo jih premostili. bo sledil v naslednjem šolskem letu in tako učinke šolanja Največja težava je bilo neznanje uporabe IKT. Ker učim v OŠ je bistveno povečamo. V nadaljevanju opisujem nekaj primerov bilo potrebno poleg kolegov in učencev hkrati izobraziti tudi dobrih praks izobraževanja prereza široke palete prebivalstva starše. Predstavljam nekaj primerov dobrih praks premagovanja predvsem staršev in učencev, in opišem nekaj prednosti odpora, neznanja in nejevolje pri uporabi spletnih orodij. izobraževanja na daljavo pred klasičnim poukom , ki bi ga bilo KLJUČNE BESEDE smiselno uvesti v reden pouk. Šolanje na daljavo, dobre prakse , premagovanje težav, starši, spletna orodja za poučevanje, izobraževanje staršev in učencev 2 KOMUNIKACIJA IN OPISMENJEVANJE ABSTRACT STARŠEV V OŠ V začetku šolanja na daljavo zaradi covid-19 učitelji in učenci The paper touches upon methods of classical in-class teaching nismo imeli neposrednega stika. Za podajanje snovi smo which could be improved by or even replaced by elements of uporabljali Arnesove spletne učilnice (Moodle), šolsko spletno distance learning. During distance learning due to covid-19 we stran in elektronske naslove staršev. Ker učenci niso imeli have successfully overcome some difficulties in teaching. The uporabniških gesel za spletne učilnice, so bili starši obremenjeni major one has been illiteracy in using communication technology z nadzorom svojih otrok, posredovanjem med učenci in učitelji, and ignorance of useful teaching applications. In this text it is poročanju in posredovanjem dodatne oz. prilagojene razlage. described how parents, students and even colleagues have Tako sem v 14 dneh kot razredničarka 6. razreda in učiteljica successfully overcome their fear and ignorance of modern tujega jezika na predmetni stopnji izmenjala približno 1200 technology elektronskih sporočil. Zato sem iskala učinkovitejše načine KEYWORDS komunikacije. Distance learning, good practice examples, overcoming 2.1 Slabosti elektronske pošte difficulties, parents, on-line teaching applications, educating Elektronska pošta je bila dobro izhodišče za komunikacijo, parents and students vendar je za potrebe šolanja na daljavo zastarela. V tretjem tednu pouka na daljavo smo prebili led in uspešno 1 UVOD izvedli prvo razredno srečanje v živo preko Microsoft Teams konference. Ker noben učenec in skoraj noben starš s tem Učinkovitost šolanja na daljavo v šolskem letu 2019 / 20 bo slabo orodjem ni imel izkušenj, je bilo potrebno ogromno priprav. primerljiva s klasičnim šolanjem, saj smo se ga lotili “ad hoc”. Preko elektronske pošte sem staršem najprej poslala obvestilo, Kljub temu je učenje na daljavo več kot uspešno rešilo mnoge da pripravljam razredno uro, vsebino razredne ure, predvideno izzive, ki so se zdeli pri klasičnem pouku težko premostljivi. uro in datum. Nato sem jim poslala povezavo do spletnih video Klasičen pouk v razredu je nenadomestljiv – prav tako so novi navodil, v katerem je ponazorjeno, kako se Microsoft Teams video sestanek vključijo brez gesla prek spleta. [2] Ker sem izbrala različico v angleščini, sem priložila tudi prevod navodil. Permission to make digital or hard copies of part or all of this work for personal or Nato smo določili dva termina pred prvo razredno uro, v katerih classroom use is granted without fee provided that copies are not made or distributed smo skupaj z otroki in starši vadili samo “vklop”. Med tema for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must “vajama” sem bila hkrati pozorna še na svojo elektronsko pošto be honored. For all other uses, contact the owner/author(s). saj sem večini staršev kljub video navodilu s prevodom pomagala Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). pri določenih korakih (npr. “Klik na moder gumb v ekranu 511 zgoraj desno na katerem z belim piše »join in« . Počakajte da se ekran spremeni.”). V povprečju sem samo med “vajo vklop” z vsakim od 25 staršev izmenjala po 5 elektronskih sporočil. Čeprav se je elektronska pošta izkazala za uporabno, je bilo potrebno najti hitrejši in prijaznejši način. 2.2 Spletne ankete Po omenjeni razredni uri, smo začeli načrtovati naslednje. Ker sem razredno uro načrtovala tudi kot poskus pouka v živo, sem želela povratne informacije. Zanimalo me je predvsem, koliko je razredna ura v živo sploh prijazna do družin – kateri termini jim časovno ustrezajo, kdaj si lahko brez težav elektronske Slika 2. Prikazuje primer slikovnih navodil za uporabo pripomočke delijo, ipd. V želji ustrezati večini sem sestavila spletnega orodja anketo prek aplikacije 1KA, eno za starše in eno za učence. Za orodje 1ka sem se odločila zato, ker sem sklepala, da je večini uporabnikov najbolj domač. Orodje je omogočilo pisanje zgolj 2.4 Video konference enega e-sporočila vsem staršem, zato sem v nadaljevanju šolanja Nobeno spletno orodje ne nadomesti osebnega stika, pa vendar na daljavo za zbiranje povratnih informacij uporabljala le še je videokonferenca trenutno najboljši približek, predvsem kadar spletne ankete; za starše še naprej 1KA, za učence pa sem jih gre za komunikacijo med dvema osebama. Ko so učenci dobili sestavila v Microsoft Forms. Slika 1 je prikaz pregledno zbranih uporabniška gesla in imena za Microsoft Teams sem z učenci povratnih informacij. komunicirala prek video klicev. Kako vzpostaviš video klic so potem učenci naučili tudi svoje starše. Tako sem opravila večino govorilnih ur na daljavo. Za roditeljski sestanek prek video konference pa se po razmisleku nisem odločila. Pretehtali sta dejstvi, da povratne informacije najbolj prijazno in učinkovito lahko zberem prek spletnih anket, podajanje informacij pa po elektronski pošti. Za vse ostalo pa sem bila na voljo individualno prek omenjenih video klicev. 3 OPISMENJEVANJE UČENCEV V OŠ IN PREDNOSTI POUKA NA DALJAVO Slika 1. Primer pridobivanja povratnih informacij prek 1ka 3.1 Arnesove spletne učilnice ( Moodle ) spletne ankete Učenci so tudi v obdobju pred šolanjem na daljavo znali uporabiti spletno učilnico. V času pred šolanjem na daljavo so 2.3 Aplikacija Microsoft Planer tam našli vaje, preverjanja, rešitve vaj in preverjanj, zanimive Konec aprila smo začeli načrtovati ocenjevanje. Eden izmed povezave do video posnetkov IPD. Ker pa niso imeli ciljev je bil sestaviti mrežni plan ocenjevanja tako, da se učencem uporabniških gesel, prek spletne učilnici z njimi nismo mogli ocenjevanje čimbolj prijazno razporedi. Učitelji smo uporabili komunicirati oz. učitelji nismo imeli povratne informacije o orodje Lopolis, učencem in staršem pa sem datume in vsebino njihovem napredku. ocenjevanja prepisala v aplikacijo Microsoft Planer. Do takrat 3.1.1 Prednosti Moodla pred Microsoft Teams so namreč učenci že dobili uporabniška gesla in imena za Microsoft Teams in je bilo tako najlažje. Vendar je bilo treba Moodle je odlično orodje izobraževanje, vendar od uporabnika učence in starše naučiti uporabe tega orodja. Zato sem sestavila zahteva precej časovnega vložka, da se ga nauči uporabljati tako, navodila za uporabo. Tehtala sem med video in slikovnimi da izkoristi vse, kar program zna. Uporabniku začetniku je navodili in sem se na koncu odločila, da bodo slikovna navodila neprijazen, kajti deluje na principih, ki ji uporabniki niso vajeni najbolj uporabna na vseh napravah, tudi kadar ne bo internetne iz drugih spletnih okolij. Hkrati pa je to velika prednost, kajti povezave. Slika 2 prikazuje eno stran slikovnih navodil za učenci težje najdejo »luknje v sistemu« in so preverljivi podatki uporabo aplikacije. Za vsak korak do vpogleda v mrežni plan in povratne informacije (npr. ocenjevanje, statistični podatki o posameznega učenca sem naredila posnetek zaslona, ga vstavila uporabi učilnice ipd.) varni in zanesljivi. v Microsoft PowerPoint, z orodji dopisala komentarje in potem 3.2 Microsoft Teams zaklenila v dokument v PDF formatu. Učencem smo gesla in uporabniška imena dodelili, vendar ne za Moodle pač pa za Microsoft Teams. To se je izkazalo za pametno potezo, kajti uporaba Microsoft Teams je zelo podobna aplikacijam, ki jih mladina že uporablja in so se novemu načinu dela hitro prilagodili. Hkrati pa smo na tak način elegantno in hitro obšli ovire, s katerimi se ukvarjamo v razredu. 512 3.2.1 Disciplina in časovni izkoristek Video konferenca s skupino učencev in z učiteljem je trenutno najboljši približek pouku v realnem času. Kljub temu, da je slab nadomestek za pouk v živo, ima vseeno številne prednosti. Ena izmed teh je ta, da obstaja gumb »mute all« (utišaj vse). V razredu je to včasih časovno zamudno dosežen cilj, sploh pri pouku tujega jezika, kjer je spodbujanje komunikacije bistvo predmeta. Frontalni del pouka zato lahko poteka nemoteno. Vsebinska vprašanja in komentarje učencev lahko obravnava učitelj ločeno, tako da posamezniku da besedo ali pa jih napiše v komentarje. V obeh primerih je tudi to bolj učinkovito, kajti v razredu se učenci včasih ne poslušajo in pogosto podobna Slika 4. Prikazuje primer avtomatske analize zabavne vprašanja postavijo večkrat. Še ena velik prednost tovrstnega ankete sestavljene v Microsoft Forms pouka pa je seveda ta, da si posnetek pouka učenci kadarkoli in kolikokrat se jim zdi potrebno ogledajo ponovno. 3.2.3 Usmerjanje pozornosti učencev 3.2.2 Motivacija in enostavno usvajanje orodij Veliko več veselja do mehaničnega utrjevanja snovi so imeli tudi Učenci so bili za pouk preko Microsoft Teams orodij zelo z učenjem novih besed prek programa Quizlet [3] motivirani, saj smo se raziskovanja lotili sodelovalno in so bili https:/ quizlet.com/496898602/flashcards, kjer sem jih pritegnila ponosni na to, da so pomočniki meni in svojim staršem. Ko so tako, da sem včasih namenoma sestavila jezikovni set z napako. imeli gesla so tudi sami ustanovili svoje skupinice (npr. 6.a Torej tako, da je program slovenske besede bral kot angleške in Punce) in se prek njih družili, si pomagali pri snovi in učenju so jezikovni set zato ponovili večkrat kot bi ga sicer, saj so se ob uporabe spletnih orodij. Veliko jim je pomenilo, kadar sem jih njem nasmejali. potrebovala, da so testirali kakšno funkcijo, ki sem se je naučila. Tako je motivacijo za utrjevanje, preverjanje znanja, Bili so zelo spretni in pomagali tudi meni, saj sami uporabljajo sodelovanje pri pouku in podobno mnogo lažje spodbuditi kot pri socialna omrežja, ki delujejo na podoben princip. Na tak način rednem pouku. Pri rednem pouku je namreč bistvo socializacija smo se naučili uporabljati obrazce in ankete v Microsoft v Forms, med učenci in ta pogosto težko tekmuje s snovjo, ki jo klepet, video klice, Microsoft Planer, OneNote zvezek in obravnavamo pri pouku. Pri rabi spletnih orodij pa učenci podobno. vseeno lahko delijo mnenja in sodelujejo, vendar jih pri tem ne V sklopu razrednih ur smo reševali kvize, ki se popravijo sami. motijo dejavniki skupinskega pouka. V mislih sem imela seveda pripravljanje na morebitno ocenjevanje, a učenci so kljub temu radi sodelovali. Sami so namreč prispevali zabavna vprašanja in se veselili, če sem 4 PREDNOSTI UPORABE DIGITALNIH uporabila prav njihov predlog. Slika 3 prikazuje primer ORODIJ PRI POUKU vprašanja razrednega kviza. Poleg že zgoraj opisanih prednosti uporabe digitalnih orodij (motivacija, pozornost, disciplina, aktivno sodelovanje) je vredno razmisliti o prednostih nekaterih oblik pouka pred klasičnimi. Nekatere bi lahko dopolnile, druge pa povsem nadomestile klasičen način pouka. 4.1 Dopolnilni pouk Dopolnilni pouk [4] v šoli je običajno organiziran po koncu pouka, enkrat tedensko. Namenjen je učencem, ki težje sledijo snovi pri pouku. Običajno je organiziran za heterogeno skupino učencev, katerih potrebe po pomoči se lahko zelo razlikujejo. Slika 3. Prikazuje primer zabavnega kviza narejenega v Poleg tega so učenci po zaključenih sedmih urah pouka pogosto preutrujeni, da bi ga lahko dobro izkoristili. Zato bi bilo veliko Microsoft Forms, ki se popravi sam bolj smiselno, da bi dopolnilni pouk potekal prek Podobno sodelovalno smo prek Microsoft Forms izvedli tudi videokonference v popoldanskih ali večernih urah (učenci in glasovanje za razredne naslove na koncu leta in sestavljali učitelji bi se uskladili), vsebino in trajanje posameznega srečanja vsebino razrednih ur v OneNote Class Note zvezku. Slika 4 pa bi učenci določili skupaj z učiteljem. prikazuje zbrane rezultate glasovanja za naziv »glavica razreda«. 4.2 Dodatni pouk in interesne dejavnosti Dodatni pouk [5] je v šoli organiziran podobno kot dopolnili pouk, le da je namenjen učencem, ki poleg rednega pouka želijo dodaten izzive ali pa se pripravljajo na tekmovanja. Le ta bi bil veliko bolj učinkovit, če bi gradivo učenci in učitelji lahko soustvarjali v OneNote Class Notebook-u in se občasno dobili v šoli ali prek videokonference in se o ustvarjenjem pogovorili v 513 živo. Tako bi pokrili bolj široko paleto interesov, bili pri delu bolj 5 ZAKLJUČEK motivirani, poglobljeni, ustvarjalni in učinkoviti. Največja ovira pri znanju uporabe digitalnih kompetenc je 4.3 Premagovanje specifičnih učnih težav nepoznavanje široke palete orodij in neznanje njihove uporabe. Čeprav imajo mnogi zadržke pri usvajanju znanja uporabe Učitelji DSP (dodatna strokovna pomoč) so nenadomestljiva orodij, obstajajo preizkušeno dobre prakse, prek katerih se lahko podpora učencem, ki imajo specifične učne težave. [6] Veliko hitro izobrazi širok prerez uporabnikov. Z znanjem uporabe teh njihove strokovne pomoči žal odpade na ročno prilagajanje orodij pa se znanje usvaja hitreje in na bolj učinkovite načine. gradiv posameznim učencem. Ta del njihove pomoči bi lahko v Ker nas je obdobje korone prisililo v raziskovanje boljših celoti prevzel. One Note Class Notebook. ki ima vgrajeno načinov podajanja in usvajanja snovi, bi bilo potrebno z dodano funkcijo potopnega bralnika. Ta omogoča prilagajanje pisnih vrednostjo nadaljevati in ponekod v celoti nadomestiti manj gradiv glede na specifične učne težave učenca. Poleg učinkovite načine komunikacije med šolskimi strokovnimi oblikovanja besedil omogoča tudi glasno branje zapisanega. delavci, učenci in starši. Namesto da učitelj DSP učencu pomaga prilagajati gradivo bi se učenci lahko naučili bralnik uporabiti sam. Učenci z bralno- napisovalnimi težavami se sicer učijo z njimi spoprijemati, VIRI vendar te težave ne izginejo in bi jim poznavanje tega orodja vse [1] Wyman, P., 2020 The Future of Learning, življenje koristila. Učitelji DSP pa bi imeli več časa, da bi z https:/ www.howtolearn.com/2020/01/the-future-of- učenci vadili specifične tehnike usvajanja znanja. learning/ (uporabljeno, 24. 8. 2020) 4.4 Individualne govorilne ure [2] IT Pros Management, Microsoft Teams, 2020, https://support.office.com/en-us/article/join-a-teams- Učitelji v OŠ imamo tedenske dopoldanske in mesečne meeting-078e9868-f1aa-4414-8bb9-ee88e9236ee4 popoldanske govorilne ure. Čeprav se šola trudi, so oboje so za (uporabljeno, 24. 8. 2020) starše pogosto ob neugodnem času. Dopoldanskih se namreč [3] Karanjac, B., 2020 The Elephant's Nose starši udeležijo takrat, kadar pride do težav in bi bilo do mesečnih https:/ quizlet.com/496898602/flashcards popoldanskih nesmiselno počakati. Za starše to pogosto pomeni, (uporabljeno, 24. 8. 2020) da se morajo za odsotnost dogovarjati z delodajalcem, za učitelje [4] Zakon o organizaciji in financiranju vzgoje in pa je organizacijsko to lahko težko izvedljivo (ni proste učilnice izobraževanje, 24. Člen, ob tisti uri, nepredvidene zadolžitve ipd.). Dopoldanske http://pisrs.si/Pis.web/pregledPredpisa?id=ZAKO445# tedenske individualne govorilne ure bi bilo pametno povsem (uporabljeno, 24. 8. 2020) nadomestiti z videokonferencam, ki bi po predhodnem dogovoru [5] Zakon o organizaciji in financiranju vzgoje in prek elektronske pošte ali chat (klepet) sporočil potekale prek izobraževanje, 23. Člen, video klicev. http://pisrs.si/Pis.web/pregledPredpisa?id=ZAKO445# (uporabljeno, 24. 8. 2020) [6] Zakon o organizaciji in financiranju vzgoje in izobraževanje, 12. Člen, http://pisrs.si/Pis.web/pregledPredpisa?id=ZAKO445# (uporabljeno, 24. 8. 2020) 514 Spletna učilnica pri športni vzgoji Online classroom for physical education Viktor Klampfer Gimnazija Bežigrad Ljubljanska 28 1351 Brezovica pri Ljubljani, Slovenija viktor.klampfer@gimb.org POVZETEK When I decided on an online classroom for sports education, there was a doubt about the reasonableness of it. Concerns such Ko sem se odločal za spletno učilnico pri športni vzgoji, se je as "but now they will still need a computer in sports education porajal dvom v smiselnost le-te. Pomisleki kot so »a sedaj bodo and sit at a desk instead of children being active." However, more pa še pri športni vzgoji potrebovali računalnik in sedeli za mizo in-depth thinking led me to decide on it anyway. The classroom namesto da bi bili otroci aktivni«. Vendar pa je bolj poglobljeno is not intended for use by students on a daily basis. The purpose razmišljanje pripeljalo do tega, da sem se vseeno odločil zanjo. is that when students are in a dilemma about the technique of Učilnica ni namenjena temu, da jo dijaki uporabljajo certain elements in sports that we have in sports education at the vsakodnevno. Namenjena je temu, da ko so dijaki v dilemi glede Bežigrad high school, they can look at these elements. It is also same tehnike določenih elementov pri športih, si lahko pogledajo intended for the submission of seminar papers, research papers te elemente. Prav tako je namenjena oddaji seminarskih nalog, and reports of sports education. But I also use it myself, because raziskovalnih nalog in poročil v okviru športne vzgoje. the selection of sports at the Bežigrad High School is such that Izkoristim pa jo tudi sam saj je izbor športov na Gimnaziji we are not able to perform quality demonstrations in all sports, Bežigrad velik. Ker nismo sposobni v vseh športih izvajati and so we can use these contents to demonstrate the proper kvalitetnih demonstracij lahko te vsebine uporabimo za prikaz technique of certain elements in different sports. These are E- pravilne tehnike določenih elementov pri različnih športih. To so materials in the form of pictures, videos, graphics, cinematics E-gradiva v obliki slik, video posnetkov, grafik, kinematik in and the like, which would allow us even better quality sports podobnega, kar bi nam omogočilo še kvalitetnejšo športno education and also teaching sports that we were not familiar with vzgojo. Obenem pa tudi poučevanje športov, s katerimi nismo during our studies or which were a problem for us and later in bili seznanjeni med študijem ali pa so nam predstavljali težavo in our careers renewed and consolidated, because we did not jih kasneje v karieri nismo obnavljali in utrjevali. Zaradi tega jih include them in our curricula precisely because we were not able nismo vključili v svoje učne načrte, ker jih nismo bili sposobni to demonstrate them. From this point of view, students would demonstrirati. S tega vidika bi tudi dijaki dobili na področjih, kjer also get in areas where the teacher is less technical, je učitelj slabše tehnično podkovan, kakovostno demonstracijo. demonstration quality and insight into the true implementation of Dobili bi vpogled v res pravo izvedbo vseh tehničnih elementov all technical elements in various sports. I also think that in this pri različnih športih. Prav tako mislim, da bi se na ta način paleta way the range of sports offered by schools to their pupils and športov, ki jih šole ponujajo svojim učencev oziroma dijakom, students would be greatly increased and at the same time the precej povečala. Dvignila bi kakovost demonstracij pri urah quality of the demonstrations during the physical education športne vzgoje. Prav tako bi lahko učitelji sprotno preverjali classes would be raised. Teachers could also keep checking their svoje znanje v različnih športih in sledili razvoju tehnike v skills in different sports and keep up with the development of posameznih športih. Seznanjali bi se tudi v smislu taktične techniques in individual sports, thus learning about the tactical priprave ekip, ki jih vodijo na tekmovanja. Zato je po mojem preparation of teams leading them to competitions. So in my mnenju spletna učilnica pri športni vzgoji smotrna in bi vsekakor opinion online classroom at physical education, will be necessary pripomogla h kvalitetnejšemu pouku športne vzgoje. for better education. KLJUČNE BESEDE KEYWORDS Šport, športna vzgoja, e-gradiva, spletna učilnica Sports, physical education, e-materials, online classroom ABSTRACT 1 UVOD Spletna učilnica pri športni vzgoji. Kaj? Kaj pa naj bi tam bilo? Permission to make digital or hard copies of part or all of this work for personal or Ima to sploh smisel? classroom use is granted without fee provided that copies are not made or distributed To so vprašanja, ki se seveda porajajo odločitvi ali je pri for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must športni vzgoji res smiselno imeti spletno učilnico. Po premisleku be honored. For all other uses, contact the owner/author(s). in tehtanju razlogov za ali proti, pa sem se na podlagi argumentov Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia odločil, da si naredim spletno učilnico. Pri postavitvi učilnice © 2020 Copyright held by the owner/author(s). 515 seveda ne gre brez izobraževanja. Če sem želel pripraviti spletno pa sem za pomoč prosil študente fakultete za šport, ki so bili pri učilnico sem se seveda moral naučiti kako se spletna učilnica nas na praktičnem usposabljanju. Skozi leta se je nabralo kar kvalitetno naredi in uporablja. In tako sem šel na izobraževanje. nekaj gradiva, ki pa je interne narave za poučevanje športne Na šoli imamo kar nekaj učiteljev, ki odlično obvladajo to vzgoje na Gimnaziji Bežigrad. Takrat se je na spletnih straneh področje, bili pa so pripravljeni to deliti z nami in organizirali dobilo še vse gradivo. Danes je veliko gradiva plačljivega, tudi izobraževanje na to temo. Tako sem se udeležil nekaj delavnic. glede uporabe spletnega gradiva se stvari lahko zapletejo, saj so Po začetnem zagonu in informacijah, pa je seveda lahko avtorsko zaščitena. Sam sem si pripravil gradiva iz odbojke najpomembneje, da zadevo uporabljaš, če ne znanje izgine nekje [1], [5], košarke, nogometa, badmintona [3], gimnastike [7], v oblakih in ves trud je bil zaman. In tako sem ugotovil kaj vse namiznega tenisa [4], atletike, fitnesa [8], v novejšem času, ko pa ponuja spletna učilnica. Veliko stvari je bilo potrebno prilagoditi, sem začel s predstavitvami osnovnih motoričnih sposobnosti, da sem lahko materiale, ki sem jih imel na voljo uspešno uporabil dijakom pripravljam še ta gradiva. To so gradiva iz ravnotežja, v spletni učilnici. preciznosti, koordinacije, hitrosti, moči, gibljivosti. Hkrati pa Že kar nekajkrat sem se znašel pred izzivom, kako pokazati tudi različne vaje za osnovno telesno pripravo športnikov ali oziroma demonstrirati elemente v kakšni športni panogi, o kateri dijakov, ki bi želeli začeti ali nadaljevati z vadbo. imam slabše znanje ali pa ga celo sploh ne znam, a bi dijaki radi ta šport igrali. Na fakulteti za šport tudi ni možno osvojiti znanja 2.1 Športna gradiva iz vseh športov, ki bi jih dijaki radi spoznali ali jih celo igrali pri E-gradiva, ki so povezana s športom, so sestavljena iz osnovnih urah redne športne vzgoje. Normalno je tudi, da smo učitelji v podatkov o športu, opremi, ki jo potrebujemo za ta šport, pravili, nekaterih športih, pa čeprav smo jih imeli na predmetniku na ki veljajo v tem športu, tehničnih in taktičnih elementih tega fakulteti za šport, slabše strokovno podkovani, ker nam ti športi športa in ne nazadnje tudi z vprašanji ali kvizom na temo niso blizu. Za izpit smo opravili obvezne vaje, opravili teoretični določenega športa. V gradivu so razne slike ali animacije, ki so in praktični del izpita in tu se z nekaterimi športi zgodba lahko vezane na tehnične elemente tega športa, slike določenih konča. Potem pa se po dvajsetih letih soočiš na šoli z oddelkom pomembnih elementov, na katere je potrebno posebej paziti. dijakov, ki bi rad spoznal ali igral ta šport. Nastane problem, ki Lahko pa so tudi razni filmčki, ki govorijo o metodiki učenja ga moraš rešiti, če želiš dijakom ponuditi kvaliteten pouk športne določenih elementov. To posebej velja za osnovne motorične vzgoje. Ko nekega športa deset ali dvajset let ne demonstriraš, ga sposobnosti, kjer za določene elemente učitelj potrebuje ali niti ne spremljaš, se ne seznanjaš z novimi pravili, torej si lahko veliko časa in želje, da se jih nauči, zato bi bili dobrodošli v veliki zagati. Še posebej morda to velja za srednjo šolo, kjer filmčki, ki so dosegljivi na raznih omrežjih in spletnih straneh, težko pred dijaki nekaj opraviš na »blef«. Na fakulteti za šport da dijakom pokaže tehniko in izvedbo določenih vaj, hkrati pa tudi ne morejo ponuditi vseh možnih športov, zato ponujajo tudi metodiko vaj, da se te elemente naučijo. Uporaba osnovne športe, pa tudi ti zadnje čase, če izhajam iz informacij, računalnika pri športni vzgoji dejansko lahko pomaga učitelju. ki jih dobim od študentov, ki prihajajo k meni na obvezno prakso, Tako je recimo aerobika [2], oziroma sestavljanje raznih niso več v takem obsegu, kot so bili v času mojega študija v koreografij in sklopov vaj pri aerobiki, lahko precej lažja devetdesetih letih prejšnjega tisočletja. Verjamem, da se je s oziroma omogoča tudi učitelju s poškodbo ali kako drugače povečevanjem vpisa v prvi letnik fakultete število študentov handikapiranemu učitelju, da poučuje takšne športe oziroma toliko povečalo, da profesor določenega praktičnega predmeta elemente določenega športa, pa čeprav jih sam ne zna ali jih ne potrebuje kar nekaj asistentov, da lahko opravijo obvezne vaje zmore več narediti, je pa usposobljen za asistenco ali opozarjanje pri tem predmetu, hkrati pa se tudi število ur praktičnega dela na napake oziroma metodične postopke pri posameznih zmanjša, da bi lahko profesor z asistenti uspel izvesti praktični elementih določenega športa. del predmeta za vse študente. Jasno je, da ker smo si ljudje Vsekakor bi lahko to pripomoglo k večji kakovosti ur športne različni, se tudi pri obveznih vajah dogaja, da asistenti bolj vzgoje, prav tako pa tudi k večji pestrosti športne vzgoje v šolah, poudarjajo določene elemente tehnike in taktike, na izpitu pa saj se pogostokrat zgodi, da so učitelji športne vzgoje pri svojem profesor zahteva poudarek na drugih tehničnih in taktičnih delu postali tako rekoč rutinerji. Kar pomeni, da so po začetni elementih. V drugih državah imajo tudi na študiju športne vzgoje vnemi zapadli v krog ustaljenih navad in metod poučevanja, ki vzporedno še en predmet, ki zagotovi širše znanje in večjo se jim zdi najboljši. Prav zaradi tega ne iščejo možnosti za možnost zaposlovanja v starejših letih, saj je jasno, da učitelj pri raznovrstnost, posebej še ne na področjih, kjer so malo manj šestdesetih letih najbrž ni več zmožen v celoti opraviti usposobljeni in kjer imajo manjši interes, ker pač teh športov ne praktičnega dela demonstracij pri določenih osnovnih športih, pa obvladajo ali pa z njimi v času svojega študija sploh niso bili tudi različne poškodbe so lahko ovira za takšne demonstracije. seznanjeni. Tudi tehnika in taktika pri posameznem športu se razvijata in napredujeta in učiteljem je težko spremljati razvoj 2 SPLETNA UČILNICA vsega. Zato menim, da bi ponudba gradiv, ki bi bila na voljo učiteljem, najverjetneje popestrila športno vzgojo dijakom v Zato sem si že pred nekaj leti sam pripravil nekatera e-gradiva, mnogih šolah, hkrati naredila ure bolj zanimive in pestre. Po ki so mi bila že takrat v pomoč in so mi, moram priznati, iz leta drugi strani bi olajšala delo učiteljem športne vzgoje in jim v leto bolj. Nekatere tehnične elemente sem že takrat našel na pokazala, da lahko s pomočjo teh gradiv poučujejo tudi športe, v spletnih straneh, nekatere pa sem posnel sam. Takrat še s katerih so slabše tehnično in taktično podkovani ali pa jih celo ne spletnimi kamerami in slabe kakovosti. Prosil sem dijake, ki so poznajo, saj bi se jih učili skupaj z učenci ali dijaki. trenirali določen šport, če mi pomagajo pri demonstraciji, prosil nekatere kolege, ki so bili vešči v določenem športu, da mi pomagajo pri demonstraciji, ali pa sem se posnel sam. Nekajkrat 516 2.2 Moja spletna učilnica [4] Letts, G., May 2018, The Forehand Counterhit. Že nekaj let pri svojem delu uporabljam tudi svojo spletno DOI=https://www.liveabout.com/table-tennis-basic- učilnico, kjer imajo dijaki na voljo raznolika gradiva v zvezi s strokes-3173502, športi, ki jih izvajamo v sklopu pouka športne vzgoje na [5] Marion, A., 2018, PhD. Adrian Honish, MSc Sport Gimnaziji Bežigrad. Biomechanics Lab University of Manitoba , An Spletno učilnico uporabljam tudi pri teoretičnih vsebinah pri Analysis of the Volleyball Jump Serve. športni vzgoji. Tako morajo dijaki oddajati razne seminarske DOI=http://umanitoba.ca/faculties/kinrec/hlhpri/medi naloge v zvezi s športno vzgojo, predvsem ko imam pouk v a/vb_jump_serve.pdf, fitnesu, obdelamo nekaj teoretičnih vsebin kot so: športna [6] Webster, M., 2018, Sports & games, [online]. prehrana [9], anatomija in fiziologija mišic, zgodovinski pregled DOI=http://www.visualdictionaryonline.com/sports- razvoja fitnesa [11], športne poškodbe [14], doping [15] in games/ball-sports/volleyball/techniques_1.php, njegov vpliv na telo in šport, pa tudi nekaj o osnovah gibanja in [7] Športna vzgoja, 2018, Gimnastika, osnovna šola osnovnih motoričnih sposobnostih [13]. Dijaki imajo v spletni Poljane. učilnici na voljo osnovne informacije o vseh osnovnih športih, ki DOI=http://www2.arnes.si/~amrak3/SPORTNA%20 jih izvajamo pri pouku, na kriterije, ki veljajo za oceno iz VZGOJA/gimnastika/gimnastika.htm, posameznega športa, o tehniki in taktiki posameznega športa. [8] Luketina, N., september 2008, magistersko delo, Na voljo imajo tudi nekatere zanimivosti iz sveta športa: A naliza možnosti trženja freestyler naprave in najboljši košarkarji, nogometaši, nosilci olimpijskih medalj z freestyler vadbenega koncepta na slovenskem trgu. zimskih in letnih olimpijskih iger, svetovnimi rekordi v atletiki, DOI=http://www.cek.ef.uni- pa tudi nekaj smešnic iz sveta športa, ki so se zgodile na raznih lj.si/magister/luketina163-B.pdf tekmovanjih. Na koncu jim je na voljo tudi kviz v zvezi s [9] N. Hojč, Fat controversial nutrient, Maščobe kontroverzno hranilo, 2012. DOI= športom, ki ga spoznavajo ali dopolnjujejo svoje znanje o njem. https://www.the-nutrition.com/single- clanek/Mascobe-kontroverzno-hranilo/71/filtriraj- 3 ZAKLJUČEK po/datum/razvrstitev/padajoce/cilj/Sport/stran/2 [10] N. Hojč, A. Đorđevski, Carbohydrates are the best Vsekakor menim, da mi je spletna učilnica omogočila da lahko fuel, ogljikovi hidrati najboljše gorivo, 2012. DOI= pri športni vzgoji obravnavamo tudi teoretične vsebine in se https://www.the-nutrition.com/single- dijaki seznanjajo tudi z informacijami, ki jih sicer ne bi dobili, clanek/Ogljikovi-hidrati---najboljse- prav tako pa lahko s posnetki, ki so na voljo na spletnih straneh gorivo/67/filtriraj- dobijo kvalitetno demonstracijo. Izkazala pa se je tudi v obdobju, po/datum/razvrstitev/padajoce/cilj/Sport/stran/2 [11] Krejač K. 2015. Fitness danes in jutri - vizija razvoja. ko je pouk zaradi korona virusa odpadel in smo dejansko lahko [internet]. [citirano 28.10.2019]. DOI= preko spletne učilnice opravljali pouk športne vzgoje. Dijaki so https:/ www.fsp.uni- lahko uporabljali gradiva, ki so bila v spletni učilnici, lahko so lj.si/COBISS/Diplome/Diploma22110012KrejacKlem oddajali poročila in naloge, ki so jih morali narediti doma. Lahko en.pdf so reševali pripravljeni kviz. Tudi teoretično ocenjevanje bi se [12] Seznam mišic človeškega telesa. [internet]. [citirano lahko izvedlo v kolikor bi bilo to potrebno. Skratka spletna 27. 11. 2019]. DOI= učilnica je uporabna tudi pri športni vzgoji, vsekakor pa ne sme https://sl.wikipedia.org/wiki/Seznam_mi%C5%A1ic_ nadomestiti telesne aktivnosti ampak jo spodbujati. %C4%8Dlove%C5%A1kega_telesa [13] Dovč, K. D. 2013. Osnovne motorične sposobnosti in kako jih razvijamo. [internet]. [citirano 29.11.2019]. LITERATURA DOI=http://www.o- jozmos.lj.edus.si/files/2013/05/OSNOVNE_MOTORI [1] Meusel, A., September 2016, Komplextraining: %C4%8CNE_SPOSOBNOSTI_IN_KAKO_JIH_RA Aufschlag und Annahme (volleyballtraining kompakt) ZVIJAMO.docx Taschenbuch. DOI=http://aufschlag-annahme.de/, [14] Snoj, Ž. 2019. Najpogostejše športne poškodbe. [2] Zagrajšek, J. 2018, center sokol Vič, vaje Špela Jakša, [citirano 10.10.2019]. DOI=https://www.nasa- V aje z žogo. lekarna.si/clanki/clanek/najpogostejse-sportne- DOI=https://www.aktivni.si/fitnes/vaje/video-vaje-z- poskodbe/ zogo-fitball/ [15] Kaj je doping. 2017. [internet]. [citirano 10.10.2019]. DOI=http://www.sloado.si/kategorija/sportniki- [3] Everything About Badminton, November 2, 2014. krsitve-kaj-je-doping DOI=https://everythingaboutbadminton.wordpress.co m/2014/11/02/how-to-play-net-shot/, 517 Vodenje aktiva med šolanjem na daljavo Team leadership during distance learning Jožica Knez Osnovna šola Stična Cesta občine Hirschaid 1 1295 Ivančna Gorica, Slovenija jozica.knez@os-sticna.si POVZETEK posameznega učitelja usmeri v izboljšanje lastnega dela in k medsebojnemu sodelovanju. Članek opisuje vodenje sedemčlanskega šolskega strokovnega aktiva matematikov na OŠ v času šolanja na domu med 16. 3. 2020 in 25. 5. 2020. Ker gre za primer šole z matično šolo in 2 STROKOVNI AKTIV dvema podružnicama, večino članov aktiva dela na vsaj dveh lokacijah, zato je bilo potrebno veliko spretnosti pri usklajevanju Strokovni aktiv šole obravnava problematiko predmeta oziroma in prilagajanju na nove okoliščine. Članek torej opisuje, kako predmetnega področja, usklajuje merila za preverjanje in smo delovni načrt iz začetka šolskega leta hitro in uspešno ocenjevanje, daje učiteljskemu zboru predloge za izboljšanje prilagodili delu v času pandemije. Opisuje predvsem učinkovito vzgojno-izobraževalnega oziroma študijskega dela, obravnava vodenje zahtevnega aktiva pod novimi delovnimi pogoji. pripombe staršev, učencev, vajencev, dijakov in študentov višjih šol ter opravlja druge strokovne naloge, določene z letnim KLJUČNE BESEDE delovnim načrtom. [1] Strokovni aktiv je skupina učiteljev istega predmeta. Delovati Strokovni aktiv, MS Teams, matematični aktiv, vodenje morajo enotno ter sodelovati na različnih področjih svojega dela: ABSTRACT • oblikujejo in usklajujejo učiteljeve letne priprave, • načrtujejo učne ure, The paper focuses on leading a professional mathematical team • spoznavajo standarde znanja, at a primary school during the period of distance learning from • določajo merila in kriterije za ocenjevanje, 16th March to 25th May, 2020. The majority of 7 team members • predstavljajo in uporabljajo nove didaktične pristope, work at two branch schools, so leading the team demanded • načrtujejo medpredmetne povezave, skilful compromising and swift adapting to the unexpected • obravnavajo pritožbe staršev in učencev, working conditions. Therefore, the paper describes how the • sodelujejo z aktivi po vertikali in načrtujejo različne original working plan from the beginning of the school year was dejavnosti, successfully adapted to working through the pandemic. It focuses • razvijajo in nadgrajujejo študijsko delo, on successful team leadership under new working conditions. • izvajajo projekte, načrtujejo dneve dejavnosti, organizirajo delavnice. KEYWORDS Professional team, Microsoft Office Teams, mathematical team, 3 VODJA AKTIVA leadership Vodja aktiva je določen s strani ravnatelja ali pa je za vlogo določen znotraj posameznega aktiva. V poročilu o pilotni izvedbi 1 UVOD o vodenju aktiva so mnenja, da imajo vodje aktivov zelo različno Sodobni čas od nas zahteva, da se vsi učitelji prilagajamo, vlogo in opravljajo široko paleto nalog, ki se od zavoda do sledimo spremembam, da se dobro poznamo in dobro zavoda razlikujejo, odvisno od njegove ravni, vrste, velikosti, sodelujemo. Sodelovanje učiteljev je zagotovo prvi pogoj za kulture, zgodovine in stila vodenja. Posamezni udeleženci so odlično delo. Vedno moramo gledati, da delamo kakovostno in omenili, da opravljajo (le) tri naloge, nekateri so jih našteli več da to pomeni, da spodbujamo znanje, nenehno učenje in kot dvajset. Potrebo po razjasnitvi nalog pojasnjujejo refleksije izobraževanje, izmenjavo izkušenj, odgovornost, upoštevanje udeležencev, saj so omenili, da od učenja v programu pričakujejo predpisov itd. S strokovnimi aktivi ima šola možnost, da predvsem razjasnitev svoje vloge in nalog, na podlagi česar sklepamo, da vloga in naloge na ravni zavodov niso razjasnjene. [2] Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full 4 VODENJE AKTIVA MATEMATIKE citation on the first page. Copyrights for third-party components of this work must V letošnjem letu sem bila prvič vodja aktiva matematike. Na naši be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia šoli poučuje matematiko sedem učiteljev. Poučujemo na matični © 2020 Copyright held by the owner/author(s). šoli in še na dveh podružničnih devetletnih šolah. Nekateri 518 sodelavci so stalno samo na eni lokaciji, tri pa se vozimo tudi na in je vmes prekinjalo, kar je pomenilo, da smo morali biti še podružnico. To pomeni, da nam za medsebojno komunikacijo ni toliko bolj dosledni pri poslušanju sodelavcev. preostalo drugega, da smo se velikokrat srečali preko elektronske pošte. Za posamezne ure pouka smo se morali dogovarjati sproti, 5.3.1 Tedenski plan največkrat na začetku tedna. Snov pri manjših učnih skupinah, Za vsak prihodnji teden sem predstavila plan dela (slika 1). Ob kjer je bil potem prisoten tretji učitelj, smo morali uskladiti, da tem je bilo potrebno slediti snovi vseh razredov, tudi če nisi delal so učenci iz dveh različnih razredov lahko delali isto snov. priprave za dotični razred in hkrati smiselno določiti, ali kje Približno petkrat na leto smo se srečali tudi “v živo”. Takrat smo dodamo kakšno uro utrjevanja, morda potrebujemo preverjanje se po navadi dogovarjali o datumih pisnih preizkusov in njihovi znanja. Na tem mestu smo bili zelo v kontaktu z vodstvom, da vsebini, velikokrat tudi o organizaciji tekmovanj Kenguru in smo vedeli, če je potrebno načrtovati samo 3 ure pouka (zaradi ostalih. Na začetku šolskega leta pa smo seveda določili cilje načrtovanih dni dejavnosti). Ker so imeli vsi učenci enoten urnik letnega delovnega načrta (LDN) in razpored snovi po urah, ki na vseh treh devetletnih šolah, pomeni, da so imeli vsi isti dan nam pomaga pri lažjem sledenju obravnavane snovi. V mesecu iste predmete. V realni učni situaciji to seveda ni izvedljivo, v marcu 2020 pa se je vse obrnilo na glavo. virtualnem/elektronskem svetu pa. Pravzaprav nam je bilo to zelo v pomoč pri organizaciji dela. 5 VODENJE AKTIVA NA DALJAVO 5.1 Elektronska pošta Ko je bilo jasno, da se s ponedeljkom, 16. 3., začne šolanje na daljavo, smo se v aktivu dogovorili, da bomo snov podajali enotno, v vseh razredih, na vseh treh devetletnih osnovnih šolah, to je na matični šoli OŠ Stična, PŠ Višnja Gora in PŠ Zagradec. Vse priprave bodo na šolski spletni strani prosto dostopne za učence oziroma starše. Priprave bomo delali v parih. Naša komunikacija se je najprej preselila izključno na elektronsko Slika 1. Prikazan je plan dela za 9. teden šolanja na pošto. Glede na ozadje pošte je to pomenilo, da je bilo najmanj daljavo šest odgovorov, se pravi, novih e-mailov na eno temo. Ampak v Včasih smo zaradi lažje organizacije in preglednosti dela prvem tednu ni bilo druge možnosti. Je pa to vse skupaj načrtovali kakšno uro tudi že za teden kasneje. Še vedno smo si pomenilo, da smo se vsak dan prebijali skozi goro besedila, dopuščali možnost popravkov. Dovolili smo si, da upoštevamo mnenj, idej … Pri uporabi elektronske pošte se pisec počuti, kot mnenja učencev ali staršev, od katerih smo dobivali povratne da bi govoril. Zato je več možnosti, da pride do nesporazumov informacije o delu učencev doma. zaradi slovničnih napak ter napačne uporabe besed. [3] Elektronska pošta, vemo, zna biti velikokrat neosebna, saj smo si ljudje različni in potrebujemo tudi slušne informacije. Tega pa 5.3.2 Srečanja v živo nam je že po prvem tednu primanjkovalo. Več je bilo tudi Enkrat tedensko ob večernih urah smo izvedli sestanek aktiva. komunikacije ena na ena preko telefona. Vseeno nam je uspelo Jaz sem v začetku tedna v aplikaciji organizirala dogodek in postaviti pravi načrt za obdelavo snovi. zapisala cilje sestanka (slika 2). Sodelavci so potem imeli čas, da potrdijo udeležbo. Tako sem vedela, da so objavo videli in da si 5.2 Office 365 in MS Teams bodo takrat vzeli čas za naš aktiv. V drugem tednu šolanja na daljavo smo se odločili, da naše dejavnosti prestavimo na orodje Microsoft Teams. Gesla za Oblak365 smo že imeli in uporabljali. Oblak365 povezuje Arnes AAI s storitvami Microsoft Office 365. Ena od možnosti Microsoft Officea je tudi MS Teams. 5.3 Delo v MS Teams Ko smo odkrili oziroma odkrivali MS Teams, so se nam odpirala obzorja. Pri tem smo vsak dan odkrili nove funkcije, nove lastnosti oziroma uporabnosti tega orodja. Predvsem pa to, da smo se lahko naenkrat vsi slišali in videli ter se kulturno pogovorili o svojem delu. Pogovor v takem okolju seveda pomeni, da je bilo potrebno vzpostaviti nekaj novih/starih pravil. Pogovor je moral potekati po bontonu. Ko nekdo govori, ostali Slika 2. Objava sestanka z dnevnim redom in potrditev ne skačemo v besedo. Počakamo, da dokonča s poročanjem, in nekaterih članov aktiva. nato lahko naslednji pove svoje mnenje. Čim manj skakanja v besedo, čim manj prekinjanja drug drugega in seveda poslušanje. Pri sestankih je bilo pomembno, da se za vsako tematiko Pri tem smo bili deležni tudi morda slabših internetnih povezav dogovorimo. Vsak je imel možnost povedati svoje dileme in pričakovanja. Obvezno smo si poročali odzive svojih učencev. 519 Zavedali smo se, da so si učenci različni. V primerih, ko so bile priprave pretežke ali predolge, smo sklenili, da zmanjšamo število nalog. V času šolanja od doma so se pokazale tudi raznorazne stiske; tudi za to smo poskušali poskrbeti. Pomembno je, da si zaupamo, da si lahko povemo, da lahko izrazimo svoje dvome, skrbi in da to nekako konstruktivno prebrodimo skupaj. Kot pravi psiholog Musek Lešnik: »Sodelujte s kolegi, pomagajte si, delite dobre prakse, delite informacije; nobena sramota ni, če česa ne veste, ne znate, ne razumete – ogromno učiteljev se ta trenutek šele uči plavati v vodi, ki se ji reče izobraževanje na daljavo.« [4] 5.3.3 Pisanje in objavljanje zapisnikov Kot vodja aktiva je moja naloga, da obveščam ravnatelja o naših dogovorih, problemih, sklepih … zato sem po vsakem sestanku Slika 4. Razporeditev kanalov v aplikaciji MS Teams. še zapisala naše sklepe, jih naprej objavila v MS Teams, kjer smo si izoblikovali mapo v kanalu splošno (general) z imenom V vsakem kanalu so bile priprave, ki so bile shranjene na ZAPISNIK (slika 3). Tam so ostali učitelji aktiva prebrali dogovorjeno ime (slika 5). Najprej razred, potem zaporedna ura zapisano in mi pomagali oblikovati sklepe ter dopisati, če sem in še naslov ure. kaj pozabila. Slika 3. Objavljeni zapisniki v aplikaciji. Slika 5. Priprave v kanalu za 9. razred. Pri vsakem zapisniku se vidi ime zapisnika, kje se nahaja, kdaj je bil nazadnje spremenjen in tudi kdo ga je spreminjal. Zato smo lahko vsi spremljali potek zapisov v dokumentu. 6 ZAKLJUČEK Dokumenta ni bilo potrebno shranjevati na svoj računalnik, kar V času šolanja na daljavo sem pridobila neverjetno veliko novih je dobro z več vidikov: ni nepotrebnih datotek na računalniku, znanj. Med drugim sem se naučila in potrdila spoznanje, kako tudi lažje in bolj aktivno urejanje dokumentov “online” in večja zelo je pomembna komunikacija, pozitivna spodbuda, dobri preglednost samih dokumentov, zbranih na enem mestu. zgledi. Po vrnitvi v šolo smo ohranili delo na MS Teams, kjer smo objavljali uporabne dokumente, zapisnike, poročila, ki smo 5.3.4 Razdelitev kanalov jih morali še dopolniti ali urediti. Menim, da je delo v tem Tekom tednov se je nabralo veliko vseh dokumentov v eni mapi. spletnem orodju kakovostno, učinkovito in predvsem za nas Zato smo se odločili, da bo najboljša organizacija dela, če si za učitelje najenostavneje. vsak razred posebej ustvarimo kanal (mapo) (slika 4). V vsako mapo bomo oddajali dnevne priprave na vpogled sodelavcem. Vsak si jo lahko odpre, komentira, zapiše svoje mnenje kot VIRI komentar. Prednost tega spletnega orodja je, da lahko online [1] Zakon o organizaciji in financiranju vzgoje in spreminjamo dokument, ki se sproti shranjuje. Vsak udeleženec izobraževanje, 64. Člen, vidi, kaj je bilo spremenjeno, kar potrdi ali pa ne. Naše http://pisrs.si/Pis.web/pregledPredpisa?id=ZAKO445# usklajevanje je potekalo hitreje in bolj dinamično. (uporabljeno, 3. 8. 2020) [2] Ažman T. in Zavašnik Arčnik M. 2016. Vodenje strokovnega aktiva [Elektronski vir] : poročilo o pilotni izvedbi programa v šolskem letu 2014/2015, Kranj: Šola za ravnatelje http://solazaravnatelje.si/wp- content/uploads/2012/03/Porocilo_o_pilotni_izvedbi_Vod 520 enje_aktiva_2014_2015_cip.pdf (uporabljeno 16. 08. [4] Musek Lešnik, K. 2020. Človeku prijazno izobraževanje 2020) na daljavo v času koronavirusa, [3] Groznik T. 2007. Učinki komunikacije preko elektronske https://www.abced.si/post/%C4%8Dloveku-prijazno- pošte na delovno uspešnost, 11 http://www.cek.ef.uni- izobra%C5%BEevanje-na-daljavo-v-%C4%8Dasu- lj.si/u_diplome/groznik2653.pdf (uporabljeno 16. 08. koronavirusa (uporabljeno 16. 08. 2020) 2020) 521 Pl@ntNet in XMind pri pouku slovenščine in naravoslovja Pl@ntNet and XMind at Slovene and science classes Martina Kokelj Osnovna šola Antona Martina Slomška Vrhnika Pod Hruševco 33 1360 Vrhnika, Slovenija martina.kokelj@gmail.com POVZETEK Information technology, cross-curricular integration, Slovene, Danes si življenja brez informacijske tehnologije ne znamo science, Pl@ntNet, XMind predstavljati. Pametni telefoni, računalniki, tablice in vsa druga informacijska tehnologija krojijo današnji vsakdan učencev in 1 MEDPREDMETNO POVEZOVANJE tudi nas odraslih. Učenci se v šoli veliko naučijo. Pomembno je, da znanje, ki ga osvojijo pri enem predmetu, uporabijo tudi pri Učni načrti se prenavljajo in posodabljajo in zahtevajo drugem predmetu. Medpredmetno povezovanje je eden od fleksibilnega in inovativnega učitelja, ki postavi v ospredje elementov sodobnega pouka. Na naši šoli smo se odločili, da učenca, ki pri pouku aktivno sodeluje [1]. Zelo pomembno je tudi povežemo pouk slovenščine in naravoslovja. Učenci v 6. razredu povezovanje različnih predmetnih področij. Medpredmetno pri pouku naravoslovja obravnavajo rastline, zato smo povezovanje je celosten didaktični pristop – pomeni horizontalno raziskovali floro v okolici šole. S pomočjo aplikacije Pl@ntNet in vertikalno povezovanje znanj, vsebin in učnih spretnosti [2]. smo identificirali rastline s fotografiranjem s pametnim Medpredmetno zasnovan pouk spodbuja učenca k samostojnosti, telefonom in rastline opisali. Nastale so zanimive fotografije sodelovanju in k aktivni vključenosti v pouk. Raziskave so rastlin in miselni vzorci opisov v programu XMind, ki so jih pokazale, da učenci pri medpredmetnem reševanju učnih situacij učenci v obliki govornega nastopa tudi predstavili. razvijajo interes in motivacijo za učenje ter poglabljajo razumevanje in uporabo znanja, pri čemer dosegajo boljše učne KLJUČNE BESEDE uspehe, kažejo bolj kakovostne medosebne odnose in zavzetost za učenje [2]. Informacijska tehnologija, medpredmetno povezovanje, Tudi na naši šoli se spodbuja medpredmetno povezovanje, slovenščina, naravoslovje, Pl@ntNet, Xmind zato sva se s sodelavko odločili, da medpredmetno poveževa ABSTRACT slovenščino in naravoslovje, pri čemer uporabiva tudi informacijsko tehnologijo. Učencem sva želeli dokazati, da se Today, we cannot imagine life without information technology. sodobnih elektronskih naprav ne uporablja samo za pogovor s Smartphones, computers, tablets and all other information prijateljem ali za igranje igric, ampak nam lahko olajšajo delo, se technology shape today's everyday life of us adults and students z njihovo pomočjo nečesa novega naučimo. V ta namen jih pri as well. Pupils nowadays learn a lot of things at school. It is pouku učimo uporabe različnih informacijskih orodij, aplikacij important that the knowledge they acquire in one subject is used in programov, ki jih bodo lahko uporabili tudi kasneje, v času in another subject as well. Cross-curricular integration is one of študija, službi … the elements of modern teaching. At our school, we have decided to combine the lessons of Slovene and Science. Pupils in 6th grade learn about plants in Science classes, so we decided to 2 NAČRTOVANJE POUKA research the flora around the school. Using the Pl @ ntNet app, we identified plants by taking photos with a smartphone and Učiteljici naravoslovja in slovenščine sva se odločili, da pouk described the plants. Interesting photographs of plants and mind načrtujeva sodobno, medpredmetno in z uporabo informacijske maps of plants descriptions in the XMind program were created, tehnologije. Zavedava se, da je razvoj komunikacijsko- which the students also presented in the form of an oral informacijske tehnologije prinesel nove možnosti za učenje in presentation. poučevanje. Najprej se moramo uporabe sodobne tehnologije in naprednih aplikacij naučiti učitelji, da lahko znanje prenašamo KEYWORDS naprej na učence. Učenci pri pouku naravoslovja v 6. razredu obravnavajo rastline, njihovo zgradbo, razmnoževanje, razvrščanje, njihove prilagoditve … [3]. Permission to make digital or hard copies of part or all of this work for personal or Načrtovali sva drugačen pouk, pouk zunaj učilnice, z uporabo classroom use is granted without fee provided that copies are not made or distributed sodobne informacijske tehnologije in z medpredmetnim for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must povezovanjem slovenščine in naravoslovja, saj se nama zdi be honored. For all other uses, contact the owner/author(s). pomembno, da učenci osvojeno znanje povezujejo. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 522 Na tablice sva naložili aplikacijo Pl@ntNet, na računalnike v par je med svojimi fotografijami izbral najboljšo, najlepšo in jo računalniški učilnici pa program XMind, ki je namenjen prenesel v aplikacijo. Program jim je včasih ponudil več različnih izdelovanju miselnih vzorcev. rešitev. Vemo, da so si nekatere rastline med seboj zelo podobne in se razlikujejo v malenkostih, zato smo fotografije natančno 2.1 Aplikacija Pl@ntNet primerjali, da smo poiskali pravo rastlino. Učenci so dobili Pl@ntNet je aplikacija (glej Slika 1), ki nam omogoča rešitev v latinskem jeziku. Latinsko ime so vpisali v iskalnik in identifikacijo rastlin s fotografiranjem s pametnim telefonom [4]. poiskali slovensko ime za rastlino. Pl@ntNet je velik projekt, saj vse rastline, ki jih fotografiramo, Drugi del naloge je bil opis rastline. Najprej so v zvezek zbirajo znanstveniki po vsem svetu in jih analizirajo. Aplikacija napisali osnutek miselnega vzorca (glej Slika 3). Ponoviti smo nam omogoča identifikacijo rastlin, dreves, trav, iglavcev, morali, katere podatke mora opis rastline vsebovati. Skupaj smo vinskih trt, divjih solat in kaktusov. Aplikacija zna prepoznati ugotovili, da bomo zapisali slovensko in latinsko ime rastline, rastlino po rodu ali družini. Z iskanjem najdemo latinsko ime družino, v katero spada, dele rastline, čas cvetenja, rastišče, rastline, ki ga vnesemo v iskalnik in poiščemo slovensko ime uporabnost in raziskali, ali ima rastlina več različnih rastline. poimenovanj. Pri opisu rastline so si lahko pomagali s spletom ali odšli v knjižnico, kjer so poiskali slikovne ključe za določanje rastlin. Slika 1. Aplikacija Pl@ntNet [5] 2.2 Program XMind XMind je program, ki nam omogoča izdelovanje miselnih vzorcev in je zelo enostaven za uporabo. Izdelamo lahko enostavne miselne vzorce, v katere lahko dodajamo besedilo, slike in različne datoteke. Program nam omogoča uporabo različnih predlog in ozadij [6]. Slika 3. Oblikovanje miselnih vzorcev 2.3 Navodila za delo Ko so učenci v zvezek oblikovali miselni vzorec, smo se preselili v računalniško učilnico. Na računalnikih je že bil Učence sva razdelili v pare. V razredu je enako število dečkov in naložen program XMind. Najprej sva jim pokazali, kako deklic, zato so se naključno postavili v dve koloni, tako da sta program deluje, nato so sami oblikovali (iz zvezka prepisali) bila v paru deklica in deček. Vsak par je dobil svojo tablico. miselni vzorec. Vanj so vstavili svojo fotografijo rastline. Odpravili smo se v naravo v okolici šole. Pozorni so morali biti Ko so vsi opravili vse naloge, so v parih predstavili svojo na floro, predvsem na cvetoče rastline, mahove, lišaje in drevesa. rastlino v obliki govornega nastopa. Učenci so imeli 90 minut časa, da so poiskali različne cvetoče rastline in jih fotografirali. Slika 2 prikazuje učenca, ki fotografirata rastlino. 3 ZAKLJUČEK Medpredmetni pouk zahteva veliko načrtovanja in usklajevanja. Učitelji morajo biti pripravljeni na sodelovanje, poznati cilje, ki jih želijo doseči, in se didaktično usposobiti. Za delo smo porabili sedem šolskih ur. Dve šolski uri smo se zadrževali v naravi, na travniku, kjer so učenci samostojno iskali rastline in jih fotografirali. Dve uri smo porabili v razredu, da so poiskali ime rastline s pomočjo aplikacije Pl@ntNet in oblikovali miselni vzorec opisa rastline v zvezek. Dve šolski uri so s pomočjo programa XMind oblikovali miselne vzorce. Zadnjo šolsko uro pa smo namenili predstavitvi rastlin v obliki govornega nastopa. Na koncu sva opravili spletno anketo, kjer so učenci zapisali svoja mnenja o pouku. Vsi učenci so bili navdušeni, saj so spoznavali svojo okolico, rastline in uporabljali sodobno Slika 2. Fotografiranje rastlin s pomočjo tablice tehnologijo. Pouk je potekal sproščeno in naučili so se veliko Po končanem fotografiranju smo se odpravili v učilnico, kjer novega. Vsi so bili enotnega mnenja, da si želijo več pouka v sva učencem predstavili delovanje aplikacije Pl@ntNet. Vsak 523 obliki medpredmetnega sodelovanja in več pouka, kjer so http://www.didakta.si/doc/revija_didakta_2008_november. aktivno udeleženi v učni proces. pdf Na koncu je pomembno tudi to, da učence naučimo [3] Učni načrt, Naravoslovje. 2011. Ljubljana: Ministrstvo za vseživljenjskih znanj, da bodo znali misliti, da se bodo znali učiti, izobraževanje, znanost in šport, Zavod Republike da bodo znali poiskati informacije in ločiti bistvene informacije Slovenije za šolstvo. Dostopno na naslovu: od nebistvenih … Čaka nas še veliko dela. https://www.gov.si/teme/programi-in-ucni-nacrti-v- osnovni-soli/ [4] PlantNet Plant Identification. Dostopno na naslovu: VIRI IN LITERATURA https://play.google.com/store/apps/details?id=org.plantnet [1] Učni načrt, Slovenščina. 2018. Ljubljana: Ministrstvo za &hl=sl izobraževanje, znanost in šport, Zavod Republike [5] Pl@ntnet. Dostopno na naslovu: Slovenije za šolstvo. Dostopno na naslovu: https:/ www.facebook.com/PlantNetProject/photos/a.4887 https://www.gov.si/teme/programi-in-ucni-nacrti-v- 33651212058/1408347862583961 osnovni-soli/ [6] XMind. Dostopno na naslovu: http://splet2- [2] Sicherl-Kafol, B. 2008. Medpredmetno povezovanje v 0.splet.arnes.si/xmind/ osnovni šoli. Didakta. Dostopno na naslovu: 524 Včeraj za danes in jutri Yesterday for today and tomorrow Metka Kolenc, Alenka Močnik Srednja šola Veno Pilon Ajdovščina Cesta 5. maja 12 5270 Ajdovščina, Slovenija metka.kolenc@ss-venopilon.si, alenka.mocnik@ss-venopilon.si POVZETEK medpredmetne povezave način poučevanja, ki zahteva podrobnejšo organizacijsko in snovno pripravo. V prispevku je predstavljena izvedba projektnega dne, ki ga na Projektni dnevi, ki se na naši šoli izvajajo že nekaj let zapored, Srednji šoli Veno Pilon Ajdovščina izvedemo en dan v šolskem predstavljajo profesorjem izziv pri iskanju podajanja snovi na letu. Lansko leto v mesecu novembru smo izpeljali projektni dan drugačen, zanimivejši način. V preteklem šolskem letu smo se na temo izumov, z naslovom IzUMi za trajnost. Sodelavci iz tako povezali profesorji kemije, zgodovine, fizike in matematike. področij kemije, zgodovine, fizike in matematike smo z dijaki Na temo izumov smo dijakom predstavili razvoj in uporabnost spoznavali, kako so nam izumi skozi različna obdobja življenje odkritega z različnih predmetnih področij. izboljšali, nekateri pa tudi otežili in za vedno zaznamovali V tem članku bova profesorici zgodovine in matematike človeštvo. predstavili, kako smo ta dan izpeljali. KLJUČNE BESEDE Matematika, zgodovina, kemija, fizika, izumi 2 IZZIVI SODOBNEGA POUČEVANJA ABSTRACT Na srednji šoli Veno Pilon Ajdovščina, kjer obe poučujeva že vrsto let, izvajamo pouk tudi s pomočjo medpredmetnih povezav, The article presents the implementation of the project day, which ki jih načrtujemo v letnem učnem načrtu posameznega predmeta. takes place for one day each year at Secondary School Veno Matematiko lahko povežemo tako rekoč z vsakih predmetom, saj Pilon Ajdovščina. Last year in November, the project day, lahko prikažemo lepoto in uporabnost le-te na vseh področjih. entitled Inventions for Sustainability, was about inventions. Prav tako tudi zgodovino. Students and teachers from chemistry, history, physics and Medpredmetno povezovanje je eden od možnih didaktičnih mathematics observed how inventions have improved our lives pristopov poučevanja, ki si prizadeva povezovati vsebine in different periods of time, and sometimes even made life različnih predmetov in medpredmetnih področij. Profesor difficult and forever marked humanity. poskuša določeno vsebino ali problem obravnavati čim bolj celostno ter isto vsebino osvetliti z različnih vidikov, pri čemer KEYWORDS morajo biti jasno prepoznavni cilji drugih predmetov [1]. Mathematics, history, chemistry, physics, inventions Zakaj medpredmetno povezovanje? Pri dijaku spodbuja samostojno, aktivno pridobivanje učnih izkušenj ter poteka v celostni dejavnosti dijaka [2]. Pouk je bolj zanimiv, pozitivno 1 UVOD vpliva na razvoj samostojnega in kritičnega mišljenja ter se z Posodobljeni učni načrti profesorjem ponujajo možnosti za razvijanjem različnih strategij mišljenja in povezovanja znanja pripravo drugačnih učnih ur. Ker dijakom poskušamo prikazati povečata kakovost in trajnost pridobljenega znanja [3]. kompleksnost predmetov, ki jih poučujemo, iz različnih zornih Sodelovanje s profesorji z drugega predmetnega področja kotov in področij, se poslužujemo tudi medpredmetnih povezav. omogoča doseganje ciljev, ki jih posamezen profesor v okviru Dijaki na ta način pridobijo nova znanja, tudi v kontekstu svojega predmeta ne more doseči tako dobro, kot v sodelovanju vseživljenjskega učenja. Tak način dela ima tudi močan s profesorjem drugega predmeta. Sodelovanje in usklajevanje s motivacijski učinek, saj dijakom predstavimo neko snov kolegi poveča motivacijo za delo in omogoča profesionalni multiperspektivno. Dijaki se aktivno vključijo v proces pri razvoj. Zagotovo pa je medpredmetno sodelovanje tudi izziv, ker pridobivanju novih informacij. Za profesorja pomenijo omogoča drugačen način dela, izboljša komunikacijo med profesorji, hkrati pa posameznik razširi in poglobi lastno znanje. Pomembnost timskega poučevanja je v tem, da navzočnost dveh učiteljev dijakom omogoča sočasno podporo iz dveh predmetov, bolj individualiziran pouk in vzor timskega dela. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed V našem primeru medpredmetne povezave smo uporabili for profit or commercial advantage and that copies bear this notice and the full metodo sodelovalnega učenja, ker so dijaki to metodo poznali in citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). jo uporabljajo tudi pri drugih urah pouka. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 525 Pomembnost sodelovalnega učenja je, da z metodo izvirne se moramo izrednega pomena izobraževanja s področja uporabe sestavljenke dosežemo, da dijaki drug drugemu pomagajo. inovativnih pristopov, medpredmetnih povezav in izmenjav Posameznik ima določeno nalogo in je hkrati za svoje delo izkušenj med sodelavci. odgovoren v svoji skupini. Bolje kot člani skupine sodelujejo, bolje, lažje in prej je delo opravljeno. Poleg zgoraj naštetega smo se pri izpeljavi projektnega dne 3 DEJAVNOST posluževali tudi skupinskega dela v razredu. Elizabeth G. Cohen skupinsko delo definira kot delo dijakov v skupini, ki ga jasno 3.1 Ideja in oblikovanje dejavnosti določi učitelj. Skupina naj bo dovolj majhna, da lahko vsak Razredničarki 2 letnika gimnazijskega programa ter 4 letnika od njih k nalogi nekaj doprinese. Od dijakov se pričakuje, da predšolske vzgoje sva se odločili, da bi sodelovali pri izvedbi izpeljejo nalogo brez neposredne in takojšnje pomoči učitelja. [4] projektnega dne na temo izumov. Poleg naju, ki poučujeva Ko učitelj da dijakom delo v skupini in jim pri tem dovoli, da matematiko oziroma zgodovino, sva povabili h sodelovanju še delajo napake in se sami borijo za uspeh, s tem izvede prenos profesorja fizike in kemije. svoje avtoritete na dijake. Prenos avtoritete na dijake pa je V Katalogu znanja za gimnazije kot tudi za srednje strokovno temeljna posebnost (ang. key feature) skupinskega dela. To izobraževanje je priporočena uporaba različnih oblik in metod pomeni, da so zdaj dijaki odgovorni za svoj prispevek k dela ter je poudarjeno samostojno delo učencev [6, 7, 8]. Dijaki skupinskemu delu. Pri svojem delu so svobodni, saj nalogo naj bi pri samostojnem delu uporabljali različne vire in sodobno dokončajo na način, za katerega menijo, da je po njihovem tehnologijo. Zato smo izvedbo zasnovali tako, da so dijaki pri mnenju najboljši, učitelju pa so odgovorni predstaviti svoj naših urah bili samostojni in podajali svoje ideje ter kot končni izdelek. Prenos avtoritete nikakor ne pomeni, da je učni posamezniki bili vključeni v skupinsko delo. proces nekontroliran. Učitelj z distance nadzoruje in ocenjuje delo dijakov ter na koncu oceni njihov končni izdelek. 3.2 Cilji Naslednja posebnost skupinskega dela je, da člani skupine Dijaki: sami ne morejo dokončati naloge, zato potrebujejo en drugega. - razvijajo veščine dela v skupini in iskanja kompromisov za Tako dijaki prevzamejo vlogo poučevanja in začne se doseganje ciljev ter razvijajo ustvarjalnost in samoiniciativnost medvrstniško učenje s tem, ko dajejo ostalim članom v skupini (elementi podjetnosti); predloge, kaj naj delajo, da poslušajo druge in jih upoštevajo, - oblikujejo definicijo pojmov izum in odkritje; spoštujejo vsa mnenja in da soodločajo pri tem, kako bodo delo - ovrednotijo pomen izumov za človeka in zgodovinski razvoj; zaključili v predvidenem časovnem okviru in z rekviziti, ki jih - argumentirajo, kakšno bi bilo njihovo življenje brez izumov; imajo na voljo. - predlagajo nove izume za zmanjšanje okoljske krize, Delo v skupini je aktivno in živahno, ker vključuje izboljšanje udobja, reševanje življenj; - razvijajo občutljivost za zaznavanje aktualnih problemov in postavljanje vprašanj, razlaganje, podajanje predlogov, iščejo rešitve; kritiziranje, poslušanje, strinjanje, nestrinjanje, iskanje rešitev, - razvijejo temeljne spretnosti, veščine, znanja in navade za usklajevanje in skupne odločitve. Interakcija ni samo verbalna, učinkovito in uspešno uporabo digitalne tehnologije; ampak tudi neverbalna (npr. ponazarjanje, kimanje, - spoznavajo nove oblike učnih ur za popestritev frontalnega neodobravanje, smejanje). [5] pouka. Za načrtovanje takih povezav porabimo veliko več časa, zato 3.3 Načrtovanje dejavnosti jih moramo tudi večkrat ponoviti. Če povezavo izvedemo le enkrat, je izkoristek našega dela zelo majhen. Dijaki osvojijo nov Načrtovanje dejavnosti se je začelo z uskladitvijo učnih ciljev in način razmišljanja šele po nekaj ponovitvah. Pri preverjanju in pripravo poteka učnih ur. ocenjevanju pa se je izkazalo, da je znanje dijakov pri takem Profesorica matematike se je že v samem začetku povezala z načinu poučevanja kakovostnejše in trajnejše. gospo Nino Klun Čakš iz Urada RS za intelektualno lastnino, ki Poleg tega so učenci izpostavljeni nenehnim impulzom je posredovala veliko literature, ki nam je bila v pomoč in vodilo sodobne tehnologije in tudi s tega vidika potrebujejo drugačen pri izvedbi. Poiskali smo še video posnetke ter gradivo o izumih pristop. Učitelji jim moramo omogočiti, da so pri pouku čim bolj skozi čas. Dogovorili smo se glede delitev v skupine. Odločili aktivni, da samostojno pridobivajo potrebne informacije ter da smo se, da oblikujemo skupine, ki bodo sestavljena iz enakega razvijajo veščine, ki jim bodo pomagale pri vseživljenjskem števila dijakov programa gimnazija in predšolska vzgoja. To bi učenju. Razvijati morajo kritično mišljenje, biti sposobni omogočilo lažje vodenje skupin, saj so dijaki 4. letnika programa samovrednotenja in samokritičnosti. V poplavi informacij predšolska vzgoja vešči vodenja manjših skupin. Člani skupine morajo biti sposobni presoditi, ali so informacije, ki jih pridobijo so bili nato izžrebani na dan izvedbe. Naredili smo seznam na spletu pridobljene iz verodostojnih virov. Pomembno je, da za potrebnih pripomočkov za delo profesorjev in dijakov. Klopi v svoje delo prejmejo povratne informacije, ker jih spodbudijo k razredu so bile postavljene v obliki kvadrata za lažjo nadaljnjem raziskovanju, sami pa morajo biti pripravljeni v delo komunikacijo med člani skupine. Naloge so si razdelili člani vložiti svoj čas in trud. skupine. Določili pa smo dijake – novinarje, ki so celotno Učitelji smo vsakodnevno postavljeni pred izzive sodobnega izvedbo snemali, fotografirali in nato predstavili na plenarnem časa in digitalizacije pouka. Pri svojem delu moramo ponujati delu v obliki videoposnetka. inovativne pristope in ustvarjalne dejavnosti, čeprav je to včasih težko zaradi preobremenjenosti učiteljev in slabše pripravljenosti učencev za opravljanje obsežnega samostojnega dela. Zavedati 526 3.4 Izvedba dejavnosti Delo je potekalo v obliki medpredmetnega sodelovanja med zgodovino, matematiko, kemijo in fiziko. Dijaki so delali v skupinah, del dejavnosti je potekal s tehniko svetovne kavarne. Najprej smo dijakom predstavili cilje in potek dela. Kot prvo iztočnico za delo so si dijaki ogledali eksperiment (slonova zobna pasta), ki sta ga pripravila profesorica kemije in profesor fizike. Pri tem sta dijakom razložila kemijske in fizikalne elemente. Druga iztočnica za delo pa je bil ogled animiranega filma Slika 2. Izdelek druge dejavnosti Baltazar – Izumitelj čevljev. To je dijake spodbudilo, da so po Tretja dejavnost je bila zastavljena tako, da so dijaki po ogledu razmišljali o izumih, napakah, ki se dogajajo med delom, skupinah izbrali najpomembnejši izum iz antike. Svojo izbiro so začetnih neuspehih in vztrajnosti, ki je pomembna za dokončanje morali utemeljiti in ovrednotiti pomen izuma za razvoj človeka dela. ali gospodarstva. Sledilo je poročanje po skupinah. Skupine dijakov so bile sestavljene tako, da je imela vsaka Nato je profesorica matematike dijakom pokazala in razložila skupina po dva člana iz 2. letnika gimnazijskega programa ter še nekaj zabavnih izumov, ki pa nimajo vrednosti za človekov dva dijaka iz 4. letnika predšolskega programa. razvoj. Izvedba projektnega dne je potekala po dejavnostih. V prvi Nadaljevali smo s predstavitvijo štirih slovenskih izumiteljev dejavnosti je vsaka skupina na list napisala definicijo izuma in in njihovih najpomembnejših izumov (brata Rusjan, Janez Puhar, odkritja ter napisano predstavila ostalim skupinam. Janez Puh in Peter Florjančič). Pri tem smo izpostavili pomen Nato je profesorica matematike dijakom predstavila vpliv nekaterih slovenskih izumov in izumiteljev, npr. v letu 2020 smo izumov na človeka in razvoj, nastanek izumov kot potreba po obeležili stoto obletnico prvega slovenskega poleta Edvarda nečem, kar ne obstaja, pomoč drugim, izkoriščanje znanja o Rusjana. naravi ter najpomembnejše izume po izboru. V četrti dejavnosti so dijaki uporabili mobilne telefone za V naslednji dejavnosti je profesorica zgodovine vsaki skupini reševanje kviza Slovenski kvizum, katerega začetno stran dala nemi zemljevid sveta in komplet sličic z antičnimi izumi. prikazuje Slika 3, na temo slovenskih izumiteljev. Delo je Naloga dijakov je bila, da posamezni izum postavijo na celino, potekalo individualno. na kateri je nastal. Dijaki so najprej razvrščali sličice na papirni zemljevid, ki smo ga predhodno pripravili (glej Sliko 1). Slika 3. Začetna stran Slovenskega kvizuma Sledil je eksperiment (dimni balon), ki sta ga pripravila profesorica kemije in profesor fizike in dijakom razložila kemijske in fizikalne lastnosti. Slika 1. Izdelek druge dejavnosti Pri peti dejavnosti je delo dijakov potekalo s tehniko svetovne Pogovorili smo se o pravilnosti izbire postavitve kavarne. Najprej je vsaka skupina izbrala eno temo iz sledečega posameznega izuma v zemljevidu. Potem pa so dijaki enako nabora: Izumi, ki nam poenostavljajo življenje, Izumi, ki rešujejo dejavnost ponovili še v Arnesovi spletni učilnici. Dejavnost, kje življenje, Izumi, ki nam škodijo, Izumi, ki bi pomagali rešiti so dijaki razvrščali različne predmete na zemljevid, je pripravil ekološko krizo [9]. Naloga vsake skupine je bila, da so izbrali tri kolega Urban Šček, s katerim smo skupaj sodelovali pri tem izume in utemeljili izbiro. Nato je en dijak ostal pri mizi v vlogi projektnem dnevu. Primer izbranih odgovorov je prikazan na poročevalca, ostali trije pa so odšli k drugim skupinam. Pri Sliki 2. matični skupini so novi člani dodali po tri izume in jih utemeljili. Nato so izbrali novega člana za poročanje o delu v skupini, ostali pa so se selili. Dejavnost se je zaključila, ko je vsak dijak sodeloval v vseh skupinah. Skupine so bile na koncu v drugačni sestavi kot na začetku in so poročali ostalim. Pri tej dejavnosti so dijaki uporabljali aplikacijo Padlet na način kot je prikazano na 527 Sliki 4, kjer so podajali ideje, o katerih so se pogovarjali v posamezni skupini. Slika 4. Izdelek pete dejavnosti V nadaljevanju smo na tablo zapisali besede motor, knjiga, fotoaparat, telefon, ura, računalnik, radio, čevlji ter bicikel. Dijaki so morali po skupinah sestaviti nov izum tako, da so Slika 7: Montaža videoposnetka. povezali dva ali tri samostalnike med seboj (glej Sliko 5). Izum V dnevu po delavnicah so dijaki naredili evalvacijo so razložili ostalim in izpostavili uporabnost in prednosti novega projektnega dne v obliki vprašalnika. izuma. 4 EVALVACIJA UDELEŽENCEV Dijaki so po končani dejavnosti izpolnili evalvacijski vprašalnik, v katerem smo jim zastavili štiri vprašanja, in sicer: 1. Kaj ti je bilo pri takem načinu dela všeč? Zakaj? 2. Zapiši predloge izboljšav. 3. Ovrednoti delo ostalih skupin v delavnici. 4. Naštej dve novi informaciji o izumih ali izumiteljih, ki ti bosta ostali v spominu. Večini dijakov je bila celotna dejavnost všeč, vendar je bila predolga. Nekaterim delo z dijaki, ki jih ne poznajo, ni všeč in tega ne bi ponovili. Zelo ustvarjalni so bili pri sestavljanju novih izumov (združevanje samostalnikov). Presenetil jih je še živeči izumitelj Peter Florjančič in njegovi izumi. Delo ostalih skupin Slika 5. Skupinsko delo šeste dejavnosti so ovrednotili kot uspešno, ustvarjalno zabavno in uporabno. Nato so dijaki individualno reševali kviz Kahoot o izumih in Dijake sta navdušila eksperimenta in nekateri so poskusili izumiteljih. Del kviza je prikazan na Sliki 6. Najboljšega smo oblikovati dimni balon. Težave so imeli z montažo nagradili s praktičnim darilom. videoprispevka, ker je bila ena ura časa premalo za dovršen izdelek. 5 EVALVACIJA IZVAJALCEV Sama tema izumov in izumiteljev ni posebej zajeta v učni načrt, ampak nas izumi spremljajo dnevno, zato je smiselno, da dijaki razmišljajo o tem in ovrednotijo vlogo izumov in izumiteljev za življenje ljudi. Delo je zasnovano medpredmetno, zato je potrebno veliko koordinacije med sodelujočimi učitelji in veliko truda pri oblikovanju dejavnosti in usmerjanju dijakov pri delu. Pri oblikovanju skupin je smiselno, da se pred začetkom dela Slika 6: Kviz izdelan s pomočjo Kahoota. izvede igro spoznavanja članov, ker se vsi ne poznajo med seboj V osmi dejavnosti so dijaki v skupini izbrali tri predmete, ki in nato delo lažje steče. Ker je bila celotna dejavnost dolga 6 ur jih uporabljajo vsak dan. Nato so opisali, kako drugačno bi bilo je bila na določenih delih težko motivirati dijake za delo, saj so njihovo življenje, če teh izumov ne bi izumitelji delili s svetom. bili aktivni skozi celoten proces (razen pri eksperimentih in Potem so poročali ostalim skupinam, preostali dijaki so ustno predstavitvi izumiteljev) in jim je koncentracija padala. Nekoliko ovrednotili izbor posamezne skupine. jih je bilo treba usmerjati pri svetovni kavarni, da so se člani Nazadnje je nekaj dijakov, ki so prikazani na Sliki 7, vsakokrat primerno razporedili po skupinah. Dijake smo med pripravilo videoposnetek o delavnicah, v katerih so sodelovali. poročanjem opozarjali na izražanje in rabo besedišča. Izdelan posnetek smo predstavili na skupni prireditvi, kjer so vsi sodelujoči na projektnem dnem imeli priložnost videti, kaj smo počeli. 6 ZAKLJUČEK Projektni dan na temo izumov se nam je že sprva zdela zanimiva tema, ki jo je moč raziskati z različnih zornih kotov. Zbrali smo 528 se profesorji iz različnih področij, ki se tudi sicer zelo dobro [5] Prirejeno po: Ravnihar, D., Učinkovito skupinsko delo v dopolnjujemo, tako pri izvajanju vsakodnevnega pouka kot tudi razredu. [Elektronski vir] DOI= v zasebnem življenju. Pri pripravi in izvedbi dela v delavnicah http://www.bcnaklo.si/fileadmin/projekti/mednarodni/tuji_ smo se zato zabavali in s sproščenostjo in dobro voljo tudi jeziki/Irska_marec_2016/Ravnihar_Darja_Ucinkovito_sk izpeljali potek celotnega dne. Meniva, da nam je uspelo upinsko_delo_v_razredu.pdf (dostop: 2.7.2019). predstaviti izbrano temo na zanimiv in drugačen način, saj se [6] Katalog znanja zgodovina srednje strokovno sicer dijaki v samem učnem načrtu s tovrstno tematiko ne izobraževanje. [Elektronski vir] DOI= srečujejo. http://portal.mss.edus.si/msswww/programi2016/programi/ SSI/KZ-IK/katalog.html (22. 8. 2020). [7] Učni načrt. Matematika. Splošna, klasična in strokovna LITERATURA IN VIRI gimnazija. 2008. [Elektronski vir] DOI= [1] Kovač, M., Starc, G., Jurak, G. 2003. Medpredmetno in http://eportal.mss.edus.si/msswww/programi2010/program medpodročno povezovanje pri športni vzgoji. V: Šport, i/media/pdf/un_gimnazija/un_matematika _gimn.pdf (22. letnik 51, št. 2, (str. 11–15). 8. 2020). [2] Sicherl Kafol, B. 2002. Glasbena didaktika v luči [8] Pavlič, G., Kavha, D., Rugelj, M., Šparovec, J. 2012. medpredmetnih povezav. V: Sodobna pedagogika, letnik Planum Novum, Matematika za gimnazijo. Ljubljana: 53, št. 2, (str. 50–61). Modrijan. [3] Marentič Požarnik, B. 2000. Psihologija učenja in pouka. [9] Uči se iz preteklosti, ustvarjaj prihodnost: Izumi in patenti. Ljubljana: DZS. Svetovna organizacija za intelektualno lastnino. Urad RS za intelektualno lastnino. Ljubljana. 2006 [4] Cohen, E. G. 1994. Designing Groupwork: Strategies for the Heterogeneous Classroom. New York, London: Teachers College Press, Columbia University. 529 Določevanje težnega pospeška s pomočjo pametnega telefona Determining gravitational acceleration using smartphone Goran Kosem I. gimnazija v Celju Kajuhova 2 3000 Celje, Slovenija goran.kosem@prvagim.si POVZETEK home, and the results were very accurate. The advantages and disadvantages of this approach will be presented, as well as ideas Učenje na daljavo je učiteljem naravoslovnih predmetov for upgrading the experiment. predstavljalo poseben izziv pri izvedbi eksperimentalnega dela. Medtem ko je predavanje učne snovi in ocenjevanje znanja dokaj KEYWORDS enostavno izvajati preko spleta, pri eksperimentiranju ni tako. Učitelji smo morali laboratorijske vaje prilagoditi tako, da so bile Experimental work, gravitational acceleration, smartphone, primerne za samostojno delo v domačem okolju. Pri tem smo si Phyphox, Logger Pro, ICT lahko pomagali tudi s sodobnimi IKT orodji. V prispevku bo prikazan primer izvedbe fizikalnega eksperimenta na daljavo, pri 1 UVOD katerem so dijaki 1. letnika gimnazije določevali velikost težnega pospeška s pomočjo pametnega telefona. Uporabljali so mobilno Raziskava, s katero je Zavod Republike Slovenije za šolstvo aplikacijo Phyphox za zajem podatkov in programsko orodje preverjal učinkovitost letošnjega poučevanja na daljavo, kaže, da Logger Pro za grafično predstavitev rezultatov. Dijaki so je okoli ⅘ učiteljev na daljavo uspelo predelati vsaj ⅔ predvidene eksperiment lahko izvedli s pripomočki, ki jih najdemo v vsakem učne snovi [1]. Poučevanje in ocenjevanje na daljavo torej ni bilo domu in pri tem dobili zelo natančne rezultate. Predstavljene posebej problematično, kakovostno izvajanje eksperimentalnih bodo prednosti in pomanjkljivosti omenjenega pristopa ter ideje vaj pa je učiteljem predstavljalo težavo. Večina vaj namreč za nadgradnjo eksperimenta. zahteva pripomočke in opremo, ki je povprečen učenec nima na voljo doma. Učitelji smo zato morali, kjer je bilo to mogoče, KLJUČNE BESEDE prilagodili vaje za izvajanje v domačem okolju. Za prikaz Eksperimentalno delo, težni pospešek, pametni telefon, naravnih zakonitosti smo se fiziki lahko zanesli tudi na sodobno Phyphox, Logger Pro, IKT IKT opremo, kot so različne spletne simulacije (appleti) in pametni telefoni. ABSTRACT Distance learning presented a special challenge for science 2 PAMETNI TELEFON V FIZIKALNEM teachers in the implementation of experimental work. While LABORATORIJU lecturing and assessing knowledge is fairly easy to do online, experimentation is not. Teachers had to adapt the laboratory K uporabi različnih spletnih orodij pri pouku fizike nas spodbuja exercises so that they were suitable for independent work in the tudi učni načrt [2]. Sam problem pri uporabi računalniških home environment. We were also able to help ourselves with simulacij vidim v tem, da njihov algoritem temelji na tistem modern ICT tools. The paper will present an example of naravnem zakonu, ki ga nameravamo preizkušati. Na ta način performing a physical experiment at a distance, in which first- bomo seveda vedno dobili vrednosti, ki izhajajo iz določenega year high school students determined the magnitude of algoritma in ne moremo sklepati, če bi enake rezultate dali tudi gravitational acceleration using a smartphone. They used the dejanski poskusi v naravi ali laboratoriju. Zato menim, da je Phyphox mobile application to capture data and the Logger Pro fizikalne poskuse treba opravljati v živo in se posluževati software tool to graphically present the results. Students were računalniških simulacij le v redkih primerih, ko prvo ni mogoče. able to perform the experiment with accessories found in every Drugačno možnost za izvajanje eksperimentov v domačem okolju pa nam nudijo pametni telefoni. Z njimi lahko dejansko fizično izvedemo nek eksperiment, pametni mobilnik pa uporabimo za zajem različnih parametrov. Moderni pametni Permission to make digital or hard copies of part or all of this work for personal or telefoni namreč vsebujejo pester nabor različnih senzorjev: classroom use is granted without fee provided that copies are not made or distributed mikrofon, zvočnik, kamero, GPS, merilnik pospeška, žiroskop, for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must magnetometer, termometer, barometer, higrometer, senzor be honored. For all other uses, contact the owner/author(s). zaznavanja bližine in osvetljenosti, kotomer … Torej jih lahko Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia uporabimo za zajemanje in obdelavo mnogih fizikalnih količin © 2020 Copyright held by the owner/author(s). 530 iz okolja. Čeprav se zanesljivost in kvaliteta tako pridobljenih poteči od začetka do konca poskusa. Tako lahko dosežemo, da podatkov verjetno ne moreta primerjati s specializirano aplikacija reagira le na naš začetni sunek ter trk uteži s tlemi, ne laboratorijsko opremo, menim, da pametni telefoni predstavljajo pa npr. na odmeve v zaprtih prostorih ali druge zvočne motnje precejšno popestritev pouka in poceni priložnost za izvedbo med poskusom. Seveda pa mora biti ta zamik v vsakem primeru številnih enostavnejših eksperimentov, predvsem v primarnem in manjši od dejanskega časa padanja. Dijakom sem svetoval, naj si sekundarnem šolstvu. nastavijo prag zajemanja zvoka na 0,5 relativnih enot in Da lahko pametni telefon uporabimo kot del fizikalnega minimalni zamik na 0,2 sekunde ter te vrednosti po potrebi laboratorija, potrebujemo primerno aplikacijo. V prispevku bo prilagodijo (slika 2). predstavljena večkrat nagrajena aplikacija Phyphox, ki je bila Nato so dijaki lahko začeli s poskusom. Ravnilo je bilo razvita na nemški Univerzi RWTH v Aachnu. potrebno položiti na vodoravno podlago (mizo, stol, polico …), tako da je en konec visel čez rob in na ta konec so dijaki postavili svojo utež. V bližino so postavili telefon in zagnali eksperiment 3 DOLOČEVANJE TEŽNEGA POSPEŠKA S Akustična štoparica v Phyphoxu. Nato so s palico udarili ravnilo POMOČJO PAMETNEGA TELEFONA v vodoravni smeri, tako da se je odmaknilo in je utež začela prosto padati (slika 3). Ta udarec je sprožil akustično štoparico, 3.1 Teoretična izhodišča zvok padca uteži s tlemi pa jo je ustavil. Na ta način so dobili Težni pospešek ob površju Zemlje ( g) lahko določimo s pomočjo natančno izmerjen čas padanja. Na koncu so s pomočjo prostega pada. Telo, ki ga spustimo padati z višine h, pade na tla izmerjene višine in časa padanja izračunali težni pospešek. v času t, pri čemer velja zveza: 𝑔𝑔 = 2ℎ [3]. Pri tem smo Poskus so opravili štirikrat, vsakič z drugačne višine. 𝑡𝑡2 zanemarili vpliv zračnega upora. Za določitev težnega pospeška moramo torej natančno izmeriti čas padanja z znane višine. Aplikacija Phyphox za to merjenje uporablja akustično štoparico, ki lahko do tisočinke sekunde natančno meri čas med dvema zvočnima signaloma [4]. Prvega ustvarimo ob tem, ko spustimo telo, drugi pa nastane, ko telo pade na tla. Izbrati moramo telo in podlago, ki ob trku ustvarita čim bolj glasen zvok, poskus pa je seveda treba izvajati v tihem okolju. 3.2 Izvedba eksperimenta Dijaki so si na pametni telefon morali naložiti aplikacijo Phyphox, ki je brezplačno dostopna v Google Play in App Store (slika 1). Poleg telefona so potrebovali še merilni trak za merjenje višine, utež, ravnilo in palico. Za utež smo jim svetovali kakšen manjši kovinski predmet (npr. kovanec), ki ob padcu na Slika 2. Akustična štoparica v Phyphoxu trdo podlago ustvari glasen zvok. Namesto palice so lahko uporabili kuhalnico ali kar jedilno žlico. V primeru mehke podlage, so si lahko pomagali tudi s kovinsko ali leseno ploščo Rezultate so dijaki vpisali na delovni list. Na koncu so (npr. pladnjem), ki so jo položili na tla za okrepitev zvoka ob dobljene vrednosti uporabili še za grafično upodobitev. V pristanku uteži. programski opremi Logger Pro, ki jo na šoli uporabljamo pri fizikalnih eksperimentih, so narisali graf, ki prikazuje odvisnost višine od časa padanja. V graf so vnesli tudi prilagoditveno kvadratno funkcijo. Nato so omenjeni graf še linearizirali in iz naklona dobljene premice odčitali povprečni težni pospešek. Oba grafa so priložili delovnem listu ter ga, skupaj s fizikalnimi ugotovitvami in komentarji, poslali profesorju. Slika 1. Aplikacija Phyphox V Phyphoxu so odprli eksperiment Akustična štoparica (Acoustic Stopwatch). Najprej so si nastavili prag zajemanja zvoka (Treshold). Višji, kot je prag, glasnejši mora biti zvok, ki sproži štoparico. S primerno nastavitvijo praga, se lahko izognemo zvočnim motnjam iz okolja. Nastavili so si tudi Slika 3. Postavitev eksperimenta minimalni zamik (Minimum Delay), to je najmanjši čas, ki mora 531 3.3 Rezultati eksperimenta Aplikacija Phyphox se je pri tem eksperimentu izkazala za zelo zanesljivo, saj je večina dijakov za težni pospešek dobila rezultate, ki so za manj kot 5% odstopali od dejanske vrednosti 9,81 m/s2 [3]. Glede na enostavnost eksperimenta, gre za presenetljivo dobre rezultate. Opazili smo, da so vrednosti, dobljene z višjih višin padanja, bolj natančne od tistih z nižjih višin (tabela 1). To gre verjetno pripisati dejstvu, da je relativna napaka izmerjenega časa manjša pri daljšem času. Veliko dijakov je odstopanja pripisalo dejstvu, da smo pri poskusu zanemarili vpliv zračnega upora. Prav tako pa smo zanemarili čas, ki ga zvok potrebuje za pot do mikrofona v telefonu. Zaradi slednjega je dejanski čas padanja uteži pravzaprav manjši od izmerjenega in sicer za približno 0,003 sekunde na meter prepotovane višine. Z upoštevanjem tega popravka bi se izračunane vrednosti težnega pospeška malo povečale in torej še Slika 5. Lineariziran graf prostega pada bolj približale dejanski vrednosti (tabela 1). Tabela 1. Rezultati meritev 3.4 Evalvacija eksperimenta in dodatne možnosti Phyphox se je pri tej eksperimentalni vaji odlično izkazal. Delo je bilo enostavno in hitro, rezultati pa zelo natančni. Aplikacija je brezplačna in ponuja izvedbo številnih poskusov iz različnih področij fizike. Navodila za izvedbo poskusov so jasna in v nekaterih primerih vsebujejo celo video posnetke in delovne liste za učence. Kot edino pomanjkljivost lahko omenim le dejstvo, da nekaterih eksperimentov ni mogoče izvajati na starejših pametnih telefonih. Natančnost rezultatov je bila vidna tudi iz priloženih grafov, Phyphox pri uporabi akustične štoparice omogoča tudi zajem saj sta se prilagoditvena kvadratna in linearna funkcija odlično niza petih zaporednih zvočnih signalov (Sequence) in meri čas prilegali vnesenim točkam. S kvadratno funkcijo so dijaki med njimi. Če bi namesto kovinskega telesa spustili padati potrdili, da se je utež gibala enakomerno pospešeno (slika 4), saj gumijasto žogico, bi lahko na ta način proučevali (ne)elastičnost velja ℎ = 𝑔𝑔∙𝑡𝑡2. trkov in energijske izgube žogice ob trkih. Naslednja možnost je 2 zajem poljubnega števila zvočnih signalov v poljubnem času (Many), kjer dobimo celo izrisan graf dogodkov v času, povprečen tempo (bpm) in frekvenco dogodkov. Omenjeno možnost bi lahko npr. uporabili pri merjenju radioaktivnih razpadov s klasičnimi prskači. Prav tako se lahko akustična štoparica uporabi za merjenje hitrosti zvoka, vendar v tem primeru potrebujemo dva telefona in dve osebi za izvedbo eksperimenta. 4 ZAKLJUČEK Pametni telefoni si nedvomno utirajo pot v fizikalni laboratorij. S svojimi številnimi senzorji ponujajo zajemanje številnih fizikalnih količin iz okolja ter celo njihovo analizo in grafično Slika 4. Višina v odvisnosti od časa pri prostem padu predstavitev. Pri prikazani vaji so se izkazali za presenetljivo natančen pripomoček, ki ponuja številne prednosti. Aplikacija Medtem pa je naklon premice lineariziranega grafa podal Phyphox je brezplačna, enostavna za uporabo in je pri prikazani povprečno vrednost gravitacijskega pospeška. V predstavljenem eksperimentalni vaji dala zelo natančne rezultate. Dijaki imajo grafu je ta znašal 9,79 m/s2, kar je natančno na 0,2% (slika 5). radi takšen način dela in so se v velikem številu lotili samostojnega eksperimentiranja. Kot prednost omenjenega pristopa so omenili tudi samostojno prilagajanje časovne izvedbe poskusa in manjši stres. Vaja ne zahteva veliko učiteljeve priprave, večjih slabosti nisem zaznal. Pametni telefoni nam bodo olajšali terensko delo, saj ne bomo več potrebovali toliko nerodne laboratorijske opreme. Še posebej pa so lahko uporabni v primeru izvajanja pouka na daljavo, saj jih imamo praktično vsi. Aplikacijo Phyphox vsekakor priporočam učiteljem fizike. 532 VIRI IN LITERATURA za šolstvo, 2008. Učni načrt za fiziko, 2008. DOI= http://eportal.mss.edus.si/msswww/programi2019/program [1] Zavod Republike Slovenije za šolstvo. 2020. Analiza i/media/pdf/un_gimnazija/2015/UN-FIZIKA-gimn-12.pdf. izobraževanja na daljavo v času epidemije Covid-19 v Sloveniji. DOI= [3] Mohorič, A. in Babič, V. 2013. Fizika 1: učbenik za fiziko https:/ www.zrss.si/digitalnaknjiznica/IzobrazevanjeNaDal v 1. letniku gimnazij in štiriletnih strokovnih šol. javo/. Ljubljana: Mladinska knjiga. [2] Učni načrt. Program splošna gimnazija. Fizika. Elektronski [4] Phyphox. Free fall acoustic detection. DOI= vir. Ljubljana : Ministrstvo za šolstvo in šport: Zavod RS https:/ phyphox.org/experiment/free-fall-2/. 533 Uporaba aplikacije KamenCheck pri pouku geografije Using the KamenCheck application in geography lessons Lidija Kotnik Klaužer OŠ Lesično Lesično 5b 3261 Lesično, Slovenija lidijakot@gmail.com POVZETEK KEYWORDS Živimo v obdobju, ko so družbene, gospodarske, izobraževalne in vzgojne potrebe čedalje večje, zato je uvedba informacijsko- Communication technology, primary school, geography, komunikacijske tehnologije (IKT) v naše življenje pomembna in application KamenCheck neizogibna. Pri vzgojno-izobraževalnem delu lahko z osmišljeno rabo IKT pri pouku geografije v osnovni šoli pouk obogatimo, 1 UVOD učence motiviramo za raziskovanje in učenje, hkrati pa razvijamo geografske veščine in spretnosti. Z razvojem IKT in V času hitrih družbenih, gospodarskih in tehnoloških sprememb številnih aplikacij je raba le-te smiselna in uporabna ne le v je uporaba IKT nujna. Vseživljenjsko učenje danes je dolžnost učilnici, ampak tudi pri terenskem delu. posameznika, da se izobražuje vse življenje – ne le formalno, ampak tudi neformalno. Prispevek opisuje načrtovanje in izvedbo naravnogeografskih Eden bistvenih dejavnikov vseživljenjskega učenja je učnih vsebin z uporabo aplikacije določevalnega kamninskega uporaba IKT v izobraževanju, saj le-ta pomembno pripomore k ključa KamenCheck, pri čemer so devetošolci v šolskem parku vseživljenjskemu učenju tako s širitvijo dostopa do vsebin kot kamnin pri pouku geografije raziskovali in spoznavali kamnine, tudi z vpeljevanjem bolj raznovrstnih poti učenja. Uvajanje ki jih najdemo v Sloveniji. novih učnih sredstev in učil omogoča učitelju, da sta učni proces in vsebine učinkovita, zanimiva, razumljiva in aktualna. Tako je KLJUČNE BESEDE IKT prinesla nove možnosti za učenje, poučevanje in Informacijsko-komunikacijska tehnologija, osnovna šola, pridobivanje znanja v sodobni družbi. geografija, aplikacija KamenCheck Za uspeh v današnji družbi, bogati z informacijami in znanjem, morajo učenci in učitelji učinkovito uporabljati ABSTRACT tehnologijo. Uvedba IKT v učilnice vpliva na naslednje načine: We live in a period when social, economic and educational needs - učencem pomaga razviti spretnosti, ki so potrebne za are becoming more and more demanding, so the introduction of uspešno življenje in delo v 21. stoletju; information communication technology into our lives is - spodbuja učitelje k izboljšanju načina učenja v razredu inevitable and necessary. Calculated use of ICT in teaching z interaktivnimi in dinamičnimi viri, ki jih nudi IKT, geography in primary school can result in enriched lessons, in student motivation and developing of geographical skills. With - zagotavlja več motivacije in bogatejšo izkušnjo učenja the development of ICT and numerous applications, the use of it za učence, s tem pa možnosti za bolj učinkovito učenje is reasonable and useful, not only in the classroom, but also in in večje vključevanje učencev samih v izobraževalni field work. proces. [1] The article describes planning and performance of geography V učnem načrtu geografije za osnovne šole [4] je pri and natural resources educational content with the use of rock opredelitvi predmeta zapisano, da z vsebinami in dejavnimi identification key KamenCheck. It was used in the school rock metodami pri pouku geografije razvijamo sposobnosti učencev park by ninth graders during the geography lesson to see and za uporabo preprostih geografskih raziskovalnih metod, s explore rocks, found in Slovenia. katerimi pridobivajo informacije o okolju in v okolju. Usposabljamo jih za rabo različnih sredstev in medijev, s katerimi urejajo, razlagajo, predstavljajo, uporabljajo, vrednotijo in posredujejo geografske informacije. Ob tem je še posebej pomembna informacijska tehnologija. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed 2 APLIKACIJA KamenCheck for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must Kamencheck je aplikacija določevalnega kamninskega ključa za be honored. For all other uses, contact the owner/author(s). poučevanje geoloških vsebin v okviru naravoslovnih predmetov. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). Nastala je v okviru projekta StoneKey znotraj razpisa Po 534 kreativni poti do znanja, ki spodbuja povezovanje visokošolskih didaktično primernost lokacije za pouk, ki naj ustreza ključnim zavodov s trgom dela in na tak način daje študentom možnost za merilom, kot so prostorsko spoznavna oz. sporočilna moč pridobitev praktičnih izkušenj že med izobraževanjem. Projektno pokrajine, povezanost s cilji učnega načrta, oddaljenost, skupino so sestavljali študentje Geologije, Grafične in metodična raznolikost in dostopnost učnega gradiva. [4] interaktivne komunikacije ter Elektrotehnike in Multimedije, pri Učenci v 9. razredu pri geografiji spoznavajo geografske, razvoju pa so sodelovali s podjetjem DigiEd, d.o.o., ki je tako naravne kot družbene, značilnosti Slovenije. OŠ Lesično specializirano za razvoj produktov in storitev s področja e- ima učilnico na prostem, ki jo v sodelovanju s Kozjanskim izobraževanja. V proces izdelave in končno evaluacijo so parkom dopolnjujemo in nadgrajujemo. Leta 2019 smo jo vključili uporabnike. dopolnili s parkom kamnin, ki je prikazan na sliki 2. Strokovna zasnova aplikacije, kar prikazuje slika 1, obsega navodila za uporabo ključa, »malo šolo«, kjer se nahaja razlaga 16 pojmov in 6 opisov poizkusov na kamninah, vsebinski del v obliki določevalnega kamninskega ključa, kjer prepoznavamo kamnine glede na mineralna zrna, plastnost in dodatne kriterije glede na tip kamnine, ter končne opise kamnin (encikopedija), kjer je 28 opisov kamnin, so izdelali študenti geologije. Študentje grafičnih in interaktivnih komunikacij so poskrbeli za predstavitev in interpretacijo kamnin skozi grafični jezik. Pri načrtovanju in implementaciji multimedijske interaktivne mobilne aplikacije pa so sodelovali študentje elektrotehnike oz. multimedije. Avtorji so z inovativnimi in kreativnimi rešitvami izdelali orodje, ki obogati uporabnikovo izkušnjo učenja in doživljanja nežive narave. Slika 2: Šolski park kamnin. Aplikacija je zasnovana kot interaktivni pripomoček za Učenci že v 6. razredu pri pouku naravoslovja spoznajo vrste učenje v/o naravi in je uporabna za izobraževanje geoloških kamnin in njihov nastanek. Pri urah geografije učno snov vsebin ter raziskovanja nežive narave. Učni pripomoček je ponovimo in jo nadgradimo s terenskim delom, ki temelji pa zanimiv za uporabo, inovativen in združuje možnost prepoznavanju kamnin in ovrednotenju kamninske zgradbe za interaktivnega učenja tako v učilnici kot v naravi. Aplikacija je človeka. Šolski park kamnin predstavlja edinstveno priložnost prosto dostopna. Deluje na sistemu Android. [2] za problemsko, izkustveno in raziskovalno načrtovan pouk, zato sem učne vsebine obravnavala v obliki terenskega dela, v katerega sem vključila IKT. Na takšen način uresničujem cilje sodobnega pouka, učencem približam učne vsebine, jih naredim privlačnejše in zanimivejše. 3.2 Izvedba učnega procesa v parku kamnin Učence sem na terensko delo pripravila v razredu. Sami so se razdelili v skupine, ki so ji sestavljali trije oz. štirje učenci. Opozorila sem jih, da potrebujejo pametni mobilni telefon ali tablico in jih pozvala, da se dogovorijo, kdo bo telefon oz. tablico prinesel v šolo. Nato sem podala navodila, da si doma aplikacijo Slika 1: Aplikacija KamenCheck. KamenCheck namestijo na svoje naprave. Na dan izvedbe terenskega dela, ki smo mu namenili 2 šolski uri, smo odšli v park kamnin, kjer smo s problemskim 3 NAČRTOVANJE IN IZVEDBA vprašanjem » Zakaj imamo kamnine v parku razporejene v tri različno velike skupine? « preverili predznanje ter ponovili in 3.1 Načrtovanje utrdili že znano učno vsebino, da kamnine glede na nastanek Geografija je v program osnovne šole umeščena zato, da učencu delimo na magmatske, sedimentne in metamorfne ter kaj je pomaga pridobiti znanje, sposobnosti in spretnosti, s katerimi se posamezno skupino kamnin značilno. lahko orientira in razume ožje in širše življenjsko okolje, in da ga Sledila so navodila za delo. Opozorila sem na natančno vzgaja v pravilnem vrednotenju in spoštovanju okolja, s čimer si opazovanje in branje kamninskega ključa. pridobi tudi odnos do narave, sebe, sočloveka in družbe. Učni Raziskovanje in spoznavanje kamnin so pričeli tako, da si je proces mora biti uravnotežen med poučevanjem in različnimi skupina izbrala po dve kamnini v vsaki skupini in ju s pomočjo oblikami učenčevih dejavnosti. Učenje mora temeljiti na razvoju kamninskega ključa v aplikaciji KamenCheck poimenovala ter sposobnosti in spretnosti – vedeti, kako – in spoznavnosti – jo natančneje spoznala. Aktivno delo učencev prikazujejo slike vedeti, kaj. Vedno bolj poudarjen pa je namenski vidik – vedeti, 3, 4 in 5, na katerih vidimo, da so učenci pri delu uporabljali zakaj potrebujemo neko znanje, spretnost oz. sposobnost. mobilni telefon in tablico. Svoje ugotovitve so zapisovali na Usvajanje geografskega znanja temelji na več stopnjah. Ena delovne liste, ki so jih reševali sproti. najpomembnejših je opazovanje, ki je osnova terenskega dela. Pri izboru učnega prostora je pomembno, da učitelj prouči 535 povečamo. Poleg tega pa razvijamo veščine dela z IKT, kar je izredno pomembno v času, v katerem živimo. Osnovni namen, poleg spoznavanja nove učne vsebine o kamninah, je bil prikazati uporabnost mobilnika in aplikacije v konkretni situaciji na primeru šolskega parka kamnin. Cilj je bil v celoti uresničen. Devetošolci in devetošolke so spoznali še eno izmed možnosti, ki jih ponuja praktična uporaba pametnega mobilnika ali tablice v vsakdanjem življenju. Sliki 3: Učenke spoznavajo kamnine s pomočjo aplikacije KamenCheck na pametnem telefonu. Slika 5: Aktivno opazovanje in proučevanje kamnin. Terensko delo je temeljilo na natančnem opazovanju in branju, kar so tekom raziskovanja ugotovili tudi učenci. Učenci so razvijali sposobnosti in spretnosti ter spoznavali in prepoznavali kamnine ter njihovo uporabnost, hkrati pa pridobili uvid, zakaj potrebujemo znanje o kamninah in se urili v spretnosti oz. sposobnosti uporabe aplikacije KamenCheck na pametnem telefonu oz. tablici. S tem so bili uresničeni številni cilji predmeta. Razvoj novih tehnologij in aplikacij od nas učiteljev zahteva Slika 4: Spoznavanje kamnin z uporabo tablice. vse več IKT znanja, zato je pomembno trajno izobraževanje, tako formalno kot neformalno, in učiteljeva prizadevnost za uporabo 3.3 Pregled dela in evalvacija IKT pri pouku. S tem pa se spreminja tudi vloga učitelja, ki se iz Tretja šolska ura je bila izvedena v učilnici. Namenjena je bila podajalca znanja spreminja v organizatorja dejavnosti, mentorja pregledu dela in evalvaciji. Učenci so predstavili posamezne in trenerja veščin. kamnine, ki so jih proučevali. Pri tem sem po potrebi opozorila na morebitne pomanjkljivosti, dodatno opisala ali pojasnila kamnino in njeno uporabnost ter učence usmerjala k VIRI IN LITERATURA dopolnjevanju odgovorov. Učencem sem posredovala povratne [1] Brečko, B. N., Vehovar, V. 2008. Informacijsko- informacije o njihovi kvaliteti dela, za zaključek pa izpostavila komunikacijska tehnologija pri poučevanju in učenju v vsebinske poudarke ter spodbudila k zastavljanju morebitnih slovenskih šolah. Ljubljana: Pedagoški inštitut. vprašanj. Učenci so se nato preverili v kvizu o poznavanju Pridobljeno 20. 8. 2020 s kamnin. https:/ core.ac.uk/download/pdf/95411076.pdf. Ustno so podali povratno informacijo o poteku učnih ur o [2] KamenCheck. Pridobljeno 20. 8. 2020 s spoznavanju kamnin v šolskem parku. Učencem je terensko delo http://kamencheck.digied.si/. všeč. Bilo jim je zanimivo, da je pouk potekal v naravi in z [3] Lipovšek, I., Poljšak, A., Lilek, D. 2015. Smernice uporabo pametnih telefonov oz. tablic. za uporabo IKT pri predmetu geografija. Pridobljeno 20. 8. 2020 s http://arhiv.inovativna- sola.si/images/inovativna/Smernice/GEOGRAFIJA_smern 4 ZAKLJUČEK ice_IKT.pdf. Terensko delo je sestavni del pouka geografije. Zaradi številnih [4] Učni načrt. 2011. Program osnovna šola. Geografija. prednosti, ki jih prinaša tovrstno delo v domači pokrajini, je Pridobljeno 21. 8. 2020 s smiselno, da učitelji vedno znova iščemo nove možnosti za delo https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/O v pokrajini, hkrati pa raziskovanje prepuščamo tudi učencem. Če snovna-sola/Ucni-nacrti/obvezni/UN_geografija.pdf. temu dodamo še uporabo IKT, motivacijo za delo le še 536 Delo z učenci s posebnimi potrebami v času šolanja na daljavo Working with pupils with special needs during distance schooling Lucija Kupec CIRIUS Kamnik Novi trg 43a 1241 Kamnik, Slovenija lucija.kupec@cirius-kamnik.si POVZETEK that bad, because there's a lot of interesting and fun stuff going on there. Šolanje na daljavo je od učiteljev zahtevalo spremembo načina dela. V zelo kratkem času smo se morali prilagoditi danim In the initial work we devoted time to learning and handling new razmeram. To smo reševali na različne načine: s pregledovanjem tools. With the help of a teacher, pupils registered on portals with dostopnih programov, portalov, spletnih strani. Vse z namenom, interactive textbooks. It was followed by a course that smog a da bi učencem, kljub šolanju na daljavo, uspeli čimbolj približati regular, daily exercise via Skype. Students were explained the učno snov, ostati v stiku z njimi. Marsikdo je ugotovil, da šola le learning material in all subjects in grade 5 via Skype or via video. ni tako slaba, saj se tam dogaja tudi veliko zanimivih in zabavnih Instructions for consolidating and repeating the learning reči. substance were also given by e-mail. In accordance with the requirements, the volume of the learning substance was reduced V začetnem delu smo čas namenili učenju, spoznavanju in by 2 to 3 times and followed the learning material at a slower rokovanju z novimi spletnimi orodji. Učenci so ob pomoči pace. When we returned to school, we found that the students had učitelja opravili registracijo na portale z interaktivnimi učbeniki. a pretty good learning value. We also dealt with all the other Sledil je pouk, ki smo ga redno, vsakodnevno izvajali preko problems, dilemmas that students or parents had, via Skype. In Skype. Učenci so razlago učne snovi pri vseh predmetih v 5. this way, we also held speaking hours and a parenting meeting. razredu dobili preko Skype ali preko videoposnetkov. Navodila We estimate that we have gained quite a lot of valuable za utrjevanju in ponavljanje učne snovi so dobili še preko experience that we will use in the future, as long as there are such elektronske pošte. V skladu z zahtevami smo obseg učne snovi needs. zmanjšali za 2- do 3-krat in v počasnejšem tempu sledili učni snovi. Po vrnitvi v šolo smo ugotovili, da so učenci precej dobro KEYWORDS osvojili učno snov. Preko Skype smo reševali tudi vse ostale težave, dileme, ki so jih imeli učenci ali starši. Na ta način smo Pupils with multiple disabilities, adaptations, ICT, distance izvedli tudi govorilne ure in roditeljski sestanek. Ocenjujemo, da education smo dobili kar veliko dragocenih izkušenj, ki jih bomo uporabili v prihodnje, v kolikor bodo takšne potrebe. 1 UVOD KLJUČNE BESEDE Učenci so se v času šolanja na daljavo srečevali z različnimi Učenci z več motnjami, prilagoditve, IKT, šolanje na daljavo težavami, stiskami v domačem okolju. Pomembno je, da jim v takšnih trenutkih omogočamo čustveno varnost, stabilnost in ABSTRACT ustrezno samopodobo. Menimo, da so bilo to področje zelo Distance education has required teachers to change the way they pomembno v času karantene, saj so bili učenci prestrašeni, work. In a short period of time, we had to adapt to the situation. negotovi, zaskrbljeni zaradi trenutne situacije, prav tako tudi Teachers have dealt with this in different ways, but there is no njihovi starši. Zavedajo se, da so vsi opredeljeni kot rizični otroci doubt that this has required us to review possible programs, zaradi zdravstvenih težav, ki jih spremljajo. Od osmih učencev, portals, websites, so that, despite remote schooling, pupils can be ki so obiskovali 4. /5. razred jih je šest opredeljenih kot učenci z able to get as close to the learning material as possible, to stay in več motnjami. touch with them. A lot of people have found that the school isn't Čustvena varnost je pomemben temelj samopodobe in samospoštovanja. V kolikor otroku sporočamo, da ni pomemben lahko to trajno vpliva na njegovo samospoštovanje in samopodobo [4]. Samopodoba je kompleksen proces, ki vpliva Permission to make digital or hard copies of part or all of this work for personal or na številne procese pri otroku in je pomembna za nadaljnji razvoj classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full in uspešnost otroka. Jurišičeva [1] opredeljuje tri vidike, ki citation on the first page. Copyrights for third-party components of this work must vplivajo na samopodobo otroka: kognitivni, telesni in edukativni be honored. For all other uses, contact the owner/author(s). dejavniki. Kognitivni posegajo v oblikovanje otrokove Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). samopodobe ter vplivajo na razvoj vseh ostalih sposobnosti. 537 Telesni dejavniki vplivajo na razvoj telesnih zmožnosti in videza. so sporočila, glasovna sporočila, si pošiljali glasbo. . Starši so Edukativni trajajo vse od vstopa v šolo in tja do konca osnovne hitro ugotovili, da so učenci veliko časa na internetu in so šole. Pogosto je v ospredju le šolsko delo, ostala področja so nekateri omejili te prijateljske klepete v popoldanskem času. zanemarjena. Torej je izredno pomembno, kako bomo opogumili Pri družbi so učenci razlago učne snovi skoraj v celoti dobili učence, da se soočajo s to, povsem novo situacijo [3]. preko Skype. Pri ponavljanju in utrjevanju smo si pomagali z nalogami na učimse.com. Tako smo kombinirali skupinsko in individualno delo. Učiteljica je občasno posnela videoposnetek, 2 METODE DELA ga objavila na You tube kanalu. Učenci so ga sami predelali in V času šolanja na daljavo smo pouk izvajali na drugačen način. smo skupaj pri uri preko Skype ponovili novo znanje (slika1) ter Učitelji smo iskali različne načine, kako se povezati z učenci, dobili se še dodatno razlago, v kolikor jim snov ni bila jasna. priti v stik z njimi. V prvem tednu smo stik vzpostavili preko mesengerja, v naslednjem tednu smo nadaljevali preko Skype. V oddelku smo imeli 8 učencev z več motnjami. Vsi učenci so gibalno ovirani, stopnja le-te se razlikuje med njimi. Poleg videoklicev smo stik vzpostavili tudi preko e-maila, kjer smo jim ponudili možnost razlage učne snovi preko Skype. V roku enega tedna so se vsi učenci, ob pomoči staršev, sosedov, bratov ali sester uspeli prijaviti na Skype. Tako je pouk lahko stekel. Prve ure so bile namenjene pogovoru, potem smo oblikovali urnik. K temu smo vključili vse učitelje, ki poučujejo v oddelku. Tako je nastal nov urnik za delo preko Skype. Učenci so na začetku tedna dobili navodila za delo, kjer je bilo hkrati dopisano tudi, kaj vse bomo obravnavali preko Skype in kaj bodo opravili sami. V skladu s priporočili smo obseg učne snovi zmanjšali. Slika 1: turški vojaki Razlaga učne snovi je v celoti potekala preko Skype. Vključili smo možnost obrnjenega ekrana in ob razlagi naredili tudi Podobno smo obravnavali učno snov pri naravoslovju in tabelsko sliko s programom Slikar ali v Wordu. Tako so učenci tehniki. Kombinirali smo različne portale, saj so bili dostopni imeli tudi povzetek učne snovi, ki so jo prepisali v zvezek ali so interaktivni delovni zvezki in interaktivne naloge. Za ponovitev jo dobili v dokumentu po e-pošti. smo posneli nekaj kratkih videoposnetkov (slika 2), da so si jih Pri samem delu smo si pomagali s spletnimi portal iRokus - lahko ogledali še doma. https://www.irokus.si/ in učimte - https://www.ucimte.com/, kjer so bili brezplačno dostopni vsi delovni zvezki in učbeniki. Za samostojno delo in utrjevanje znanja smo uporabljali portal za učence učimse - https://www.ucimse.com/. Registracijo smo opravili že v šoli. V namen utrjevanja učne snovi pri matematiki smo posneli več videoposnetkov množenja in deljenja z eno in dvomestnimi števili. Tako so učenci lahko ponovili postopek izvedbe računske operacije. Videoposnetke smo posneli tudi za nekaj učnih snovi v okviru predmetov družbe ter naravoslovja in tehnike. Preverjanje in del ocenjevanj smo izvedli s pomočjo kvizov na Google obrazcih. Sprotno poročanje o opravljenem delu smo izvajali preko e- pošte (navadno staršev). Pri vseh the oblikah smo upoštevali prilagoditve, ki so jih učenci potrebovali, da so lahko sledili razlagi in učni snovi. Slika 2: fotosinteza 3 REZULTATI Posebno pozornost smo namenili obravnavi deljenja, le-ta Učenci so se s prijavo v Skype račun bili deležni redne učne navadno učencem dela veliko preglavic. Želeli smo, da starši razlage učne snovi v celoti. Pouk v živo je potekal pri vseh učence učijo na enak način, kot smo to delali preko Skype, da predmetih. Pri tem smo upoštevali tudi prilagoditve, ki so jih učenci ne bi bili dodatno zmedeni (slika 3). učenci potrebovali pri pouku. Na Skypu smo oblikovali skupino, kjer so učenci lahko spremljali pouk. Sprva so bili zadržani, že po parih dneh so bili zelo suvereni in so si oblikovali še eno skupino namenjeno klepetu brez prisotnosti učiteljev. Hitro so osvojili Skype, pisali 538 Glede na Priporočila za delo na daljavo smo v mesecu aprilu izvajali preverjanje znanja z Google obrazci (slika 6) Učenci so dobili link in so samostojno reševali preverjanje znanja. Tudi te smo reševali na različne načine, enkrat tako, da so jih reševali sami doma, brez videopovezave. Drugič smo jih reševali preko Skype. Pri tem so učenci izklopili zvok, da niso motili drug drugega. Slika 3: deljenje z enomestnim številom Zato smo posneli 8 video gradiv namenjenih deljenju in še množenju z eno- ali dvomestnimi števili. Posnetke smo objavili na You tube kanalu (slika 4), da so učenci lahko do njih dostopali tudi popoldne. Slika 6: preverjanje znanja V nadaljevanju smo na ta način izvedli tudi ocenjevanje znanja v mesecu maju. V skladu s priporočili [2] smo uporabili enake oblike in metode dela, uporabili smo učencem znano formo. Pred tem smo še analizo treh književnih del opravili s pomočjo Google obrazcev. 4 DISKUSIJA Uporaba IKT je pripomogla k temu, da smo lahko kljub izrednim razmeram izvajali pouka. Učenci so preko različnih spletnih orodij prejeli razlago, navodila za delo. Tako so učenci lahko bili Slika 4: množenje samostojni, starši niso bili okupirani s šolskim delom oz. bistveno razbremenjeni pri tem. Pri slovenščini smo utrjevali učno snov s pomočjo Google Starši so poročali o tem, da so učenci lahko na podlagi novih obrazcev. Oblikovali smo kviz s pomočjo katerega smo najprej znanj samostojneje sledili pouku preko Skype in spoznavali to spletno aplikacijo. Prvo reševanje smo izvedli samostojnejšemu reševanju nalog v času izven pouka. skupaj, nato so učenci dobili link v skupino Skype. Sledilo je Ugotovimo smo, da se lahko bistveno bolj prilagajamo samostojno delo (slika 5). Učenci niso imeli večjih težav. Je bila individualnemu tempu učenca, njegovim posebnostim, pri tem pa koristna povratna informacija, glede tega, kateri tip vprašanj pa upoštevamo prilagoditve, ki jih učenec potrebuje. Učenci so učencem povzroča več tehničnih težav. To je bil odprti tip, kjer bili okupirani le z učno snovjo, ni bilo dodatnih terapij ali so sami morali zapisati odgovor. Kot pravilen odgovor se šteje le psiholoških obravnav. Po zaključku pouka so bili doma, niso tisto, kar obkljuka učitelj oz. ponudi kot pravilno rešitev. V porabili časa za terapije ali prevoz. Nekateri porabijo več kot dve kolikor učenec besedo napačno zapiše, med dvema besedama ne uri dnevno samo za prevoz v šolo in nazaj. Posledično so bili zapiše presledka, uporabi malo začetnico namesto velike itd. je učenci bolj spočiti. Slabo je bilo to, da so lahko socialne stike odgovor napačen. Na to smo učence še posebej opozorili po ohranjali le preko videoklicev, telefonskih pogovorov, ni bilo koncu reševanja kviza, saj smo skupaj pregledali, kako so spontanih pogovorov in druženj po hodnikih šole. reševali naloge. Znanja, ki smo jih pridobili v času šolanja na daljavo bomo lahko Naslednji dan so še enkrat reševali isti kviz z namenom, da uporabili tudi v prihodnjem šolskem letu, izkušnje nadgradili z popravijo napake. Delno nam je to uspelo odpraviti. novimi. Menimo, da je pomembno, da govorimo o pridobljenih izkušnjah, širimo znanje, iščemo nove rešitve, saj je to način za kvalitetnejši napredek v profesionalnem razvoju posameznega učitelja. 5 ZAKLJUČKI Šolanje na daljavo je prineslo nove izzive iz katerih smo se mnogo naučili, bili postavljeni pred nove izzive, tako učenci kot učitelji. Dolgoročno gledano smo pridobili pomembne izkušnje, učitelji in učenci smo pokazali, da zmoremo veliko, pridobili smo Slika 5: Google obrazci – vaje za utrjevanja ogromno znanj in izkušenj na področju uporabe IKT. Ključno je, 539 da se moramo ves čas izpopolnjevati, da bomo lahko nadgradili [2] Sklepom o ukrepih za nemoteno opravljanje vzgojno- svoje znanje, izboljšali pristope in metode dela v primeru izobraževalnega dela v osnovnih šolah v šolskem letu ponovnega šolanja na daljavo. Nedvomno bomo pogumneje 2019/2020. Ljubljana. MIZŠ. stopali po tej poti. [3] Youngs, R. R. (2000). Šest temeljnih prvin samopodobe. Ljubljana: Educy. LITERATURA IN VIRI [4] Izobraževanjem na daljavo v posebnih razmerah, priporočila za ocenjevanje znanja v osnovni šoli. (2020). [1] Jurišič, M. (1999). Samopodoba šolskega otroka. Ljubljana: Zavod za šolstvo. Ljubljana: Pedagoška fakulteta. 540 Uporaba IKT v času šolanja na daljavo pri učenki s težko motnjo v gibalnem razvoju Use of ICT during distance learning in schoolgirls with difficult disturbance in motion development Lucija Kupec CIRIUS Kamnik Novi trg 43a 1241 Kamnik, Slovenija lucija.kupec@cirius-kamnik.si POVZETEK methods allow the student to stay active within her capabilities while stimulating the development which motivated further Pri učencih s posebnimi potrebami je potrebno ob pomoči growth, enabling her to make up for any deficit that were to arise učitelja najti ustrezno prilagojeno izobraževalno tehnologijo, ki due to a longer period of absence. bo učencu v pomoč pri doseganju vsebin v vzgojno- izobraževalnem procesu. To od učitelja zahteva nenehen razvoj KEYWORDS in raziskovanje tega področja, da lahko, glede na otrokove posebne potrebe najde ustrezne programe ali aplikacije. Pri delu ICT, mobility-impaired pupils, adaptation, distance learning z učenko z težko gibalno oviranostjo je to precej zahtevno delo, saj je potrebno poiskati takšne programa, ki ji bodo olajšali delo 1 UVOD in hkrati omogočili njen napredek. V času šolanja na daljavo smo pouk in razlago učne snovi pri matematiki v celoti nudili preko Delo z otroci z gibalno oviranostjo zahteva od učitelja številne Skype. V pomoč so nam služili različni spletni učbeniki, delovni prilagoditve za dosego ciljev. Deklica je težko gibalno ovirana zvezki, Power point, Google obrazci in Geogebra. Uporabljene učenka, ki je povsem odvisna od pomoči odrasle osebe. Gibalno metode učenki omogočajo, da je aktivna v skladu z zmožnostmi, ovirani otroci imajo prirojene ali tekom življenja pridobljene razvija svoje sposobnosti, je izredno motivirana za delo, lažje okvare gibalnega aparata, perifernega ali centralnega živčevja. nadomesti snov v času daljše šolske odsotnosti in pridobiva nova Razlikujemo otroke z: lažjo, zmerno, težjo, težko gibalno znanja. oviranostjo [2]. Otroci s težko gibalno oviranostjo so funkcionalno popolno odvisna od druge osebe oseba, zaradi hude KLJUČNE BESEDE motnje, ne zmorejo samostojnega gibanja. Le-to je mogoče z IKT, gibalno ovirani učenci, prilagoditve, šolanje na daljavo električnim vozičkom, koliko je le-to samostojno, je odvisno še od funkcij rok, ki so pogosto slabe. Delno ali malo lahko pomaga ABSTRACT pri osnovnih dnevnih opravilih, deklica ima tudi dihalno When talking about students with special needs, it is crucial to podporo. Pri dnevnih opravilih je povsem odvisen od pomoči work with the pupil`s teachers in order to find the optimal druge osebe, tudi zaradi motnje kontrole sfinktrov [1]. Hude technology that will enable them to achieve the goals set forth in motnje so prisotne pri orientaciji, senzomotorični integraciji, the educational plan. This requires the teacher to constantly zaznavanju in občutenju dražljajev. Pri šolskem delu potrebuje explore this area in order to find the best possible tool adapted to stalno pomoč druge osebe, prilagoditve pri sami izvedbi naloge, the child`s specific needs. When working with a physically okolja in pripomočkov (individualno prilagojen in izdelan sedež, impaired pupil, this is particularly challenging as it is hard to find miza, IK tehnologija) [2]. the best balance between a program that eases the process for the Učenka, ki je težko gibalno ovirana je kljub vsem težavam student in all fields while still challenging and allowing them to zelo motivirana za delo z IKT. Želi si pridobivati vedno nova evolve in all aspects. During distance learning, we provided znanja, biti v stiku s sošolci,kjub daljši odsotnosti. Vse učne instruction and explanation of the subject matter in mathematics obveznosti opravi kot ostali, v kolikor je le mogoče se udeleži še entirely via Skype. We were helped by various online textbooks, dodatnih matematičnih in drugih tekmovanj. V tem šolskem letu workbooks, Power point, Google forms and Geogebra. The smo se srečevali z drugačno obliko metoda, ki je od učiteljev in učencev zahtevala veliko mero prilagoditev. Šola na daljavo je lahko potekala bolj utečeno v kolikor je učitelj in učenci vešči uporabe IK tehnologije. Glede na to, da je učenka, ki jo Permission to make digital or hard copies of part or all of this work for personal or omenjamo zgoraj vešča dela z različnimi programi, aplikacijami classroom use is granted without fee provided that copies are not made or distributed nam to ni bila posebna ovira. Ključno pri vsem je bilo, da smo se for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must prilagajali zdravstvenemu stanju in psihofizični kondiciji deklice. be honored. For all other uses, contact the owner/author(s). V času šolanja na daljavo smo se lahko 100 % prilagodili temu, Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 541 urnik oblikovali glede na njene potrebe, na ta način je učenka izvrstno delovala. 2 METODE DELA Delo v času šolanja na daljavo je zahtevalo od učitelejev uporabo drugih oblik dela, ravno IKT nam omogoča povezavo tudi v tem času. Na podlagi njenega predznanja in izkušenj smo uvajali IKT na večjih področjih. Sama bom predstavila uporabo IKT pri matematiki. Pouk je v celoti potekal preko Skype, dnevno dve do tri uri. Oblikovali smo urnik, poseben za vsak razred za delo Slika 2: ponovitev učne snovi na Mojamatematika.si. preko Skype. To smo učitelji uskladili znotraj aktiva od 6. do 9. razreda. Na ta način smo z delom začeli že v drugem tednu Za razlago učne snovi koti smo pri merjenju uporabljli e- šolanja na daljavo, učenci so v tem času odprili Skype račune. V učbenik in DZ MK za 5 razred. Učenka je lahko sledila risanju z oddelku je manjše število učencev. Pri oblikovanju urnika smo geometrijskim orodjem, saj na straneh, kjer so naloge s tega upoštevali tudi želje učencev v kolikor je bilo to možno. Delo pri področja imajo učenci možnost uporabe geotrikotnika, šestila… matematiki je potekalo preko Skype. V začetku tedna so učenci Preverjanje znanja ob koncu posameznega učnega sklopa je dobili navodila za delo, kjer je pri posamezni snovi pisalo kaj učenka izvajala preko Google obrazcev, kar je omogočalo njeno bomo predelali preko Skype in kaj po njihovo samostojno delo v samostojnost. domačem okolju. Delo preko Skype je potekalo tako, da smo se pogovorili kdo je kaj naredil, preverili rezultate in razložili naloge v kolikor česa 3 REZULTATI niso znali. Učenka, ki ima težko motnjo v gibalnem razvoju je Učenka je v svoje delo vložila veliko truda in energije, da sploh sledila razlagi, poročala o opravljenem delu. Zaradi sorojencev lahko sodeluje pri pouku. Njeno zdravstveno stanje ji ne dopušča, starši niso mogli biti prisotni ves čas razlage, zato je učenka da bi delala več kot 45 minut. Delu sledi osnovne higienske in tabelske slike razlage preko Skype dobila v Wordovem prehrambene zahteve, pri Kateri potrebuje pomoč. Ravno zaradi dokumentu. Pri razlagi, ponavljanju, reševanju nalog (slika 1) tega je izjemno pomembno, da lahko sama opravi delo, reši smo uporabljali obrnjen pogled Skypa, da so pred sabo imeli naloge in sledi razlagi. Učenka je izjemno bistra, potrebuje tabelsko sliko razlage učne snovi. To je bilo še posebej ustrezne načine, da lahko učno snov osvoji. Pomembna je tudi pomembno, ko smo se srečevali z geometrijskimi vsebinami. izkušnja, videti, spoznati učno snov preko različnih poti. Deklica je zelo motivirana ze delo, želi si sodelovati pri vseh aktivnostih, delati zapise, poročati, vendar ji njeno zdravstveno stanje tega ne dopušča. Učenka je torej sledila razlagi, reševala naloge in svoje ugotovitve podajala preko Skype. Zapis zanjo ni bil potreben, sposobna je zelo veliko miselnih operacij izvesti na pamet. Sledilo je samostojno delo. Tu je bilo pomembno, da smo deklici ponudili orodja s katerimi je reševala naloge. Eno izmed orodij s katerimi se je spoprijemala znotraj vsebin krožnice je Geogebra (slika 3), ki ji omogoča samostojno delo. Slika 1: ponovitev učne snovi. Učenka je sledila razlagi, kasneje so pa to tabelsko sliko dobili pri mailu in prilepili v zvezek. Pri sami razlagi smo uporabljali e-učbenike založbe Rokus, ki so bili v tem času prosto dostopni in so nam močno olajšali delo. Vsi učenci so lahko dostopali do njih s preprosto registracijo. Hkrati smo kot uvod, zanimivost, dodatno motivacijo večkrat uporabljali naloge na spletni strani Mojamatematika (slika 2). Učenka je bila pri tem samostojna, ni potrebovala pomoči, Slika 3: delo z Geogebro po navodilih naloge v učbeniku ponovila je učno snov, ki je primerna za 5. razred, vendar so lahko koristne tudi šestošolcem. Vsem, ne samo učenki, ki ima Zaradi lažjega rokovanja je pri risanju kotov uporabila številne omejitve. Na portalu Mojamatematika učitelj registira interaktivne delovne zvezke Mladinske knjige [3], ki omogočajo, učence in jim pripravi naloge, tako lahko spremlja kaj so reševali da učenec znotraj strani, kjer so naloge uporablja geometrijsko in kako so bili pri tem uspešni. orodje. Tako je lahko sama načrtovala risanje kotov z različnimi stopinjami. Ta način dela je predstavila tudi sošolcem kot 542 zanimivost. Ostali učenci so svoje znanje urili z risanjem v željenih ciljev v času šolanja na daljavo ter lažje doseganje cilje, zvezek. ko je zaradi počitka ali preventive odsotna dalj časa. Deklica Zaradi zdravstvenih težav vedno ni mogla sodelovati pri urah. zmore le nekaj preprostih gibov s prsti, ravno toliko, da premika Razlago smo ji posneli s funkcijo, ki jo omogoča videoklic in miško in uporablja prste. poslali preko Skype. Hkrati je dobila tabelsko sliko. Tako, da je Zelo je motivirana za nove oblike dela, da se kaj novega nauči. preko slušnega in vidnega kanala osvojila učno snov. Hitro osvoji nove aplikacije in programe. Preverjanje in ocenjevanje znanja smo izvedli preko Google Pri tem je pomembno, da učitelj sam skrbi za razvijanje obrazcev , v skladu s priporočili [4]. Program in način dela je digitalnih kompetenc. Zakaj je to tako pomembno? Učitelj mora hitro osvojila. Rezultati njenega dela so bili zelo dobri in razvidni raziskovati in iskati različne aplikacije in poznati posebnosti iz slike 4. učenka, da jo lahko uporabi v praksi. Mora zelo dobro poznati prednosti in slabosti programa, aplikacije, da lahko uvidi kaj bo učenec s težko gibalno oviranostjo lahko uporabil, presodil kaj ni primerno za uporabo za učence s tako motnjo, ter da raziskuje vse te aplikacije in programe na spletu. 5 ZAKLJUČKI Znanje je njeno »orožje«. Na ta način se dokazuje, z znanjem in premikanjem meja nemogočega glede na njeno zdravstveno stanje. Uporabljene aplikacije in programe bo lahko uporabljala in nadgrajevala tudi v prihodnje ter se še dodatno izpopolnjevala na tem področju. Slika 4: rezultati ocenjevanja znanja Preteklo delo in številne izkušnje, ki smo jih učitelji dobili na tem področju v času šolanja na daljavo bomo lahko uporabljali Pogor preko Skypa je omogočal stik s sošolci. Izjemnega tudi v prihodnje. Te izkušnje so res zelo dobrodošle, saj nas čaka pomena zanjo je Skype predstavljal tudi komunikacijo s sošolci. negotova prihodnost glede načina poučevanja v prihodnje. Deklica bi bila odsotna tudi, če ne bi bilo karantene. Zdravstveno stanje ji namreč ne dopušča, da bi v času prehladnih obolenj obiskovala šolo. Pouk, razlaga preko Skype je tudi pomemben LITERATURA IN VIRI socializacijski vidik otrok, ki so veliko časa odsotni. Deklici zelo [1] Izobraževanjem na daljavo v posebnih razmerah, veliko pomeni pogovor s sošolci, drug drugega vidijo, se priporočila za ocenjevanje znanja v osnovni šoli. (2020). pogovorijo kaj je novega na šoli. Učenka je stara trinajst let in Ljubljana: Zavod za šolstvo. ima veliko željo po druženju s sošolci kot ostali njeni vrstniki. [2] Logaj, V., Zadnik, A., Korenčan, P., Lisjak Banko, V. in Po koncu karantene se zaradi slabe epidemiološke slike Antosiewicz, K. (2014). Vzgojni program za gibalno učenka žal ni mogla vrniti v šolo. Šolanje je nadaljevala doma. V ovirane otroke in mladostnike na dnevni obliki času razlage smo se pri matematiki ponovno povezali preko usposabljanja. DOI: Skype. Razlika je bila to, da so ostali učenci bili v šoli, ona je http://www.mizs.gov.si/fileadmin/mizs.gov.si/pageuploads razlago spremljala preko Skype. Naloge smo reševali na tablo in /podrocje/posebne_potrebe/programi/Gibalno_ovirani_bre projicirali na projektor. Tako, da smo s funkcijo obrnjenega z_namestitve.pdf. zaslona na Skype dosegli to, da je učenka lahko sodelovala pri [3] Rugelj, M.,Bogataj, T., Drašler T., Kozarski (2019). pouku in bila v stiku z nami. Matematika 5. Interaktivni delovni zvezek za osnovno šolo. DOI = https://www.ucimte.com/?q=isdz/#! [4] Sklepom o ukrepih za nemoteno opravljanje vzgojno- 4 DISKUSIJA izobraževalnega dela v osnovnih šolah v šolskem letu Uporaba omenjenih programov, aplikacij omogoča, da učenki 2019/2020. Ljubljana. MIZŠ. razvijamo digitalno pismenosti, ki ji omogoča lažje doseganje 543 Spletna varnost pri pouku na daljavo v času epidemije COVID-19 Online safety during class in time of COVID-19 epidemic Luka Kušar Arnes Tehnološki park 18 1000 Ljubljana, Slovenija luka.kusar@arnes.si POVZETEK pasteh, na katere lahko naletijo pri uporabi popularnih orodij za izvajanje izobraževanja na daljavo. Poleg tega so še večji pomen V času epidemije COVID-19 se je delo izobraževalnih ustanov v pridobili tudi Arnesovi spletni tečaji, ki uporabnike izobražujejo veliki meri preseililo na splet. S tem je bilo tudi večje število o uporabi naših storitev in IKT opreme na izobraževalnem uporabnikov izpostavljenih spletnim nevarnostnim. Poznavanje področju. Usposobljen uporabnik namreč ni samo opremljen z delovanja spleta in IKT tehnologij je ključnega pomena za znanjem za uporabo določene storitve, ampak se s pridobljenimi zagotavljanje uporabnikove varnosti. Arnes s svojmi množičnimi informacijami lažje in bolje znajde pri uporabi IKT in spleta na spletnimi tečaji želi ponuditi uporabniku znanja, s katerimi bo na splošno, kar bistveno pripomore k njegovi spletni varnosti. V spletu deloval varno. prispevku bom prek analize preteklih izkušenj in relevantne KLJUČNE BESEDE literature poskušal prikazati, kako je epidemija COVID-19 vplivala na večjo uporabo spleta in IKT pri izvajanju MOST, internetna varnost, učitelji, spletna učilnica, Arnes, izobraževalnega procesa ter pomen izobraževanja uporabnika za epidemija, COVID-19, izobraževanje na daljavo zagotavljanje tako njegove varnosti na spletu kot izpeljave ABSTRACT kakovostnega izobraževalnega procesa. During the COVID-19 epidemic, work of educational institutions was mostly transferred online. As a consequence, a large number 2 POVEČANA UPORABA SPLETA of users became exposed to the dangers of internet. The 16. marec 2020 je slovensko šolstvo pričelo z izobraževanjem na knowledge of safe web usage and communication technologies daljavo. Arnes je povečano uporabo storitev pričakoval, is crucial in securing the users safety. ARNES offers massive nakazovala se je že med vikendom, ko so mnogi učitelji pričeli s open online courses, which offer the user knowledge that enables pripravami na izobraževanje na daljavo. V ponedeljek je tako him to stay safe online. prišlo do izjemnega zvišanja števila uporabnikov storitev [1]. Do 22. marca 2020 se je količina internetnega prometa na stičišču KEYWORDS omrežij SIX in sicer je bila količina prenosa podatkov 130 Gbit/s MOOC, internet safety, teachers, online classroom, ARNES, [1]. epidemic, COVID-19, distance education 3 KATERA ORODJA UPORABITI? 1 UVOD Veliko število šol se je znašlo v situaciji, za katero niso imele v Z namenom varovanja zdravja v času epidemije COVID-19 so naprej pripravljenega načrta. Postavljene so bile pred dilemo, pristojne službe prekinile konvencionalno obliko pouka in kako se lotiti izobraževanja na daljavo. Predvsem je težavo namesto tega uvedle t.i. izobraževanje na daljavo. Učenci in predstavljala izbira orodij, ki so uporabni za izvajanje tega tipa učitelji tako niso bili več fizično prisotni na izobraževalnih izobraževanja. Na voljo je veliko različnih možnosti, s tem pa se ustanovah, izobraževalne aktivnosti pa so izvajali predvsem s pojavljajo za uporabnike tudi varnostna tveganja. Večina šol je pomočjo IKT in spleta. S povečano uporabo spleta je prišlo tudi iskala videokonferenčni sistem, ki bi omogočal vsaj približek do ogroženosti spletne varnosti uporabnikov storitev. Arnes je dela v razredu. Veliko učiteljev je hitro pričelo z uporabo orodja uporabnike v tem času poskušal še bolje informirati o možnih Zoom, ki je poleg enostavne uporabe tudi brezplačen, vendar vsebuje nekaj prikritih varnostnih groženj ter pomanjkljivosti pri ohranjanju uporabnikove zasebnosti. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full 4 PRIKRITE PASTI ORODIJ citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Z uporabo brezplačnih orodij, ki jih ponujajo zasebna podjetja, Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia uporabniki pogosto nevede izpostavljajo svojo zasebnost na © 2020 Copyright held by the owner/author(s). 544 spletu. Takšna orodja so brezplačna v striktno monetarnem tehnologija tista, ki mu povzroča težave. To je v veliki meri smislu, saj uporabnik njihove uporabe ne plača z denarno valuto. posledica nepoznavanja spletnega okolja in jo z ozaveščanjem o Podjetja v dobiček spremenijo samo rabo orodja, saj zbirajo vrsto potencialnih pasteh uporabe IKT in spleta lahko v veliki meri podatkov, ki jih nato prodajo drugim zainteresiranim podjetjem. odpravimo. [6]. Večina spletnih prevar in ostalih groženj za Uporabnikovo dovoljenje za takšno delovanje pridobijo z posameznikovo spletno varnost namreč računa na naivnost in njegovim pristankom na pogoje rabe, v katerih so zelo implicitno nepremišljenost uporabnika. V veliki večini primerov predvsem nakazane možne uporabe različnih podatkov, ki jih podjetje prevare uporabnika postavijo v položaj, ko se mora hitro odzvati, pridobi prek uporabnikovega dela z orodjem. Največja težava saj ga prepričujejo, da se mu bo v nasprotnem primeru zgodilo takšne prakse leži v dejstvu, da podjetja namerno izpostavljajo nekaj neprijetnega, denimo da bo izgubil prostor na strežniku za zgolj monetarno brezplačnost orodja, pri tem pa uporabnika ne svojo elektronsko pošto ali pa bo nagrada, ki jo je zadel v obvestijo neposredno, da bo na drugačen način plačal svojo nagradni igri, na katero se ni prijavil, šla drugi osebi. Tako uporabo [2]. prevaranti računajo na uporabnikov hiter, čustven in Tisti uporabniki, ki se zavedajo, da bodo uporabo storitev nepremišljen odziv ter na ta način dosežejo svoj namen, ki je plačali s svojimi podatki, pogosto temu ne namenjajo dovolj lahko raznolik – vse od pridobitve osebnih podatkov do nakazila pozornosti. Argumentacija je pogosto v smislu »saj ne skrivam denarja [7]. ničesar« ali pa »koga sploh zanimam«. V teh primerih gre za Kot smo zapisali v našem vodiču za uporabo orodja Zoom, je lažen občutek varnosti, saj se uporabniku zdi, da je nepomemben ena izmed težav videokonferenčnih sistemov vpadanje ali pa so njegovi podatki nepomembni. Ne zaveda se, da gre nepovabljenih gostov v konferenco. S takim primerom so nas dejansko za ogromne količine podatkov, ki so marsikomu, še kontaktirali iz slovenske osnovne šole. Pri izvajanju pouka na posebno v oglaševalski industriji zelo zanimivi in uporabni. Na daljavo prek Arnesovega videokonferenčnega orodja Arnes VID podlagi tega je uporabnik izpostavljen osredotočenemu je prišlo do vpada nepovabljenega gosta, ki se je izdajal za oglaševanju za določene izdelke. Tu pogosto ne gre za klasični Arnesovo tehnično podporo. Ta je učiteljico s pretvezo, da koncept oglaševanja, ki ga uporabnik prepozna, dejansko je potrebuje njeno sodelovanje za odpravljanje tehnične napake, podvržen nečemu, kar bi lahko skorajda opredelili kot prepričal, da pritisne bližnjico na tipkovnici, ki zapre delovanje »psihološko vojskovanje«, oziroma tehnikam, ki uporabljajo programa. Vse skupaj je storilec predvajal v živo, posnel in takšne elemente za dosego cilja prodaje določenega izdelka, pri objavil na video portalu YouTube. Šola je želela preveriti, če je čemer je lahko ta »izdelek« tudi določena politika, informacija bila res vpletena naša tehnična podpora, hoteli pa so se tudi ostro ali dezinformacija, ali pa je uporabnik mimo njegove vednosti odzvati proti storilcu. napeljan k spremembi vedenjskih vzorcev, da to olajša prodajo Šlo je za potegavščino, ki jo je storilec izvedel za zabavo neke storitve [3]. množice gledalcev na njegovem spletnem kanalu. V tem primeru Problematično je tudi dejstvo, da v veliko primerih ne vemo, pride v ospredje poznavanje IKT opreme in delovanja spleta, na kje se zbrani podatki fizično nahajo. Pogosto je to na strežnikih, dveh področjih. Prvo je zavedanje, da je storilec prišel do dostopa ki so locirani v državah, kjer zakonodaja zelo slabo ščiti do videokonference s pomočjo enega od udeležencev. Sam uporabnika [4]. namreč ne bi mogel naključno ugotoviti imena konference. V Arnes želi s svojim delom pri ozaveščanju javnosti o spletni kolikor ima storilec pomoč udeleženca, se lahko izogne ugibanju varnosti uporabnika opremiti z informacijami, na podlagi katerih gesla, če je z njim zaščitena konferenca, saj mu tega priskrbi bo lahko sprejel najboljše odločitve, ki se tičejo njegove varnosti udeleženec. Šola se lahko s poznavanjem delovanja in zasebnosti na spletu. Zastiranje dejanskega mehanizma videokonferenčnega sistema tako nemudoma odzove in začne z delovanja brezplačnih orodij je namreč zavajajoče za zbiranjem informacij udeležencev učne ure, če želi iskati storilca. neinformiranega uporabnika, ki je zaradi tega že v izhodišču Drugo področje pa je splošno poznavanje delovanja IKT potisnjen v smer neoptimalne odločitve. Konča odločitev o opreme oziroma v tem primeru računalnika. Bližnjica na uporabi nekega orodja je seveda v rokah posameznika, moralno tipkovnici, za katero je napadalec želel, da jo pritisne učiteljica, in etično pa je, da to odločitev sprejme na podlagi kakovostnih je znana pri tistih, ki bolje poznajo tehnologijo. Tako lahko informacij, ki so mu na voljo. vidimo, na kakšen način se akumulira splošno znanje o IKT Z namenom ozaveščanja uporabnikov pri uporabi storitve opremi in delovanju spleta ter vpliv akumulacije znanja na našo Zoom smo to pomlad na naši spletni strani objavili kratek vodič, spletno varnost. Učiteljica bi denimo lažje prepoznala namero, ki razkriva tako poslovni model Zooma kakor tudi povsem če bi poznala bližnjico. tehnične informacije, kako poskrbeti za varnosti in zasebnost ob Čeprav je šlo za potegavščino učencev, lahko v tem spletnem uporabi orodja, seveda v okviru zaščite, ki je pri uporabi sploh incidentu prepoznamo veliko večino običajnih mehanizmov, ki na voljo uporabniku. Izpostavili smo tudi najpogostejše oblike jih uporabljajo prevaranti na spletu. Storilec uporablja lažno spletnih incidentov, ki se dogajajo pri uporabi tega orodja. S tem identiteto, v tem primeru se izdaja za člana Arnesove tehnične smo želeli uporabnika informirati in mu omogočiti, da takšno podpore, z namero, da pridobi kredibilnost in žrtev prepriča v brezplačno orodje uporablja varno in z zavedanjem, da uporabo sodelovanje. Spletni prevaranti se zelo pogosto predstavljajo kot plačuje na drugačen način, in ne z denarjem. Informiranost banke, velika podjetja ali druge znane ustanove. [7]. Storilec je uporabnika je v takšnih razmerah po našem mnenju ključna [5]. prav tako učiteljico postavil v situacijo, kjer je morala reagirati hitro, brez premisleka o njegovi zahtevi. Verjetno ni imela določenega znanja o delovanju računalnika in spleta, zato je bila 5 SPLETNI INCIDENTI zaradi tega še lažja tarča. Spletni prevaranti namreč pogosto za Varnost posameznika na spletu je skoraj popolnoma v rokah svoj namen žrtev silijo v hitre odločitve, prav tako pa jim olajša njega samega, čeprav ima uporabnik pogosto občutek, da je delo, če žrtev ni podkovana v poznavanju spletnega okolja. Na 545 teh primerih lahko vidimo, da bistveno vlogo igra človeški faktor, tematiki [8]. Poleg naštetih Arnes pripravlja še nove MOST-e, ki tehnologija sama po sebi pa ne predstavlja nekega posebnega bodo obravnavali druge tematike, vezane na uporabo spleta in tveganja. Takšne prevare so pogoste tudi v drugih sferah IKT. življenja, spletno okolje je zgolj bolj izpostavljeno zaradi slabšega znanja splošne javnosti o varni uporabi spletne tehnologije. Ker se IKT in splet pogosto prikazuje kot 7 ZAKLJUČEK kompliciran in zahteven za uporabo, se s tem ustvarja tudi V času epidemije COVID-19 je bil slovenski izobraževalni predsodke, da je sama tehnologije bolj nevarna za uporabnika, sistem prisiljen v vzpostavitev izobraževanja na daljavo do konca kot je v resnici. šolskega leta 2019-20. S tem so bili učitelji in učenci prisiljeni v uporabo spleta in IKT v izobraževalne namene. S povečanjem 6 IZOBRAŽEVANJE ARNESOVIH števila uporabnikov se je povečala tudi možnost za spletne napade in incidente, še posebno zaradi dejstva, da je bilo veliko UPORABNIKOV novih uporabnikov slabše podkovanih v uporabi spletnih orodij. Pomemben del Arnesove vloge v raziskovalno-izobraževalni Želja Arnesa je, da bi vsak od uporabnikov, ki za svoje izvajanje skupnosti je tudi izobraževanje uporabnikov in prenos znanja. Ta ali sodelovanje v izobraževalnem procesu uporablja splet ali IKT poteka v različnih oblikah, od predavanj, letne konference Mreža opremo, postal kompetenten in izobražen za uporabo teh znanja, priprave strokovnih delavnic, strokovnih pripomočkov in tehnologij. Tako bo suveren pri uporabi, izobraževanje bo množičnih odprtih spletnih tečajev, ki jih označujemo s kratico kakovostno, prav tako pa bo poskrbel za svojo varnost na spletu. MOST (tu gre za prevod izvirnega angleškega naziva MOOC oz. S tem namenom Arnes organizira množične spletne odprte Massive Open Online Course.) [8]. tečaje, ki jih izvaja pod kratico MOST. Uporabnik lahko z Na Arnesov MOST se lahko prijavi vsak, ki ga obravnavana nabiranjem znanja o uporabi spleta in IKT opreme zagotovi zase tematika zanima. Tečaji potekajo na daljavo, udeleženci pa prek in za druge kakovosten učni proces, tako v primeru izobraževanja spletne učilnice dobijo gradiva in naloge, ki jih je potrebno za na daljavo kot običajnega šolskega dela. IKT in splet namreč ob uspešno končanje tečaja predelati in opraviti. Za sodelovanje na ustrezni rabi bistveno olajšata delo učencem kakor učiteljem ter tečaju je potreben zgolj dostop do spleta [8]. s tem pripomorejo h kvalitetni izvedbi izobraževalnega procesa. MOST ponuja enostavno in praktično rešitev za vsakogar, ki se želi izobraziti o tematiki, ki je obravnavana v posameznem tečaju. Ker poteka na daljavo, sodelujočim ni potrebno biti VIRI prisoten na izbrani lokaciji, kar marsikomu prihrani veliko časa [1] Arnesov pogled: Se bo internet med karanteno zlomil? Arnes. in olajša sodelovanje. Prav tako je velika večina časovnega Dostopno prek: http://arnes.splet.arnes.si/arnesov-pogled- razporeda v rokah sodelujočega. Tečaji imajo datume začetka in se-bo-internet-med-karanteno-zlomil/ (24.8.2020) konca ter določene roke za oddaje nalog, če jih tečaj predvideva, [2] Sami prodajamo svojo zasebnost. Safe.si Dostopno prek: sama obdelava gradiv in drugo delo pa si razporedi uporabnik https://safe.si/novice/sami-prodajamo-svojo-zasebnost sam. Tako si lahko organizira čas po svojem okusu, saj mu ni (24.8.2020) treba biti prisoten za računalnikom ob določeni uri, temveč so [3] What Does It Mean For Social Media Platforms To "Sell" mu gradiva na voljo takrat, ko so objavljena v spletni učilnici. Our Data? Forbes. Dostopno prek: Arnesovi MOST-i obravnavajo veliko različnih tem, vsem pa https:/ www.forbes.com/sites/kalevleetaru/2018/12/15/what je skupno, da so vezane na uporabo IKT ali spleta. MOST -does-it-mean-for-social-media-platforms-to-sell-our- Digitalne identitete obravnava skrb za baze uporabnikov, data/#387a90992d6c (24.2.2020) Vodenje in upravljanje VIZ prikazuje uporabo IKT in spleta za [4] Data Sovereignty and the GDPR; Do You Know Where namen učinkovitega vodenja VIZ, Upravljanje brezžičnih Your Data Is? Archive 360. Dostopno prek omrežij predstavlja, kako čim lažje urediti podporo uporabnikom https://www.archive360.com/blog/data-sovereignty-and- za dostop do brezžičnega omrežja eduroam, Spletna predstavitev the-gdpr-do-you-know-where-your-data-is (24.8.2020) VIZ predstavi ustvarjanje spletišča za uporabnikovo ustanovo, [5] Zoom – da ali ne in kako ga varno uporabljati? Arnes. Uporaba mobilnih naprav v VIZ prikazuje smiselno uporabo Dostopno prek: http://arnes.splet.arnes.si/zoom-da-ali-ne- mobilnih naprav pri pouku, Spletno anketiranje uči ustvarjanje kako-varno-uporabljati/ (24.8.2020) spletnih anket v orodju 1KA, Spletne učilnice predstavljajo [6] Promoting Personal Responsibility for Internet Safety. uporabo in ustvarjanje spletnih učilnic, E-listovnik seznani Larose, Robert; Rifon,Nora J.; Enbody, R.J. uporabnika s funkcionalnostmi in uporabo e-listovnika. Poleg teh Communications of the ACM 51 (3): 71 – 76. naštetih Arnes dvakrat letno izvede tudi MOST Varna raba [7] Willing to be scammed : how self-control impacts Internet interneta in naprav, ki obravnava veščine, pomembne za scam compliance. Modic, David. Dostopno prek prepoznavanje spletnih nevarnosti in za zaščito uporabnikove https:/ ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.579856 varnosti na spletu ter osebnega zdravja. Na temo spletne varnosti (24.8.2020) je učiteljem na voljo tudi MOST Znam več, varnost na spletu ni [8] Izobraževanje. Arnes. Dostopno prek: nikoli odveč, kjer učitelj prejme v uporabo že opremljeno spletno http://arnes.splet.arnes.si/izobrazevanje/ (24.8.2020) učilnico in sam vodi skupino učencev čez proces učenja o 546 Timsko delo kot osnova hipoterapije Teamwork as a basis for hyppotherapy Ana Lambić, Tilen Medved, Pia Cerkovnik, Ana Šabec, Metka Podobnik Matija Jerin Špela Ramšak Univerza v Ljubljani, Veterinarska Univerza v Mariboru, Fakulteta za Univerza v Ljubljani, Medicinska fakulteta organizacijske vede fakulteta Gerbičeva 60 Kidričeva cesta 55a Vrazov trg 2 1000 Ljubljana, Slovenija 4000 Kranj, Slovenija 1000 Ljubljana, Slovenija ana.lambic@student.um.si Nikita Polner, Tilen Breznikar Lina Lauko Goran Vukovič, Borut Werber ALMA MATER EUROPAEA – Univerza v Ljubljani, Biotehniška Univerza v Mariboru, Fakulteta za Evropski center, Maribor Fizioterapija fakulteta organizacijske vede Slovenska ulica 17 Jamnikarjeva 101 Kidričeva cesta 55a 2000 Maribor, Slovenija 1000 Ljubljana, Slovenija 4000 Kranj, Slovenija borut.werber@um.si POVZETEK ABSTRACT Hipoterapija je inovativna oblika fizioterapije, ki vključuje Hippotherapy is an innovative form of physiotherapy which uporabo konja kot terapevtskega orodja za učinkovito includes horses as a therapeutic tool for the patient, where the zdravljenje pacienta, kjer ritem hoje konja s svojim rhythm of a horse’s walking, with its three-dimensional tridimenzionalnim gibanjem nenehno spodbuja pacientovo movement, constantly works the patient’s balance into the proper ravnovesje in pravilno telesno držo. Problemsko stanje nastane posture. There is a lack of general knowledge of hippotherapy in pri splošnem poznavanju in razširjenosti hipoterapije v Sloveniji. Slovenia. Our goal is to comprehensively present the Naš cilj je posledično celostno predstaviti proces hipoterapije in hippotherapy process and hippotherapy team with their key delovanje celotnega širšega hipoterapevtskega tima z njihovimi activities in responsibility. For the purposes of our research, we ključnimi aktivnostmi in odgovornostmi. Za potrebe raziskave used several methodological approaches, including the research smo uporabili različne metodološke pristope, in sicer, approach, the review of secondary sources of literature and raziskovalni pristop, kritičen pregled sekundarnih virov literature presented our findings; qualitative approach, in na osnovi metode sintez prikazali naše ugotovitve, kvalitativni interview/conversation with professional. Based on our pristop, in sicer intervju/pogovor s strokovnjaki iz okolja, na interview we formed a rich picture of hippotherapy and Business podlagi katerega smo izoblikovali poslovni model in bogato sliko Model Canvas. We conclude that hippotherapy is a complex, hipoterapije. Ugotavljamo, da je proces hipoterapije kompleksen, multi-layered, and long process. We used a variety of modelling večslojen in dolgotrajen proces. Posledično smo z različnimi methods to create a comprehensive view of hippotherapy. The načini modeliranja ustvarili učinkovit celostni prikaz presented paper is the result of teamwork of students from hipoterapevtske dejavnosti za rešitev izpostavljenega problema. several universities and colleges in the project "Project work with Predstavljeni prispevek je rezultat timskega sodelovanja the non-profit and non-profit sector in the local and regional študentov več univerz in visokih šol v projektu »Projektno delo environment" and is an example of an alternative way of z negospodarskim in neprofitnim sektorjem v lokalnem in acquiring research competencies and skills. regionalnem okolju« in je primer alternativnega načina pridobivanja raziskovalnih kompetenc in spretnosti. KEYWORDS KLJUČNE BESEDE Hippotherapy, organisational aspect, hippotherapy team, Business Model Canvas, rich picture keywords, Hipoterapija, organizacijski vidik, hipoterapevtski tim, poslovni interdisciplinarity model, bogata slika, iterdisciplinarnost 1 UVOD Permission to make digital or hard copies of part or all of this work for personal or Hipoterapija oziroma terapija s konji je inovativna oblika classroom use is granted without fee provided that copies are not made or distributed fizioterapije, ki vključuje uporabo konja kot terapevtskega orodja for profit or commercial advantage and that copies bear this notice and the full za učinkovito zdravljenje pacienta, kjer so za pravilno izvajanje citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). potrebni zdravnik, fizioterapevt, vodič, pomočnik ter konj [11]. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Ritem hoje konja s svojim tridimenzionalnim gibanjem nenehno © 2020 Copyright held by the owner/author(s). 547 spodbuja pacientovo ravnovesje in pravilno telesno držo [7]. Sledilo je izoblikovanje modela v obliki »bogata slika« ali Usposobljen terapevt si s pomočjo različnih aktivnosti prizadeva “rich picture”. Bogata slika je risba procesa, ki ponazarja glavne izboljšati jahačevo splošno koordinacijo in motorične elemente in odnose pri hipoterapiji [8]. Sestavljen je iz slik, sposobnosti [12]. Ta kombinacija gibanja in aktivnosti pozitivno besedila, simbolov in ikon, ki se uporabljajo za grafično vpliva na jahačev nadzor telesne drže in funkcije; fizikalni učinki prikazovanje povezav med različnimi člani [14] širšega hipoterapije se prav tako kažejo v: normalizaciji mišične hipoterapevtskega tima in razmer. napetosti, večanju gibljivosti sklepov, simetriji, krepitvi mišične moči in izboljšanju kardio-respiratorne funkcije [5]. Problemsko stanje nastane pri splošnem poznavanju in 3 RAZISKAVA razširjenosti hipoterapije v Sloveniji, kot ena izmed inovativnih pristopov in oblik fizioterapije. Naš cilj je posledično celostno 3.1 Osnove hipoterapije predstaviti proces hipoterapije in delovanje celotnega širšega Hipoterapija oziroma terapija s konji je inovativna oblika hipoterapevtskega tima z njihovimi ključnimi aktivnostmi in fizioterapije, ki vključuje uporabo konja kot terapevtskega orodja odgovornostmi. Omenjeno bi zelo pripomoglo k rešitvi za učinkovito zdravljenje pacienta, kjer so za pravilno izvajanje izpostavljenega problema nepoznavanja hipoterapije. Da bi potrebni zdravnik, fizioterapevt, vodič, pomočnik ter konj [11]. uspešno dosegli zastavljen cilj je bil za štiri mesece sestavljen Ritem hoje konja s svojim tridimenzionalnim gibanjem interdisciplinarni tim (soavtorji tega prispevka) sestavljen iz nenehno spodbuja pacientovo ravnovesje in pravilno telesno študentov Medicinske fakultete, Veterinarske fakultete in držo [7]. Usposobljen terapevt si s pomočjo različnih aktivnosti Biotehniške fakultete Univerze v Ljubljani, študente študijskega prizadeva izboljšati jahačevo splošno koordinacijo in motorične programa Fizioterapije ALMA MATER EUROPAEA-Evropski sposobnosti; ta kombinacija gibanja in aktivnosti pozitivno center, Maribor in študente Fakultete za organizacijske vede vpliva na jahačev nadzor telesne drže in funkcije [3]. Univerze v Mariboru. V projektu je sodeloval Konjeniški klub Fizikalni učinki hipoterapije se prav tako kažejo v: Gibanje, ki je omogočil praktično izvajanje meritev na pacientih normalizaciji mišične napetosti, večanju gibljivosti sklepov, in sodelovanje s strokovnjaki njihovega kluba (hipoterapevti, simetriji, krepitvi mišične moči in izboljšanju kardio- vodniki konj, oskrbniki, učitelji jahanja, …). V projektu sta nam respiratorne funkcije [7]. Poleg pozitivnih učinkov na fizične bila neformalno v pomoč še dva strokovnjaka s področje težave, se pozitivni vplivi terapije s konjem kažejo v telesnem, fizioterapije in konjeništva. emocionalnem, duševnem in socialnem razvoju [10]. Hipoterapija se uporablja, ko z drugimi fizioterapevtskimi koncepti obravnave ne dosežemo uspeha oziroma ko oseba v 2 METODOLOGIJA fizioterapevtski obravnavi ne napreduje in nastane zastoj Za potrebe raziskave smo uporabili različne metodološke napredka na večjemu številu področij [7]. pristope, za kar najbolj celovit prikaz hipoterapije iz Nekatere glavne bolezni, zaradi katerih se posamezniki organizacijskega vidika. In sicer, raziskovalni pristop, kritičen zdravijo s pomočjo hipoterapije: pregled sekundarnih virov literature in na osnovi metode sintez Multipla skleroza [1]: Primarni cilji hipoterapije pri multipli prikazali naše ugotovitve, predvsem s področja teoretičnih osnov sklerozi so uravnavanje mišičnega tonusa in dihanja, krepitev o hipoterapiji. V nadaljevanju smo uporabili kvalitativni pristop, mišic trupa, izboljšanje ravnotežja, koordinacije, hoje ter in sicer intervju oziroma pogovor s strokovnjaki iz okolja, na simetrije. Poleg tega, hipoterapija spodbuja komunikacijo, vnaša podlagi katerega smo izoblikovali poslovni model (ang. veselje v življenje ter krepi samozavest. “Business Model Canvas”) in bogato sliko hipoterapije (ang. Cerebralna paraliza [9]. Pozitivni učinki terapije na “rich picture”). posameznike s cerebralno paralizo so: stabilnost jedra, nadzor Pri prvem metodološkem pristopu smo kratko in pregledno grobe in fine motorike, ravnotežje, drža, mišični tonus pripravili celovit teoretični pregled s področja hipoterapije. V (hipotonija in hipertonija), sposobnost dajanja ter sprejemanja aprilu 2020 smo izvedli intervju s strokovnjakinjo iz okolja, in vizualnih namigov, senzorične motnje, komunikacijske pridobili odgovore na vprašanja o poteku hipoterapije, člani sposobnosti, socialne spretnosti, zaupanje in samospoštovanje. hipoterapevtskega tima, njihove naloge/aktivnosti in Avtizem [2]: Hipoterapija nudi avtističnim posameznikom odgovornosti. Izdelali smo tudi seznam potrebne opreme za občutek pripadnosti, hkrati pa pozitivno vpliva na njihov stik in uspešno izvedbo hipoterapije. interakcijo z okoljem. Poveča se njihova samozavest in Na podlagi intervjuja smo izoblikovali poslovni model in socializacija, saj se učijo komunicirati in delati s svojim konjem. bogato sliko. “Business Model Canvas” ali poslovni model Downov sindrom [13]: Terapija vpliva na izboljšanje prikazuje različne sklope, področja organizacije in na preprost psiholoških, kognitivnih in komunikacijskih sposobnosti. način prikaže organizacijsko strukturo [6]. Deli se na devet Izpopolni se obnašanje in presoja posameznika, saj se nauči enakovrednih sklopov – vsi so ključnega pomena za dolgoročno, primerno ravnati s konjem. To neposredno izboljša spomin, uspešno in učinkovito delovanje posla, med seboj pa se seveda govor in samozavest. povezujejo in dopolnjujejo, zato moramo posamezne elemente Ortopedske motnje [15]: Ortopedska hipoterapija predstavlja področij ustrezno obarvati, da intuitivno prikažemo njihove novo obliko terapevtske vadbe pri zdravljenju segmentnih povezave [4]. S pomočjo omenjenega modela, smo prikazali nestabilnosti ledvene hrbtenice. Tovrstna terapija deluje na ključne partnerje, aktivnosti in vire pri hipoterapiji, dodano načelu, da pacientu posreduje tridimenzionalno nihajno gibanje vrednost, odnose s strankami, prodajne kanale, segmente strank, hrbta konja. Na te gibalne impulze se posameznik odziva s strukturo stroškov in prihodkov. premikanjem navzgor-navzdol, naprej-nazaj in levo-desno. 548 Zaradi spreminjajoče se tlačne obremenitve med vadbo se strukturo, s čimer lahko enostavno prikažemo celotno sliko izboljša delovanje aktivnih in pasivnih struktur hrbtenice. podjetja ali organizacije. Deli se na devet enakovrednih sklopov, Psihična obolenja [2]: Sem spadajo bolezni, kot so na primer: vsi so ključnega pomena za dolgoročno, uspešno in učinkovito depresija, anksioznost, fobija, manična depresija, razvojna delovanje posla, med seboj pa se seveda povezujejo in zakasnitev, ADHD, učne težave, motnje govora in zloraba drog. dopolnjujejo, zato moramo posamezne elemente področij Tesno sodelovanje s konji je pomagalo posameznikom pri ustrezno obarvati, da intuitivno prikažemo njihove povezave. premagovanju obrambnega vedenja in starih čustvenih vzorcev Elemente smo razporedili v štiri skupine. ter pri iskanju novih načinov reševanja problemov in Rumena predstavlja vse, kar je povezano z oskrbo in razumevanja perspektive ostalih. Terapevtsko jahanje je vzdrževanjem konj, vijolična predstavlja terapevtski aspekt in pomagalo pacientu, da vstopi v meditacijo, v kateri se osredotoča vse kar je povezano z njim, rdeča predstavlja stranke oziroma na reševanje problemov v sedanjem trenutku. paciente in njihovo interakcijo v celotnem procesu, zelena barva pa predstavlja ključno aktivnost ter komponente, od katerih je 3.2 Hipoterapija iz organizacijskega vidika hipoterapija odvisna. Na podlagi pridobljenih odgovorov s strani strokovnjakinje iz Iz Slike 2 je razvidnih vseh devet, prej omenjenih elementov, okolja in študije literature smo izoblikovali naslednja modela, in in sicer, ključni partnerji: Konjeniški center, zdravstveni sicer poslovni model in bogato sliko. strokovnjaki, veterinar, kovač, oskrbnik konj; ključne aktivnosti: Za nemoteno in kontinuirano izvajanje hipoterapije, izvajanje hipoterapije, iskanje primernih konj, komunikacija s potrebujemo kar nekaj virov (materialnih, nematerialnih, strankami, skrb za fizično in psihično zdravje konja; ključni viri: človeških) in ustrezne povezave med njimi. S Sliko 1 so v hipoterapevtska ekipa, terapevtski konji, prostori, konjeniška nadaljevanju prikazane ključne aktivnosti in funkcije (vloge oprema; dodana vrednost: izboljšava motoričnih, procesnih, hipoterapevtskega tima) ter povezave med njimi. Hipoterapevt komunikacijskih oz. interakcijskih spretnosti; odnosi s tako vodi hipoterapevtske seanse, med njimi mora poskrbeti za strankami: osebni, preko oskrbnika osebe; prodajni kanali: dobro komunikacijo z vodnikom konja, pripravi vaje za zdravniki, spletna stran, osebni; segmenti strank: otroci, naslednje termine, svoj kontakt ponuja na spletnih straneh, hkrati mladostniki, odrasli z različnimi obolenji; struktura stroškov: pa mora komunicirati s pacientom ter v nekaterih primerih z plače hipoterapevtske ekipe, oskrba konj, vzdrževanje prostorov zdravnikom, s katerim si izmenja diagnozo pacienta in poročilo in opreme, specialna oprema in struktura prihodkov: plačila o napredku. posameznih ur hipoterapije, javna sredstva. Glavne aktivnosti vodnika konja v sklopu hipoterapije so Materialni pogoji in človeški viri so potrebni za delovanje vodenje konja med hipoterapijo, komunikacija s hipoterapevtom vsake organizacije. Pri procesu hipoterapije poznamo šest in dogovor o terminih, hkrati pa mora skrbeti za konjevo psihično različnih vlog – vsaka je zadolžena za ustrezno izvajanje svojega in fizično dobrobit. Hipoterapija potrebuje prostor za izvedbo (po strokovnega dela. Akterji za to potrebujejo ustrezne predmete navadi pokrita jahalnica), običajno zagotovi konjeniški center, ki dela in delovna sredstva. Izvajalci pri hipoterapiji so lahko skrbi tudi za konje, njihovo hranjenje in hlevljenje in ima notranji ali zunanji, odvisno od strukture organizacije. Za dogovor o delu z oskrbnikom konj. Konj seveda potrebuje tudi nemoteno in kontinuirano delovanje hipoterapevtske aktivnosti, kovača, ki ga podkuje ali izvede korekcijo kopit, ter veterinarja, morajo izvajalci med seboj sodelovati in si poročati o ki skrbi za njegovo fizično zdravje. Zadnji akter na sliki je opravljenem delu. stranka, ki se zdravi s pomočjo hipoterapije, ki mu jo lahko Hipoterapevtsko skupino sestavljajo naslednji člani: predpiše zdravnik, informacije o njej pa lahko dobi s pomočjo hipoterapevt, vodnik konja, zdravnik, oskrbnik konja, veterinar spletnih strani. in kovač. Njihovi materialni pogoji se v velikem številu Zdravnik je odgovoren za celovito zdravljenje pacienta, aktivnosti med seboj prekrivajo. Sam proces hipoterapije se spremljanje njegovega napredka in za dobro komunikacijo s prične z diagnozo pacienta. Zdravnik je tisti, ki pacienta napoti hipoterapevtom. Hipoterapevt je odgovoren za izbiro vaj in na hipoterapijo. vodenje hipoterapije, za komunikacijo s pacientom in izbiro Veterinar in zdravnik za svoje delo potrebujeta podobna primernega konja. Vodnik konja mora med hipoterapijo ustrezno delovna sredstva – oba potrebujeta računalnik, razne obrazce, voditi konja, nuditi prvo pomoč v primeru nesreč in poškodb, napotnice, ambulanto, laboratorijski pribor, kirurški pribor in kontrolirati mora odzive konja na nenavadne zvoke med zdravila. Veterinarski tehnik je odgovoren za varovanje in hipoterapijo, odgovoren je tudi za delo s konjem v maneži in na izboljšanje zdravja konja, zdravnik pa za evalvacijo rezultatov po lonži, med seansami pa mora skrbeti tudi za konjevo psihično in opravljenih seansah hipoterapije ter svetovanje glede nadaljnje fizično dobrobit ter za sproščanje konja. rehabilitacije. Oskrbnik konja skrbi za urejenost jahalnice, za hranjenje in Veterinar mora biti v rednem kontaktu z oskrbnikom konj, saj splošno vzdrževanje konj, k čimer spada tudi naročilo kovača in mu on sporoča o zdravstvenem stanju konj v konjeniškem centru. naročilo pregleda konja pri veterinarju. Kovač je odgovoren za Oskrbnik konj prav tako vzdržuje jahalni prostor in konjeniško primerno podkovanje oziroma korekcijo kopit, veterinar pa skrbi opremo. Zadolžen je za vsakodnevno čiščenje hlevov ter in vzdržuje zdravje konja. Z oskrbnikom komunicira tudi krmljenje in negovanje konj. V primeru podkovanja ali korekcije konjeniški center, ki se z njim dogovarja o čiščenju in kopit je on tisti, ki pokliče kovača. Materialni pogoji vodnika vzdrževanju, glavna odgovornost centra pa je zagotavljanje konja in hipoterapevta so zelo podobni in dopolnjujoči. Med jahalnice za hipoterapijo. njihova delovna sredstva in predmete dela spadajo: terapevtski Z vidika organizacije, smo hipoterapijo opisali tudi s pomočjo konj, oprema za čiščenje konja, oprema za jahanje, vzdrževana poslovnega modela Slika 2. Orodje prikazuje različna področja jahalnica, rampa, prva pomoč in telefon (v primeru poškodb). organizacije in na preprost način prikaže organizacijsko 549 Vodnik konja je v procesu hipoterapije odgovoren za preverjanje stanja konja in vzdrževanje njegove kondicije. Zadolžen je za konjevo psihično in fizično dobrobit. Njegovo glavno delo je vodenje konja pod vodstvom hipoterapevta. Mora se seznaniti s pravilno terminologijo za sporazumevanje s hipoterapevtom. Terapevt pred hipoterapijo opravi sklop testiranj s pacientom in se dogovori za ustrezne termine. Prav tako izbira vaje, kontrolira in popravlja konjevo hojo, vzdržuje tempo ter gleda na pravilno držo pacienta. Proces hipoterapije se zaključi s pacientovim dosegom postavljenih ciljev hipoterapevta. 4 UGOTOVITVE IN ZAKLJUČEK Slika 23: Poslovni model hipoterapije (lasten prikaz) Hipoterapija oziroma terapija s konji je inovativna oblika fizioterapije, ki vključuje uporabo konja kot terapevtskega orodja za učinkovito zdravljenje pacienta. Problemsko stanje nastane pri FINANCIRANJE splošnem poznavanju in razširjenosti hipoterapije v Sloveniji, Raziskava je bila financirana s strani Javni štipendijski, razvojni, kot ena izmed inovativnih pristopov in oblik fizioterapije. invalidski in preživninski sklad Republike Slovenije in EU v Ugotavljamo, da je proces hipoterapije kompleksen, okviru razpisa Projektno delo z negospodarskim in neprofitnim večslojen in dolgotrajen proces. Posledično smo z različnimi sektorjem v lokalnem in regionalnem okolju – Študentski načini modeliranja ustvarili učinkovit celostni prikaz inovativni projekti za družbeno korist 2016–2020 za študijski leti hipoterapevtske dejavnosti za rešitev izpostavljenega problema. 2018/2019 in 2019/2020 (261. JR) z naslovom »Hipoterapija za Menimo, da ima hipoterapija velik potencial v Sloveniji, saj pri otroke - interakcija trodimenzionalnega gibanja«. posamezniku ustvari številne pozitivne učinke, katere je težje pridobiti z drugimi oblikami fizioterapije in zdravljenja. Glede na predpostavljeno sklepamo, da bo prispevek signifikantno LITERATURA pripomogel k razumevanju organizacijskega vidika hipoterapije [1] Bronson, C., Brewerton, K., Ong, J., Palanca, C., in v Sloveniji. Sullivan, S. J. (2010). Does hippotherapy improve balance V tem prispevku smo povzeli bistvo raziskovalne naloge, ki in persons with multiple sclerosis: a systematic review. je podrobneje zapisana v obliki monografije Hipoterapevtski tim European Journal of Physical and Rehabilitation Medicine. in kompetence na sto straneh s podrobnimi opisi in slikovnimi Pridobljeno s prikazi vseh deležnikov, njihovih nalog in zadolžitev, procesov https:/ pdfs.semanticscholar.org/da4e/6bbae36b6753a0af1 in sredstev potrebnih za izvajanje hipoterapije. Delo ne temelji le 45646e27ad7bc41de28.pdf na teoretičnem in raziskovalnem delu temveč tudi na praktičnem [2] Cabiddu, R., Borghi-Silva, A., Trimer, R., Trimer, V., delu, ki so ga vsi sodelujoči študenti opravili v praksi v realnem Ricci, P. A., Monteiro, C. I., ... in Carvalho, E. M. (2016). okolju s privolitvijo staršev proučevane pacientke. Hippotherapy acute impact on heart rate variability non- Projektno delov v okviru »Projektno delo z negospodarskim linear dynamics in neurological disorders. Physiology & in neprofitnim sektorjem v lokalnem in regionalnem okolju« se behavior. Pridobljeno s https://www-sciencedirect- je pokazalo kot nov način pridobivanja ne le strokovnih temveč com.ezproxy.lib.ukm.si/science/article/pii/S003193841630 tudi znanstvenih kompetenc študentov. 0981 Zaključimo lahko z mislijo Winstona Churchilla: “Nekaj je [3] Casady, R. L., & Nichols-Larsen, D. S. (2004). The effect na zunanjosti konja, kar je dobro za človekovo notranjost.” (ang. of hippotherapy on ten children with cerebral palsy. “There is something about the outside of a horse that is good for Pediatric Physical Therapy, 16(3), 165-172. the inside of a man.”). [4] Hong, Y. C. in Fauvel, C. (2013). Criticisms, variations and experiences with business model canvas. [5] Jang, C. H., Joo, M. C., Noh, S. E., Lee, S. Y., Lee, D. B., Lee, S. H., ... in Park, H. I. (2016). Effects of hippotherapy on psychosocial aspects in children with cerebral palsy and their caregivers: a pilot study. Annals of rehabilitation medicine, 40(2), 230. [6] Joyce, A., in Paquin, R. L. (2016). The triple layered business model canvas: A tool to design more sustainable business models. Journal of cleaner production, 135, 1474- 1486. [7] Koca, T. T. in Ataseven, H. (2016). What is hippotherapy? The indications and effectiveness of hippotherapy. Northern clinics of Istanbul. Doi: 10.14744/nci.2016.71601 Slika 22: Bogata slika hipoterapije (lasten prikaz) 550 [8] Lewis, P. J. (1992). Rich picture building in the soft [12] Petrovič, V. (2001). Hipoterapija: zdravljenje z jahanjem systems methodology. European Journal of Information konja. Velenje: Pozoj. Systems, 1(5), 351-360. [13] Ribeiro, M. F., Espindula, A. P., Ferreira, A. A., Ferraz, [9] Martín-Valero, R., Vega-Ballón, J., in Perez-Cabezas, V. M. L. F., Souza, L. A. P. S., Diniz, L. H., in Teixeira, V. (2018). Benefits of hippotherapy in children with cerebral D. P. A. (2015). Electromyographic evaluation of lower palsy: A narrative review. European Journal of Paediatric limbs in individuals with Down syndrome in hippotherapy. Neurology. Pridobljeno s https:/ www-sciencedirect- Physiotherapy. Pridobljeno s https://www-sciencedirect- com.ezproxy.lib.ukm.si/science/article/pii/S109037981730 com.ezproxy.lib.ukm.si/science/article/pii/S003194061501 1745 2225 [10] Macauley, B. L., & Gutierrez, K. M. (2004). The [14] Sutrisna, M., & Barrett, P. (2007). Applying rich picture effectiveness of hippotherapy for children with language- diagrams to model case studies of construction projects. learning disabilities. Communication Disorders Quarterly, Engineering, Construction and Architectural Management. 25(4), 205-217. [15] Sunwoo, H., Chang, W. H., Kwon, J. Y., Kim, T. W., Lee, [11] Meregillano, G. (2004). Hippotherapy. Physical medicine J. Y., in Kim, Y. H. (2012). Hippotherapy in adult patients and rehabilitation clinics of North America, 15(4), 843-54. with chronic brain disorders: a pilot study. Annals of Pridobljeno s https://europepmc.org/article/med/15458756 rehabilitation medicine. Doi: 10.5535/arm.2012.36.6.756 551 Se igram ali učim? Spletna aplikacija Wordwal Do I play or learn? Web application Wordwall Sanja Leben Jazbec OŠ Solkan Šolska 25 5250 Solkan, Slovenija sanja.leben-jazbec@guest.arnes.si POVZETEK Kot učitelj razmišljujoči praktik se sprašujem: Kako izkoristiti to (sicer tudi katero koli) atraktivno IKT-orodje, da ne S spletno aplikacijo Wordwall ustvarimo različne tipe le vzpodbudimo, temveč tudi poglobimo proces učenja? Manj interaktivnih igrificiranih nalog zaprtega tipa. V vnaprej privlačne vsebine, kot so npr. zapis z veliko ali malo začetnico, pripravljene igrificirane in atraktivne predloge vnesemo svoje sklanjatveni vzorci ipd., naredimo učencu atraktivnejše, vsebine in v nekaj minutah ustvarimo interaktivno nalogo ali si približamo se mu skozi zanj domače okolje, kot je igra. Da pa se jo pretvorimo v pdf-datoteko. V procesu učenja, ki je podprto s učenje ne zreducira zgolj na igranje in z njim doseganje čim formativnim spremljanjem, učenci po dejavnosti reflektirajo boljšega rezultata, se vedno znova vračava v učni proces s vsebine in proces, refleksiji pa sledijo nove učne priložnosti za ključnimi vprašanji Kje sem? Kam želim priti? Kako do tja? oba, izboljšanje učnih dosežkov. učitelj in učenec. Na konkretni operativni ravni velja v učni KLJUČNE BESEDE proces vgraditi refleksijo tako vsebine kot procesa, a refleksija sama po sebi ne bo dovolj, če za njo ne bo možnosti akcije. Igrifikacija, formativno spremljanje, povratna informacija, refleksija 2 NA KRATKO O ORODJU – ABSTRACT PREDSTAVITEV With the help of Wordwall web app it is possible to create Wordwall (https://wordwall.net/) je spletna aplikacija, ki v svoji different types of interactive, closed-type gamificated tasks. All brezplačni različici nudi 18 tipov nalog (v plačljivi 34), med that needs to be done is to enter the content into attractive, pre- drugim kviz (v različnih oblikah, npr. tipa milijonar), made templates. As a result, it is possible to create an interactive povezovanje, anagram, vislice, križanko, prav/narobe itn. Gre za task that can be transformed into a PDF file in just a few minutes. prednastavljene predloge (angl. template), v katere vpišemo In the learning process, supported by formative assessment, svojo vsebino. Enostavno in hitro, a v brezplačni različici z students reflect on the content and process after the activity. omejitvijo na 5 aktivnosti in brez možnosti multiplayerja. Isto Reflection is followed by new learning opportunities for interaktivno nalogo lahko spreminjamo po temi, s čimer dobimo improving learning achievements. drugačno grafiko, pisavo in zvoke. Nadaljnja opcija je, da nalogo KEYWORDS otežimo s časom in številom življenj ter ravnmi (angl. levels). Izbiramo med pokažem/skrijem dosežene točke za vsakim Gamification, formative assessment, feedback, reflection vprašanjem, na koncu ponudimo ali pa ne nabora vseh vprašanj z odgovori. Če je naloga javna, lahko spremljamo rezultate svojih učencev – po doseženih točkah in času. Ko ustvarimo aktivnost, 1 UVOD jo lahko takoj spremenimo v drugo, to možnost imajo sicer tudi Da učenje lahko podpremo z igro, ni nek inovativen pedagoški igralci. Običajen interaktivni kviz z več odgovori spremenimo v pristop. Na voljo imamo res veliko igrificiranih bolj ali manj npr. križanko, povezovanje itn. Interaktivne naloge si lahko privlačnih spletnih orodij, med katerimi izbiramo na podlagi več natisnemo (v pdf-ju) kot učne liste. Do orodja je možno dostopati parametrov, npr. glede na namen (kaj želimo doseči), način z različnih naprav. Slovenske različice ni, kar pomeni, da bodo (bomo dostopali z računalnikom, mobilnimi telefoni …), navodila in odzivi v angleščini. nenazadnje tudi ceno itn. Eno izmed njih je Wordwall, katerega sem preizkusila v času izobraževanja na daljavo. 3 DIDAKTIČNI PREMISLEK UČITELJA: ZAKAJ, ČEMU, KDAJ, KAKO WORDWALL? Permission to make digital or hard copies of part or all of this work for personal or Wordwall je atraktivno orodje s privlačno grafiko, zvoki, classroom use is granted without fee provided that copies are not made or distributed animacijami, kar bo zagotovo pritegnilo tako učenca vizuelca, for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must avditivca kot kinesteta ne glede na njegovo starost. Igra (npr. be honored. For all other uses, contact the owner/author(s). kviz) s svojo dinamiko motivira, saj takoj dobiš rezultat (točke) Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). pa tudi priložnost, da še enkrat zaigraš in izboljšaš svoje mesto 552 na lestvici igralcev. Stimulativno za tekmovalne učence, ponujeni? Kateri med njimi so nepravilni? Zakaj je ta odgovor čustvena angažiranost je velika, učenje dolgočasne vsebine, npr. (ne)pravilen? slovničnih pravil, postane zabavno. Učitelju je na tej točki izziv, Druga možnost znotraj nalog izbirnega tipa je kviz tipa kako organizirati učenje (med poukom v šoli in doma), da se bo milijonar (angl. Gameshow quiz). Še vedno gre za interaktivni učenec v resnici (na)učil, ne pa samo klikal in se pehal za čim kviz, torej za zaprto nalogo z vprašanjem in več možnimi boljšim rezultatom. Nobeno orodje in nobeno okolje sama po odgovori, vendar pa je predloga tehnično še bolj v vodah sebi ne dajeta poglobljenega znanja, torej ni dovolj, da se zgolj igrifikacije. Igralec dobi točke za pravilen odgovor, obenem se igra neko igrificirano interaktivno vsebino, kot tudi v razredu ni ga nagradi še z dodatnimi točkami za čas (za vsako sekundo dovolj, da se zgolj rešuje učni list. Rešitev je v tako zastavljenem dodatna točka). Igralec ima možnost vplivati na tekmovanje, saj učnem procesu, da učenec sproti reflektira ne le vsebine, temveč si lahko polovico nepravilnih odgovorov izloči (gumb 50 : 50), s tudi sam proces učenja. Povzeto po Sentočnikovi [1] je refleksija pravilnim odgovorom točke podvoji, potroji (gumba x2 Score, namensko sprožen proces, v katerem učenec ovrednoti naučeno x3 Score), lahko si podaljša čas (gumb Extra Time), enkrat v igri in si zastavi nove cilje. Refleksija sama po sebi ne zadošča, si razkrije pravilen odgovor (gumb Cheat). Po približno 4 učencu je potrebno neposredno po refleksiji ponuditi nove učne vprašanjih se kviz samodejno prekine, tekmovalca se motivira z priložnosti za izboljšavo. Dylan Wiliam takšno funkcioniranje dodatnimi točkami in nagradami. Tudi ta predloga je podprta z slikovito povzame z besedno zvezo refleksija in akcija (angl. atraktivno animacijo. Tehnično tako nastavljenega milijonarja ne Reflection and action!) [4]. ponujam kot učne priložnosti v fazi utrjevanja, temveč je Učeči se naj torej opazuje svoje učenje. Refleksija naj bo smiselno ga ponuditi v preverjanju. konkretna: kaj točno sem se učil (vsebina), v čem vse sem zaznal Pri kakršni koli obliki (interaktivnega) kviza se je potrebno napredek, kje so priložnosti za izboljšanje (kaj mi je delalo zavedati, da gre za nalogo objektivnega tipa z več izbirami, torej težave), kaj konkretno bom za to naredil. Na drugi strani je učitelj, bo prej ko ne na ravni nižjih taksonomski znanj. Konec koncev ki naj nenehno reflektira svoje poučevanje in ga, če je potrebno, učimo tudi znanja na (naj)nižjih taksonomskih stopnjah ustrezno modificira v smislu, da morda poseže v težavnost pomnjenja in razumevanja. So vsebine, ki se jih je potrebno (sprosti ali oteži), se vrne v namene učenja, individualizira zapomniti in potegniti iz spomina. Vsekakor bi se dalo nastaviti dejavnosti itn. Na tej točki se udejanja formativno spremljanje, distraktorje na ravni višjih taksonomskih ravni, a če imamo ko se transformirava oba, učenec in učitelj. nalogo omejeno s časom reševanja, oboje skupaj pedagoško ne Kdaj, v katerem delu učne ure ponuditi dejavnosti v vzdrži. Wordwallu – med uvodno motivacijo, utrjevanjem, Pri (interaktivnem) kvizu učeči se dobi takojšnjo povratno ponavljanjem? Katero predlogo pri tem izbrati? Pravzaprav informacijo v smislu števila oz. odstotka (ne)pravilnih kadar koli in kar koli, a s pedagoškim razmislekom, kje učenec v odgovorov, pogosto tudi z naborom konkretnih (ne)pravilnih procesu je, kam gre in kako naj pride do tja. V srži didaktičnega rešitev. Po Nykvistu (v Wiliam [3]) gre za t. i. skromno povratno premisleka naj ne bo dejavnost sama po sebi, temveč pričakovani informacijo, tj. informacijo v obliki ocen ali informacijo tipa dosežki. poznavanja rezultatov (pravilnih odgovorov). Dylan Wiliam [2] Prva različica, ki se je poslužujem, je kviz. Wordwall v in [3] v svojih raziskavah dokazuje, da bo ta, kot sicer velja za neplačljivi obliki mi ponuja dve možnosti. vse povratne informacije, relativno nekoristna, saj ima povratna Prva je običajni interaktivni kviz, ki je podprt z elementi informacija globok učinek na učenje le, ko učenca motivira za igrifikacije (npr. z glasbo v ozadju, točkovanjem, lestvico nadaljnje premišljene dejavnosti. Tu vstopi učitelj, ki učenje z najboljših po točkah in času). Kviz z izbiro različnih predlog interaktivnimi nalogami vgradi v proces učenja tako, da se učenci (angl. template) poustvari neko okolje, npr. džunglo, divji zahod, vedno znova vračajo k pričakovanim dosežkom, operirajo z televizijski kviz, vesolje, duhove itn., podprto je s stimulativnimi nameni učenja in merili uspešnosti, ki so osnova povratnim zvoki iz dotičnega okolja. Igralci lahko tudi sami spreminjajo informacijam, dokazi o učenju (v tem primeru kviz) pa so ozadje. Tako v vprašanje kot v odgovore lahko dodajamo slike izhodišče refleksiji in nato nadaljnjemu učenju. ali sestavimo kviz samo s slikami, kar bi bilo smiselno za mlajše V Wordwallu imamo na voljo še druge predloge (angl. učence. Kviz otežimo z omejitvijo časa, številom življenj, lahko template), s katerimi naredimo učenje na pamet res atraktivno. premešamo vprašanja po naključnem vrstnem redu. Če kviz Po mojih izkušnjah je predloga Udari krta! (angl. Whack-a-mole) ponudimo v fazi utrjevanja, ko se učenci še učijo, je smiselno takšna, da zmotivira prav vsakega učenca v razredu. Gre za nastaviti možnost, da se v primeru nepravilnega odgovora taksonomski stopnji poznavanja in razumevanja preko naloge pokaže zraven pravilna rešitev. Učitelj mora premisliti, koliko objektivnega tipa prav/narobe. Potrebno je izbrati pravilno vprašanj bo sploh postavil (najmanj 1 in največ 100), pri vsakem rešitev ob ponujenih nepravilnih odgovorih. Predloga Udari krta! vprašanju je potrebno tudi premisliti, koliko odgovorov ponuditi je visoko igrificirana, enako tudi njena različica Poči balon! (angl. (Tri, štiri, pet …?), kaj ponuditi kot nepravilne možnosti, da ne Baloon pop). Tekmovalec se prebija iz začetne ravni v vse težje izzveni v izločanje nepravilnih odgovorov. Premisliti velja tudi in zahtevnejše (skupno vseh je 20), pri čemer se zahtevnost glede možnosti, ali vprašanja premešati. Če sestavljamo po stopnjuje s števili primerov, hitrostjo, v kateri je potrebno težavnosti, od lažjih primerov k težjim, bi bilo verjetneje odreagirati, z nepravilnim odgovorom se točke odbijejo, igra se smiselno, da v prvi fazi učenja nastavimo opcijo, da se vprašanja navidezno prekinja, tako da ima tekmovalec iz ravni v naslednjo ne nizajo naključno, kasneje jih ponudimo premešana. Ali na raven (ang. level) možnost, da izboljša rezultat. Zelo koncu pokazati vsa vprašanja skupaj s pravilnimi odgovori? Da, stimulativno za tekmovalne učence. Ena od možnih izpeljav je, a z refleksijo. Učenec naj skupaj s sošolci analizira: S katerimi da organiziramo tekmovanje v dvojicah ali skupini treh na i-tabli vprašanji sem imel težave in zakaj? Kateri odgovori so bili pred sošolci. 553 Ker je orodje Wordwall z velikim naborom predlog izjemno priložnost, da izboljša svoje učenje. Potem ko se učenec z enostavno, ga je možno izkoristiti tudi v smislu, da je učenec tisti, interaktivno nalogo formativno preveri, je smiselno, da se ne ki sestavi novo igrificirano interaktivno nalogo. V tem primeru zadovoljimo s povratno informacijo tipa poznavanja rezultatov, izkazuje svoja vsebinska znanja na nivoju uporabe, na primer ampak nastavimo proces tako, da se sproži nadaljnje učenje. sestavi naloge z zapisom velike in male začetnice. Če pri pouku razvijamo veščino sodelovanja, naj oblikujejo v paru/skupini naloge na izbrani vsebini. V vsakem primeru jih podpremo s VIRI IN LITERATURA procesom FS-ja: ciljno jih usmerimo tako na veščino kot vsebino, [1] Sentočnik, S. 2004. Portfelj kot alternativna oblika z njimi oblikujemo merila uspešnosti, podpiramo jih s povratno vrednotenja učenčevega napredka: možnosti njegove informacijo, svoje dokaze o učenju naj objavljajo na forumu, ki uporabe v slovenskih šolah. Sodobna pedagogika, 55, št. 1, je prostor diskusije oz. učnega pogovora. Dokazi o učenju, ki 70–91. Ljubljana: Zveza društev pedagoških delavcev. nastajajo (v tem primeru naloge, ki jih sestavijo sami), naj bodo [2] Wiliam, D. 2007. Keeping learning on track: Formative nenehno vzorčni izdelki v smislu, kaj je dobro, na katerem delu assessment and the regulation of learning. DOI= pa bi se dalo še izboljšati. https:/ www.researchgate.net/publication/252646685_Kee Wordwall nam torej ponuja kar precej uporabnih igrificiranih ping_learning_on_track_Formative_assessment_and_the_r predlog, s katerimi lahko pripravimo svoja interaktivna gradiva. egulation_of_learning. Ker je veliko gradiva že pripravljenega s strani drugih [3] Wiliam, D. 2013. Vloga formativnega vrednotenja v izobraževalcev, velja pregledati za svoje področje, kaj učinkovitih učnih okoljih. V Dumont idr., O naravi uporabnega se najde. Že narejeno namreč lahko predelamo. učenja: uporaba raziskav za navdih prakse, 123–145. Ljubljana: Zavod Republike Slovenije za šolstvo. Dostopno tudi na: https://www.zrss.si/pdf/o-naravi- 4 ZAKLJUČEK ucenja.pdf. Ali je spletna aplikacija Wordwall uporabna? Nedvomno, učenca [4] Wiliam, D. 2015. Feedback for Learning: Make Time to z elementi igrifikacije in atraktivno grafiko, zvoki ipd. zelo Save Time. DOI= pritegne. Učitelj naj premišljeno sestavi nalogo, nato pa naj https://www.dylanwiliamcenter.com/2015/01/06/feedback- for-learning-make-time-to-save-time/. znotraj procesa učenja dejavnosti sledi refleksija vsebine in procesa, tej pa vedno znova akcija – učenec naj ima torej učno 554 Laboratorijske vaje pri fiziki – izzivi in možne rešitve pri poučevanju na daljavo Physics laboratory work - challenges and possible solutions for online learning Kristina Leskovar Gimnazija Franceta Prešerna Koroška cesta 65 4000 Kranj, Slovenija kristina.leskovar@gfp.si POVZETEK Razglasitev epidemije v marcu 2020 zaradi velikega števila 1 POUK NA DALJAVO okužb s SARS-CoV-2 (COVID-19) nas je pripeljala do točke, ko Učenje na daljavo vsekakor ni nekaj novega. Prvi zapisi o učenju smo morali začeti razmišljati o podajanju učne snovi na drugačen na daljavo so znani iz Združenih držav Amerike iz leta 1800, kjer način, kot smo bili vajeni. Marsikaj, kar se nam je zdelo so bili učitelji in učenci iz Univerze v Čikagu na različnih samoumevno, logično in edino prav, je sedaj postalo izziv. lokacijah. Učenje je potekalo preko dopisnih tečajev. Prvo znano Predstavljam področje poučevanja, pri katerem sem se sama, kot spletno učenje na daljavo je bilo izvedeno sredi osemdesetih let profesorica fizike na splošni gimnaziji, srečala z največ izzivi; dvajsetega stoletja. Spletno poučevanje je nato začelo naraščati fizikalne laboratorijske vaje oz. njihova izvedba. V prispevku in razdalje med učitelji ter učenci so postajale nepomembne [1]. predstavim tri načine s katerimi lahko laboratorijske vaje Vsekakor pa je zelo važno, da se učitelj zaveda, da je za uspešno predstavimo, izvedemo in posredujemo na daljavo. V zadnjem poučevanje treba upoštevati nekaj načel [2]. Učitelj mora delu prispevka predstavim še rezultate ankete, ki sem jo izvedla spodbujati učenčevo udeležbo, spodbujati mora njegovo konec šolskega leta 2019/2020 in se je nanašal na izvedbo vaj na sodelovanje, aktivno učenje ter podajati povratne informacije o daljavo. napredku. Učitelj mora podariti čas, ki je predviden za posamezne naloge, upoštevati diferenciacijo ter pristope, ki jih KLJUČNE BESEDE učenci uporabljajo za učenje [3]. Poučevanje na daljavo, fizika, laboratorijske vaje Tudi v Sloveniji pouk na daljavo poteka že kar nekaj časa. Uporabljajo ga dijaki, ki imajo status vrhunskega športnika ali ABSTRACT kulturnika in zaradi obveznosti zaradi treningov in vaj ne morejo The declaration of a COVID-19 epidemic in March 2020 brought biti prisotni pri pouku. Učitelji so tem dijakom že sedaj ponujali us to the point where we started thinking about teaching in a učenje na daljavo. Vendar v teh primerih govorimo o different way that we were used to. Many things that seemed self- individualnih načrtih. V marcu 2020 smo se v Sloveniji prvič vsi evident, logical and right to do, has become difficult to achieve. učitelji srečali s poučevanjem na daljavo v večjem obsegu. As Physics teacher, in general grammar school I present area that Izkazalo se je, da na to nismo bili pripravljeni, prav tako nismo I found most challenging. Physical laboratory exercises and their poznali opreme, računalniških programov, ki bi nam to implementation. In this paper, I present three ways in which omogočali. Vsak učitelj se je poskušal znajti po svoje. Aktivno those experiments can be presented, implemented and sodelovanje med šolskimi aktivi je omogočilo hitro transmitted in online learning. In the last part of the article, I napredovanje v znanju učenja na daljavo. present the results of a survey about the implementation of Pri predmetu fizika je v prvih treh letih v programu splošnih laboratory work that took place at the end of the 2019/2020 gimnazij je na letnem nivoju predvidenih 10 ur laboratorijskih school year. vaj dijakov [4]. Področja iz katerih si učitelj vaje izbere so lahko poljubna in prosta izbira učitelja, saj je izvedba vaj odvisna od KEYWORDS eksperimentalne opreme, ki je dosegljiva v šoli. Pri učenju na Online learning, physics, laboratory work daljavo je bila možnost izbire vaj še večja prednost, kot sicer. Na ta način lahko učitelj izbere laboratorijske vaje, kjer zagotovi opremo doma, vajo posname, poišče simulacijo, ki mu omogoča prikaz fizikalnih zakonitosti ali pa razmisli o opremi, katera je dosegljiva tudi dijakom doma in si vajo pripravijo iz domačih pripomočkov. Sama sem tekom poučevanja na daljavo Permission to make digital or hard copies of part or all of this work for personal or preizkusila tri možnosti, ki so v nadaljevanju opisane. classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 555 2 LABORATORIJSKIE VAJE NA DALJAVO 2.1 Posnetek laboratorijske vaje Prva možnost, ki jo predstavljam, je posnetek vaje. Vajo, ki jo želimo predstaviti dijakom posnamemo, ko jo sami izvajamo v razredu [slika 1]. Dijakom posnetek vaje posredujemo ter pripravimo pripadajoče učne liste, kjer dijaki s pomočjo posnetka ugotavljajo glavne zakonitosti. Slika 25. Posnetek zaslona računalnika, kjer je prikazana simulacija iz portala PHET; vaja: Lomni in odbojni zakon. 2.3 Naredi sam Zadnja možnost, ki jo predstavljam v tem prispevku je izvedba laboratorijske vaje na način “naredi sam”. Pri izvedbi te vaje mora biti učitelj zelo pozoren na izbiro vaje ter pripomočkov, ki Slika 24. Izsek iz posnetka laboratorijske vaje, ki sem jo jih morajo učenci imeti doma. Pri izbiri teh vaj je po mojem posnela v šoli s šolskimi pripomočki; vaja: Stoječe valovanje mnenju učitelj najbolj omejen na izbiro fizikalnega področja, na vrvi. kjer je vaja izbrana. Vsekakor ima tip laboratorijske vaje “naredi Prednosti, ki bi jih izpostavil pri tem podajanju vaje je, da se sam” kar nekaj prednosti. Poudarila bi, da morajo dijaki aktivno izognemo težavam z opremo. Dijakom posredujemo vajo, ki je razmišljati že pri postavitvi vaje, ki jo bodo izvajali. Izkazati se bila že v začetku predvidena. Posnetek vaje lahko posredujemo morajo pri izbiri priporočenih pripomočkov ter sami izvedbi dijakom preko ustaljenega komunikacijskega kanala. S tem ne vaje. Če učitelj pripravi učne liste za pripadajočo vajo, dijaki povzročamo dodatnih stresorjev. Prednost je tudi, da vajo relativno natančno raziščejo fizikalne lastnosti. Pri vajah tega posnamemo na način, da dijaki pravilno vidijo pojav, na katerega tipa, ki sem jih posredovala dijakom, so dijaki meritve izvajali s se osredotočamo ter vaja v tem pogledu vedno »uspe«. Vsi dijaki pomočjo aplikacije Phyfox [slika 3], ki so si jo namestili na imajo enake podatke in na ta način lažje primerjajo pridobljene pametne telefone. Izvedba teh vaj je bila zelo zanimiva in je dala rezultate, kar pa je hkrati lahko tudi slabost. Enaki rezultati so uporabne rezultate. Bistvena prednost tega pristopa so zelo lahko pridobljeni na način, ki ni primeren - prepisovanje. Slabost, natančne meritve in dostopna tehnologija. Dotična aplikacija je ki bi jo nadalje izpostavila je, da dijaki nimajo stika z opremo. brezplačna. Dijaki pa imajo skoraj vsi, brez izjeme, ustrezne Ravnanje z opremo in inštrumenti je del učenja, ki ga v tem pametne telefone. Hkrati pa so pri uporabi telefonskih aplikacij primeru izgubimo. Prav tako učitelj nima nadzora nad zelo vešči. Slabost te vaje je nedostopnost vseh pripomočkov pri postopkom usvajanja znanja. Postavljanje vprašanj med vajo dijakih doma. S tem nekaterih fizikalnih področij ni mogoče namreč ni mogoče. Vse nejasnosti, vprašanja in dileme se lahko izvesti oziroma so težje izvedljiva. Tak primer je npr. dušeno razrešijo šele, ko je ura namenjena diskusiji rezultatov. nihanje, saj večina dijakov doma nima primerne vzmeti. 2.2 Računalniška simulacija laboratorijske vaje Dijaki lahko vaje izvajajo tudi preko simulacij. Našla sem kar nekaj virov vaj, ki jih lahko posredujemo preko simulacij. Na univerzi v Coloradu Boulder so leta 2002 izdelali brezplačne simulacije iz fizike na portalu PHET. Omenjene simulacije sem uporabljala že pred pričetkom pouka na daljavo. Takrat nisem imela primerne opreme za izbrano vajo. V času učenja na daljavo so se simulacije izkazale za izvrstno orodje [slika 2]. Glavna prednost izvajanje vaj preko računalniških simulacij je, da dijaki raziščejo več fizikalnih pojavov sočasno. Dijak izvaja vajo v njemu ustreznem tempu, prednost je tudi, da vajo lahko ponovi ter sam spreminja parametre. Hkrati pa je spreminjanje velikega števila parametrov tudi manjša slabost. Vaja s spreminjanjem vseh spremenljivk postane dolga, ali celo nepregledna. Dijak izgubi rdečo nit vaje. Slika 26: Posnetek zaslona pametnega telefona pri uporabi aplikacije Phyfox; vaja: Raziskovanje zemeljskega magnetnega polja. 556 3 MNENJA DIJAKOV VIRI Zaradi lastne izkušnje s poučevanjem na daljavo, me je po [1] Sun, A. and Chen, X. 2016. Online education and its končanem šolskem letu 2019/2020 zanimalo, kako so ta način effective practice: a research review. Journal of poučevanja občutili dijaki. Predvsem me je zanimalo, katera od information Technology Education: Research, vol.15, pp. zgoraj opisanih oblik laboratorijskih vaj se jim je zdela 157-190. najučinkovitejša. Vprašalnik sem poslala vsem dijakom, ki sem [2] Stern, J. Introduction to Online Teaching and Learning, jih v šolskem letu 2019/2020 poučevala. 80% dijakov je anketo University of Maryland University College (UMUC) v celoti izpolnilo. 85% teh dijakov je posredovane vaje ocenilo, DOI= http://www.wlac.edu/online/documents/otl.pdf kot dobre ali zelo dobre. Najbolj všeč jim je bila vaja podana kot [3] Sadiku, M. N. O., Adebo, O. P. and Musa, S. M. 2018. računalnička simulacija. Najmanj jim je bilo všeč iskanje Online teaching and Learning. International Journals of podatkov iz posnete vaje. Advanced Research in Computer Science and Software Engineering ISSN: 227-128X (Volume-8. Issue 2). [4] Planinšič, G., Belina, R., Kukman, I., in Cvahte, M. 2008. ZAHVALA Učni načrt: Fizika. Ministrstvo za izobraževanje, znanost Zahvaljujem se aktivu matematike in fizike na Gimnaziji in šport, Zavod RS za šolstvo. Franceta Prešerna, ki me je v času učenja na daljavo podpiral. 557 ACM Tekmovanja – Pišek, tekmovanje v programiranju z delčki ACM Competitions – Pišek, visual programming language competition Matija Lokar Maja Mujkić Univerza v Ljubljani, Fakulteta za matematiko in fiziko OŠ Koseze Jadranska ulica 19 1000 Ljubljana, Slovenija 1000 Ljubljana, Slovenija maja.mujkic@gmail.com matija.lokar@fmf.uni-lj.si POVZETEK presented. We conclude with a description of our plans for school Vzpodbujanje k učenju računalništva preko računalniških year 2020/2021. tekmovanj je razširjeno povsod po svetu, tudi v Sloveniji. V zadnjih nekaj letih je ACM Slovenija s tekmovanji pokrila skoraj KEYWORDS celotno populacijo učečih se, od najmlajših udeležencev do Programming competition, visual programming language, študentov. Vendar podatki kažejo, da se število udeležencev na Blockly, teaching programming prehodu od osnovnošolskih do srednješolskih tekmovanjih zelo zmanjša. Zato smo pripravili novo tekmovanje Pišek – tekmovanje v programiranju z delčki, ki naj bi povezoval 1 UVOD tekmovanje v računalniškem mišljenju in tekmovanje v Splošno velja, da je sodelovanje na različnih tekmovanjih lahko programiranju. koristna učna izkušnja. Kot pravi Katz v [5] lahko tekmovanje naredi poučevanje različnih predmetov bolj privlačno. Enako Večji del članka predstavlja tekmovanje samo. Navedenih je velja tudi za poučevanje in učenje računalništva. Dagiene v [3] nekaj podatkov o poskusnih tekmovanjih, ki smo ju izvedli v letu trdi, da so računalniška tekmovanja lahko ključ k novemu znanju 2020, ter opisano, kako smo prišli do take strukture tekmovanja. in atraktiven način za povezovanje tehnologije in izobraževanja. Članek zaključimo s predstavitvijo tekmovanja, kot ga Zasledimo lahko različne oblike tekmovanj, ki pokrivajo načrtujemo v šolskem letu 2020/2021. različna področja računalništva od robotike, umetne inteligence KLJUČNE BESEDE do uporabe pisarniških orodij. Prav tako se izvajajo v različnih oblikah (glej npr. Plohl [7]). Lahko so enodnevna tekmovanja, Računalniško tekmovanje, programiranje z delčki, Blockly, lahko zasnovana kot večmesečna priprava in predstavitev izdelka, poučevanje programiranja lahko kot reševanje določenega skupka nalog. V strokovnih ABSTRACT krogih se vodi živahna razprava, kakšna oblika je najprimernejša v povezavi z učnim procesom. Vendar je še vedno prevladujoča Promoting computer science through programming competitions oblika računalniških tekmovanj reševanje programerskih nalog, is widespread all around the world, also in Slovenia. In the last torej oblika, kot jo uporablja Mednarodna olimpijada iz years ACM Slovenia established almost a complete vertical line informatike (IOI [4]). Tekmovalci rešujejo naloge, ki zahtevajo of competitions aimed from the youngest up to the university rešitev določenega algoritmičnega problema v obliki programov. students. As a huge gap in attendance between primary and Pravilnost teh programov se preverja avtomatsko in temelji na secondary school, we started to prepare a new competition, primerjavi izhodnih rezultatov. named Pišek - Programming with Blocks Competition with the goal to address the area between Computational thinking and problem solving with programming and algorithms. 2 RAČUNALNIŠKA TEKMOVANJA V The main part of the paper is the presentation of the competition. SLOVENIJI We discuss some of the decisions about its structure. Some data Računalniška tekmovanja imajo v Sloveniji zavidljivo about the two trial competitions we conducted in 2020 are zgodovino. Vse se je začelo že leta 1977 z idejo o organizaciji tekmovanja, ki bi dopolnjevalo poučevanje računalništva, ki so ga od šolskega leta 1971/1972 poskusno izvajali na nekaj srednjih šolah [11 šola, Batagelj/Krapež …]. Kot kažejo podatki v Tabeli 1, povzeti iz [1], je bilo tekmovanje zelo dobro sprejeto. Permission to make digital or hard copies of part or all of this work for personal or Kot pravi Grobelnik v [2] "se je na slovenskih srednješolskih classroom use is granted without fee provided that copies are not made or distributed računalniških tekmovanjih prekalilo veliko generacij dijakov, ki for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must dandanes po večini predstavljajo okostje slovenske računalniške be honored. For all other uses, contact the owner/author(s). skupnosti. Bivši tekmovalci so dandanes profesorji na univerzah, Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 558 raziskovalci na institutih, predvsem pa si brez njih ni mogoče Tabela 7. Število tekmovalcev osrednjih tekmovanj ACM v predstavljati slovenske računalniške industrije." zadnjih letih leto Bober RTK UPM Tabela 6. Število tekmovalcev v prvih letih 2011/2012 3380 273 174 1977 47 2012/2013 8147 234 153 1978 79 2013/2014 11653 278 159 1979 92 2014/2015 16797 306 210 1980 88 2015/2016 24714 309 186 1981 101 2016/2017 29124 351 171 1982 101 2017/2018 29561 310 156 1983 137 2018/2019 33356 341 126 1984 213 2019/2020 28803 306 123 V teh štirih desetletjih je poučevanje računalništva dosegalo Skupna ugotovitev še z drugimi kolegi je bila tudi ta, da naj svoje vzpone in padce, pojavljala so se različna mnenja glede bi bilo to tekmovanje v reševanju problemov z zapisom vsebine predmetnika in oblike izvedbe z računalništvom algoritmov, kjer bi kot programski jezik uporabljali programski povezanih predmetov. Top je vsekakor vplivalo tudi na jezik z delčki, kot so na primer Scratch, Snap in podobni. tekmovanja in danes lahko slovenski učenci, dijaki in študenti Predvsem na pobudo J. Demšarja je bila sprejeta odločitev, da pri sodelujejo na zelo različnih tipih računalniških tekmovanj. tekmovanju ne bi uporabili jezika Scratch, pa čeprav je bil (in je Omejili se bomo na tekmovanja, ki potekajo v sklopu ACM še) ta po slovenskih šolah med vsem jeziki, ki omogočajo Slovenija (Slika 27). programiranje z delčki, najbolj razširjen. Podlaga za to odločitev je bilo prepričanje, da Scratch prvenstveno ni programski jezik, namenjen reševanju problemov in zapisu algoritmov, ampak bolj jezik in okolje, namenjeno ustvarjalnemu izražanju učencev. Prav tako je pri Scratchu velik poudarek na medsebojnem sodelovanju učencev, deljenju izdelkov in njihovemu spreminjanju ([6]). Zelo smeli načrti glede tekmovanja so bili taki, da bi poskusili zajeti med četrtino in polovico sodelujočih na tekmovanju Bober. Ker to pomeni, da naj bi sodelovalo med 8 in 14 tisoč tekmovalci, je bilo očitno, da je potreben sistem, ki bi omogočal avtomatsko Slika 27. Tekmovanja v okviru ACM Slovenija preverjanje pravilnosti rešitev. Trenutno so uradna tekmovanja pod okriljem ACM Slovenija Na srečo smo leta 2017 na mednarodni delavnici za pripravo tri: nalog za tekmovanje Bober navezali stike s kolegi iz Francije. • Bober - Mednarodno tekmovanje iz računalniškega Spoznali smo njihov sistem Algorea (http://www.france-ioi.org). razmišljanja Ta izstopa med tistimi redkimi sistemi za preverjanje pravilnosti • RTK - Srednješolsko tekmovanje ACM iz računalništva in programskih rešitev, ki podpirajo jezike za programiranje z informatike delčki. V sodelovanju s kolegi iz Francije smo njihov sistem priredili • UPM - Univerzitetni programerski maraton za uporabo tudi v slovenskem jeziku, ga poimenovali Pišek in Prvi dve tekmovanji sta namenjeni predvsem osnovno in postavili na spletni naslov https://pisek.acm.si/. Pri prevajanju in srednješolcem, tretje pa univerzitetnim študentom. Vsa so po postavitvi sistema so sodelovali G. Jerše, M. Lokar in J. Vičič, svoji osnovni obliki zasnovana in vpeta v mednarodna G. Anželj pa je prispeval prevod jezika Blockly. tekmovanja (Bebras, IOI in ACM ICPC). V Tabeli 2 so zbrani Naslednjega leta, 2018, so v okviru ŠPIK projekta ProNAL podatki zadnjih 10 let tekmovanj. Ker imajo tekmovanja različne študentje različnih fakultet Univerze v Ljubljani pod vodstvom nivoje, so podatki dani za prvi, najmnožičnejši, šolski nivo. Tam M. Lokarja in G. Jeršeta sestavili nekaj nalog za Piška in ni omejitve glede števila udeležencev. pokazalo se je, da bi na sistemu Pišek lahko vzpostavili Kot kažejo podatki, obstaja precejšen "prepad" med številom tekmovanje, ki bi bil most med Bobrom (tekmovanjem v sodelujočih na tekmovanju Bober in na tekmovanju ACM RTK. računalniškem razmišljanju) in ACM RTK-jem (tekmovanju v Tako sta A. Brodnik in M. Lokar od leta 2015 dalje imela algoritmih). številne razgovore o tekmovanju za "vmesno stopnjo", še posebej Konec leta 2018 sta dva študenta (K. Špenko in Ž. Flajs) v pa po uvedbi izbirnega predmeta Računalništvo v drugi triadi OŠ. sodelovanju z M. Lokarjem dodala vrsto nalog. Prav tako so se Primarna naloga tega tekmovanja naj bi bila popularizacija uvedli novi tipi nalog. Še bolj pa je Pišek postal uporaben učenja programiranja. spomladi 2019, ko so v okviru novega ŠPIK projekta Pišek študentje pod vodstvom M. Lokarja, G. Jeršeta in K. K. Ošljak v sam sistem dodali preko 300 različnih nalog. 559 3 PIŠEK – TEKMOVANJE V PROGRAMIRANJU Z DELČKI 3.1 Priprava poskusnega tekmovanja Ker smo s šol dobivali zelo pozitivna mnenja glede uporabe sistema Pišek in ker je želja, premostiti omenjeni prepad v številu udeležencev res velika, smo se odločili poskusiti s tekmovanjem. Septembra 2019 je M. Lokar na sestanek povabil učitelje z osnovnih in srednjih šol ter profesorje s fakultet, ki so že prej sodelovali pri tekmovanjih ACM. Odzvalo se jih je 19, iz zelo različnih ustanov – osnovnih šol, srednjih šol, z univerz, Zavoda RS za šolstvo. Decembra 2019 je ACM Slovenija formalno ustanovil Programski svet Tekmovanja Pišek. Razdelili smo se v skupine, določili vodje in začeli priprave. Poleg najbolj očitnega, torej nalog, smo potrebovali še tekmovalce. Slika 29. Primer naloge za 4. in 5. razred Večina nalog za osnovno šolo je bila v obliki naloge na mreži, kjer se glavna figura premika in izvaja »naloge«. Pogosto smo uporabili tudi naloge z želvjo grafiko. Pri sestavljanju nalog se je pokazala tudi prednost uporabe jezika Blockly, saj ta omogoča, da v programsko okolje dodajamo delčke s čisto novimi ukazi kot npr. poberi lešnik, naberi med, izvedi pirueto … Tako so delčki, ki so sicer konceptualno enaki (na primer, naredi nekaj s predmetom, ki je na polju, kjer je trenutno lik), v različnih nalogah poimenovani različno (poberi plastenko, pojej deteljico …) Prav tako pri sestavljanju naloge tvorimo nove delčke in tako v posamezni ukaz "skrijemo" določeno kompleksnost (npr. v nalogi uporabimo delček "nariši kvadratek" ali pa "preberi podatke v tabelo") Slika 28. Spletišče tekmovanja Pišek Prav tako smo sledili določenim dognanjem s področja didaktike računalništva in med nalogami večkrat uporabili tudi 3.2 Izvedba prvega poskusnega tekmovanja tipe nalog, kjer problem že vsebuje napisan program, ki pa ga je V šolskem letu 2019/2020 smo načrtovali tri poskusna bilo potrebno ali popraviti ali pa le urediti. tekmovanja, preko katerih bi lahko dobili čim več izkušenj, na Pri prvem poskusnem tekmovanju februarja 2020 je podlagi teh pa bi v šolskem letu 2020/2021 pripravili prvo sodelovalo 10 osnovnih in 7 srednjih šol oz. 374 učencev in 269 »pravo« tekmovanje. dijakov. Njihov odziv je bil odličen. Tekmovalce in mentorje Večina sodelujočih pri organizaciji tekmovanja smo bili smo pozvali, da po tekmovanju izpolnijo anketo, s katero smo hkrati tudi mentorjih učencem in dijakom. Povabili pa smo še pridobili povratne informacije. Mentorji so pohvalili sistem, nekaj učiteljev osnovnih in srednjih šol, vendar smo pazili, da pripravljenost, obveščanje, tekmovalci so bili večinoma število ne bi bilo preveliko, saj nismo poznali zmožnosti zadovoljni z nalogami in si takega tekmovanja želijo. francoskega strežnika. Vedeli smo tudi, da nas po tekmovanju Tabela 8. Rezultati prvega poskusnega tekmovanja čakajo obsežnejše vsebinske analize. Zanimalo nas je predvsem, Št. Povp. št. Št. tekm. z Št. tekm. kako smiselno razdeliti tekmovalce v kategorije in katere Kategorija Št. tekm. možnih doseže- vsemi z 0 programske koncepte uporabiti. točk nih točk točkami točkami Tekmovanje smo izvedli v petih kategorijah glede na starost 4. in 5. razred 179 600 417 92 24 tekmovalcev: 6. in 7. razred 167 600 233 7 18 8. in 9. razred 48 600 252 1 10 • 4. in 5. razred osnovne šole, 1. in 2. letnik 203 500 59 4 131 • 6. in 7. razred osnovne šole, 3. in 4. letnik 66 500 59 0 42 • 8. in 9. razred osnovne šole, 3.3 Priprava in izvedba drugega poskusnega • 1. in 2. letnik srednje šole, tekmovanja • 3. in 4. letnik srednje šole. Pri načrtovanju drugega poskusnega tekmovanja smo upoštevali Tekmovalci so imeli na voljo 40 minut, naloge so lahko rezultate tekmovanja ter mnenja, ki smo jih dobili preko anket, oddajali večkrat, sistem pa jim je takoj javil, ali je naloga rešena ki so jih izpolnili tekmovalci in mentorji po prvem poskusnem pravilno ali ne. tekmovanju. Tako smo upoštevali dejstvo, da so bili tekmovalci v nekaterih kategorijah izjemno uspešni (npr. v kategoriji 4. in 5. razred je izmed 179 tekmovalcev kar 92 njih prejelo vse točke), v nekaterih kategorijah pa so bili rezultati zelo slabi (v kategoriji 560 3. in 4. letnih dveh nalog ni rešil nihče od tekmovalcev, v Število doseženih točk je precej bolj enakomerno razporejeno kategoriji 1. in 2. letnik več kot polovica tekmovalcev ni dosegla kot pri prvem poskusnem tekmovanju, zato ustvarjalci nobene točke) – več prikazuje Tabela 8. Prav tako smo imeli tekmovanja ocenjujemo, da smo bolj primerno razvrstili številne razgovore glede primernosti starostne razdelitve v luči kategorije in izbrali naloge, ki so omogočale realno razvrstitev. besedil nalog ter kako upoštevati zelo različno predznanje Zelo malo tekmovalcev se je odločilo za reševanje nalog v učencev istih starostnih kategorij. Zato smo se odločili, da najtežji kategoriji Srednja šola – poznavalci, zato smo se odločili, spremenimo kategorije. Med tekmovalci v osnovni šoli so velike da v prihodnjih tekmovanjih te kategorije verjetno ne bo. razlike, ki pa niso odvisne od njihove starosti, ampak predvsem Verjamemo pa, da, ko se bodo učenci, dijaki in mentorji sistema od tega, koliko let so obiskovali izbirni predmet računalništvo. navadili, da se jih bo več opogumilo in se preizkusilo v najtežjih Seveda je treba upoštevati tudi kognitivni razvoj otrok in učni kategorijah. Hkrati pričakujemo, da se bodo tisti najspretnejši načrt v šoli. Tako so nastale nove kategorije: raje udeležili tekmovanj, kjer se programira v »pravih« • 4.-6. razred osnovne šole – začetniki programskih jezikih, s tem pa bo naš cilj, da zapolnimo vrzel med • 4.-6. razred osnovne šole – napredni Bobrom in RTK tekmovanjem izpolnjen. • 7.-9. razred osnovne šole – začetniki 3.4 Tretje poskusno tekmovanje • 7.-9. razred osnovne šole – napredni Tretjega poskusnega tekmovanja iz očitnih razlogov nismo • Srednja šola – začetniki izpeljali. Kljub vsemu smo se odločili, da bomo v šolskem letu • Srednja šola – napredni 2020/2021 izpeljali pravo tekmovanje. Predvideni termin je februar 2021. • Srednja šola – poznavalci Vse naloge z obeh poskusnih tekmovanj so dostopne na Drugo poskusno tekmovanje je bilo načrtovano v mesecu spletni strani https://pisek.acm.si, kjer objavljamo tudi naloge za aprilu 2020, vendar je prišlo do epidemije in smo morali najti pripravo na tekmovanje. novo rešitev. Izpeljali smo poskusno odprto spletno tekmovanje, ki pa žal ni bilo tako obiskano, kot smo si želeli. Prav tako smo preko anket dobili precej manj povratnih informacij s strani 4 TEKMOVANJE V ŠOLSKEM LETU mentorjev in tekmovalcev. Sodelovalo je 296 tekmovalcev, 2020/2021 večina med njimi se je preizkusila v več kategorijah. Oglejmo si Oglejmo si nekaj vodil, ki sestavljavce vodijo pri načrtovanju in povzetek rezultatov tekmovanja po kategorijah (vsi rezultati so izbiri nalog za tekmovanje. objavljeni na spletni strani https:/ tekmovanja.acm.si/?q=node/618): 4.1 Kategorije in programski koncepti Tabela 9. Rezultati drugega poskusnega tekmovanja Št. Povp. št. Št. tekm. Ob določitvi sedmih tekmovalnih kategorij smo določili tudi, Kategorija Št. Št. tekm. z 0 kateri programski koncepti bodo uporabljeni v izbranih tekm. možnih doseže- z vsemi točk nih točk točkami točkami tekmovalnih nalogah za posamezno kategorijo. Seznam je 4.-6. razred objavljen na spletni strani tekmovanja, na začetniki 170 500 269 35 17 https://tekmovanja.acm.si/?q=pisek/tekmovalne-kategorije. 4.-6. razred Seveda ni nujno, da bodo v nalogah za posamezno tekmovanje napredni 54 500 103 3 23 pokriti vsi našteti koncepti. 7.-9. razred Tako bodo mentorji lažje svetovali svojim tekmovalcem pri začetniki 80 600 136 7 40 izbiri kategorije. 7.-9. razred napredni 35 600 100 2 24 4.2 Naloge srednja šola začetniki 63 500 198 12 29 Posamezna kategorija vsebuje 5 ali 6 nalog. Naloge so različnih srednja šola tipov. Tako določene naloge zahtevajo, da tekmovalci sestavijo napredni 12 500 291 3 2 program. Spet druge so naloge Parsonsovega tipa, torej morajo srednja šola tekmovalci dane ukaze urediti v ustrezno zaporedje, pri tretjih pa poznavalci 10 600 300 4 4 je potrebno v danem programu poiskati in odpraviti napake. Naloge vsebujejo različne programske koncepte in so Kot vidimo, je daleč največ tekmovalcev sodelovalo v različnih težavnostnih stopenj. Praktično pri vseh kategorijah kategoriji 4.-6. razred ZAČETNIKI, kjer je tudi največ tistih, ki pazimo, da je vsaj ena naloga taka, da jo lahko rešijo vsi so dosegli vse možne točke. Nekoliko zaskrbljujoče je dejstvo, tekmovalci, da v več kategorijah polovica tekmovalcev ni dobila nobene Naloge za osnovno šolo so večinoma naloge na mreži točke, v kategoriji 7.-9. razred – napredni pa je takih skoraj 70 %. (Slika 30). Vendar je podrobnejša analiza zapisov tekmovalnega sistema pokazala, da velika večina teh sploh ni poskusila nalog reševati »zares«, ampak so si naloge le ogledali. Možno je tudi, ker je tokratni način omogočal, da so se z istim uporabniškim imenom lotili reševati naloge v več kategorijah, da se med tekmovanjem v eni in drugi kategoriji niso odjavili in ponovno prijavili in jim je zato zmanjkalo časa. 561 Naloge lahko otežimo na različne načine. Predvsem pri mlajših kategorijah se je pokazalo, da je precejšnja razlika, če pri nalogi ponudimo tudi nepotrebne delčke (in jih morda še "skrijemo" v kategorije – npr. naloga na Slika 30) ali pa so dani le delčki, potrebni za rešitev (npr. naloga na Slika 33). Prav tako lahko nalogo otežimo, če omejimo število delčkov, ki jih lahko uporabi program (glej podatek desno zgoraj pri nalogi na Slika 33). Slika 30. Naloga na mreži z več testi Pogoste so tudi naloge z želvjo grafiko (Slika 31). Slika 33. Naloga z omejitvijo števila delčkov Tako je naloga Pišek pospravlja smeti rešljiva le z uporabo delčkov, ki se nanašajo na premikanje ter z delčkoma poberi plastenko in pospravi plastenko. Vendar bi v tem primeru tekmovalec potreboval 18 delčkov. A pri tej nalogi piše, da je na voljo le 11 delčkov. Torej mora tekmovalec uporabiti zanko ponavljaj in s tem zmanjšati število ukazov v svojem programu. Kakor hitro program porabi preveč delčkov, sistem rešitve ne sprejme, niti je ne »pregleda«. Takrat le zapiše, »Uporabljaš preveč delčkov!« (Slika 34). Slika 31. Naloga z želvjo grafiko Nekaj (predvsem med nalogami za srednjo šolo) pa je tudi "klasičnih" programerskih nalog, kot je na primer ta, prikazana na Slika 32. Slika 34. Opozorilo ob uporabi prevelikega števila delčkov Prav tako pri nalogah, ki preverjajo zahtevnejše programske koncepte, pogosto uporabimo več testov. Vsi so tekmovalcem vidni. Prav tako sistem označi, kateri testi so bili opravljeni in kateri ne (Error! Reference source not found. ). Z uporabo več testov se izognemo temu, da bi tekmovalci rešili nalogo, ki bi delovala izključno za dane vhodne podatke. Slika 32. "Klasična" programerska naloga 562 da bo tekmovanje potekalo (tako kot tekmovanje Bober) vsaj teden dni (posamezen mentor bo sam izbral enega ali več terminov v sklopu odprtosti tekmovanja) menimo, da bodo vsi, ki jih sodelovanje zanima, lahko tekmovali. Pri določitvi datuma Slika 35. Rezultati testov smo upoštevali, da bomo v prihodnjih letih tekmovanje morda nadgradili tudi s tekmovanjem na državni ravni. Primer take naloge je Pišek gre čez reko. 5 ZAKLJUČEK Želja ustvarjalcev Piška in organizatorjev ACM tekmovanja v programiranju z delčki ni organizirati še eno tekmovanje, ki bi le preverjalo poznavanja programiranja, temveč ta, da bi se čim več učencev in dijakov sploh srečalo s programiranjem in ugotovilo, kako zabavna dejavnost je to lahko. Celotna organizacija tekmovanja poteka na povsem prostovoljni osnovi. Sodelujejo študentje, učitelji in profesorji, ki verjamejo, da je programiranje veščina, ki nam pride prav na vseh področjih in ki želijo, da bi stavek »Programiranje je težko.« zamenjal stavek »Programiranje je zabavno.«. Vse, ki vas sodelovanje pri tekmovanju na kakršen koli način zanima (sestavljanje nalog, prispevanje idej za naloge, Slika 36. Naloga z več testi – Test 1 sodelovanje pri organizaciji, pri tehničnem razvoju portala Pišek, pri razgovorih o primernosti določene naloge…), vabimo, da nam pišete na naslov pisek@acm.si. Prav vsak sodelavec je resnično dobrodošel! VIRI IN LITERATURA [1] Batagelj, V. in soavtorji, Enajsta šola računalništva, Rešene naloge z republiških tekmovanj 1977 – 1987, DMFA in ZOTKS, 1988 [2] Brank, J. 2006. Rešene naloge s srednješolskih računalniških tekmovanj: 1988-2004. Institut Jožef Stefan, Ljubljana. [3] Dagiene, V. 2006. Competition in information technology Slika 37. Naloga z več testi – opozorilo – learning in an attractive way. In Pohl, W. (ed.) Perspectives on Computer Science Competitions for (High Na Slika 36 vidimo, kako bi tekmovalec lahko rešil prvi test School) Students. http://www.bwinf.de/competitionworkshop/papers.html. zgolj z osnovnim poznavanjem zaporedja ukazov. Vendar pa to zaporedje ne reši drugega testa. Ko program zaženemo, se izpiše [4] General Assembly of IOI: International olympiad in opozorilo, da je ob izvajanju drugega testa prišlo do napake informatics regulations. 2019. (Slika 37). https://ioinformatics.org/files/regulations19.pdf. Opozoriti velja, da je zasnova tekmovanja taka, da delne [5] Katz, L. G., Chard, S.C. 1989. Engaging children's minds: rešitve (in s tem del točk) niso predvidene. Naloga mora biti The project approach. Norwood. NJ: Ahlex. rešena v celoti. [6] Maloney, J., Resnick, M., Rusk, N., Silverman, B., & Eastmond, E. 2010. The Scratch programming language 4.3 Termin tekmovanja and environment. V ACM Transactions on Computing Education (TOCE), 10(4). V koledarju je že veliko tekmovanj. Določiti primeren termin je precej zahtevno. Poleg tekmovanj so tu obdobja, ko so učenci, [7] Pohl, W., et al. 2006. Computer science contests for dijaki in učitelji dodatno obremenjeni z ocenjevanjem, secondary school students: approaches to classification. nacionalnimi poskusi znanja, maturo, ali pa so celo odsotni Informatics in Education – An International Journal 5(1), 125-132. zaradi obvezne prakse. Po obširnem usklajevanju smo se odločili, da bomo izvajali tekmovanje v februarju. Glede na to, 563 Uporaba Sistema Pišek pri pouku neobveznega izbirnega predmeta računalništvo Teaching elective subject computing using system Pišek Matija Lokar Maja Mujkić Univerza v Ljubljani, Fakulteta za matematiko in fiziko OŠ Koseze Jadranska ulica 19 1000 Ljubljana, Slovenija 1000 Ljubljana, Slovenija maja.mujkic@gmail.com matija.lokar@fmf.uni-lj.si POVZETEK tem navajanju na natančnost in doslednost lahko izrabimo lastnosti računalnika. Ta ne upošteva čustev in obrazne mimike, V članku je v prvem delu predstavljen Sistem Pišek, spletna ne bere misli, ne predvideva, kaj smo želeli povedati, pa smo se storitev, ki vsebuje bogato zbirko nalog s samodejnim samo nerodno izrazili in podobno. Računalnik naredi le tisto, preverjanjem pravilnosti rešitev. Naloge rešujemo s pomočjo samo tisto in točno tisto, kar smo mu »ukazali«. programskega jezika Blockly, ki omogoča programiranja z V osnovni šoli je eden od ciljev pri neobveznem izbirnem delčki. V drugem delu prispevka je opisan način uporabe Piška predmetu računalništvo, ki se izvaja v drugi triadi, tudi ta, da pri poučevanju osnovnih konceptov programiranja pri znajo učenci algoritem zapisati s programom v nekem neobveznem izbirnem predmetu računalništvo, ki se izvaja v programskem jeziku. Programski jeziki, kot so Java, C, Python drugi triadi OŠ. Pri tem je predstavljeno tako delo v razredu, kot in podobni, so za osemletnike, ki se prvič srečujejo s tudi uporaba Piška v drugem delu šolskega leta 2019/2020, ko je programiranjem, izredno zahtevni. Poleg tega, da se morajo bil pouk izvajan na daljavo. naučiti »programerskega« razmišljanja, morajo usvojiti še KLJUČNE BESEDE sintakso in semantiko, ki sta pri vsakem jeziku drugačni. Učenja programiranja pri najmlajših (in tudi pri starejših začetnikih) se Poučevanje, osnovna šola, programiranje, programski koncepti, je veliko lažje lotiti s programskimi jeziki, kjer programa ne programiranje z delčki, delo na daljavo, Blockly tipkamo, ampak ga zložimo iz predpripravljenih delčkov. Na ta ABSTRACT način se izognemo tipkarskim napakam, napačni uporabi presledkov, uporabi velikih in malih črk, manjkajočim The first part of the article presents Pišek, a system with a rich podpičjem na koncu vrstic in drugim sintaktičnim napakam. collection of automatic verifiable problems. Problems are being Učenci se lahko osredotočijo le na pomembnost vrstnega reda solved in visual programming language. The second part of the ukazov, uporabe zank, pogojnih stavkov in podobno. article describes the usage of the system in teaching basic Pri učenju je eden od najpomembnejših elementov povratna programming concepts in the elective subject Computing informacija. Hitrejša in natančnejša je, bolj je smiselna in attended by pupils in the second triad of the primary school. The uporabna. A pri reševanju problemov s programiranjem je article presents work in classroom as well as the usage of Pišek pogosto več poti do rešitve. Zato večinoma splošna in enovita in the second part of the school year 2019/2020 when distance povratna informacija ni možna. To pomeni, da mora učitelj learning has been used. pregledati vsako oddano nalogo posebej. Če ima v razredu 25 učencev, je precej nemogoče hitro pregledati vse, kar so učenci KEYWORDS v eni uri ustvarili in jim hitro dati kvalitetno povratno informacijo. Teaching, elementary school, computer programming, Zato so orodja, ki učitelju pomagajo pri pripravi povratnih programming concepts, visual programming languages, distance informacij tako pomembna. learning and teaching, Blockly 2 O SISTEMU PIŠEK 1 UVOD Sistem Pišek je portal, namenjen uporabi v slovenskem šolskem Programiranje je veščina. Od posameznika zahteva natančnost in prostoru kot pomoč pri poučevanju programiranja. Je javno doslednost. Lastnosti, ki nam pogosto prideta prav v življenju, dostopen in njegova uporaba je povsem prosta. vsekakor pa tudi učencem pri poljubnem predmetu v šoli. In pri Osnutek portala je nastal leta 2018 na osnovi francoskega sistema Algorea, ko so v okviru ŠIPK projekta ProNAL študenti pod vodstvom M. Lokarja in G. Jeršeta sestavili prvih nekaj nalog za Piška. Sam sistem pa je postal uporaben za splošno rabo, Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed ko se je leta 2019 v sklopu projekta Naloge za poučevanje in for profit or commercial advantage and that copies bear this notice and the full učenje računalniškega mišljenja – Portal Pišek (NPUR), pri citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). katerem so sodelovali Fakulteta za matematiko in fiziko Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Univerze v Ljubljani, Kreativni center Poligon ter Code Week © 2020 Copyright held by the owner/author(s). 564 Slovenija, močno razširila baza nalog, ki jih lahko rešujemo na Pišku. Nadaljnji razvoj Sistema Pišek je v letu 2019/2020 potekal v sklopu priprav na izvedbo ACM Tekmovanja v programiranju z delčki. Sama priprava na tekmovanje in izvedba dveh poskusnih tekmovanj so močno razširili obstoječo zbirko nalog. Prav tako je sistem dobil novo podobo, nov grafični vmesnik. Slika 39. Delčki, razporejeni v kategorije 3 UPORABA SISTEMA PIŠEK PRI POUKU Za začetnike v učenju programiranja je ključno dvoje: sistem, ki omogoča ukvarjanje z vsebino problema in sistem, ki omogoča takojšnjo povratno informacijo. Sistem Pišek zajema oboje. Sistem Pišek je lahko učitelju v veliko pomoč, saj v razredu omogoča diferenciacijo in individualizacijo. Vsebuje naloge čistih začetkov in naloge, ki zahtevajo kompleksnejša znanja. Ker so enake naloge pripravljene v različnih težavnostnih Slika 38. Naloga v posodobljenem grafičnem vmesniku stopnjah, lahko učenci rešujejo le najlažje ali najtežje. Ker sistem Podrobneje si o samem konceptu Piška in njegovem razvoju sam javi, ali je naloga opravljena ali ne, se lahko učitelj posveti lahko preberete v prispevku [2], tukaj pa si oglejmo nekaj tistim učencem, ki imajo težave. Učenci lahko sami po uspešno poudarkov: opravljeni nalogi nadaljujejo z drugo nalogo in jim ni treba čakati, da učitelj nalogo pregleda. Ker sistem omogoča tudi prijavo z uporabniškim računom, ima učenec (in učitelj) pregled nad • Na levi strani posamezne naloge je besedilo, ki opisuje opravljenim delom in lahko rešuje vedno nove naloge. problem. Desni del je namenjen sestavljanju programa. Najprej je stolpec, kjer so navedeni delčki, ki so na 3.1 Zasnova sistema voljo. Od sestavljavca naloge je odvisno, ali bo navedel le delčke, ki so potrebni za rešitev, ali bo dodal še kakšne nepotrebne. Prav tako lahko te delčke razporedi v kategorije (Slika 39) ali ne (Slika 38). • Večina nalog je tipa "naloge na mreži" (glej npr. primer na Slika 38). Vse se dogaja na praviloma pravokotni mreži, kjer se liki gibljejo po mreži in opravljajo določene akcije. Program je napisan pravilno, če je končno stanje na mreži tako, kot je zahtevano • Zaradi uporabe jezika Blockly so delčki, ki so sicer konceptualno enaki (na primer, naredi nekaj s predmetom, ki je na polju, kjer je trenutno lik), v različnih nalogah lahko poimenovani različno (poberi Slika 40. Učna pot plastenko, pojej deteljico). Prav tako lahko sestavljavec naloge tvori nove delčke in tako v Sistem je zasnovan tako, da se lahko učitelj posveti le enemu posamezni ukaz "skrijem" določeno kompleksnost programskemu konceptu ali pa naredi ponovitev različnih (npr. v nalogi je delček "nariši kvadratek"). Ustvarjanja konceptov. V prvih urah učenja programiranja je pomembno, da funkcij, ki so za to potrebne, v jezikih, kot je npr. učenci usvojijo zaporedje ukazov, kasneje to nadgradijo z Scratch, ne moremo "skriti". • Sistem omogoča zelo različne tipe nalog. Pri tem bi zankami, pogojnimi stavki, spremenljivkami in drugimi posebej izpostavili naloge tipa "zloži delčke v pravi programskimi koncepti. program" (primer je prikazan na Slika 47). Gre za tako imenovan Parsonsov tip problemov ([4]) za katerega so raziskovalci pokazali (glej na primer [5]), da precej pripomore k lažjemu in hitrejšemu osvajanju osnovnih programskih konceptov. 565 3.3 Povratna informacija za učenca in učitelja Zaradi takojšnje povratne informacije, bodisi pravilne (Slika 51), bodisi napačne (Slika 50), lahko učenec samostojno rešuje naloge v svojem lastnem tempu. Učitelj mu pomaga z usmeritvami. Če gre učencu težje, lahko rešuje samo naloge na prvi stopnji, če mu gre zelo dobro, jih lahko rešuje na vseh ali pa samo na zadnji. Sistem poleg pravilnosti rešitev pregleduje tudi optimizacijo programa (z omejitvijo števila delčkov, ki jih sme učenec uporabiti, je prisiljen v uporabo zank, senzorjev, pogojnih stavkov). S tem učitelju ni treba pregledati vsakega programa Slika 41. Seznam programskih konceptov posebej, ampak se lahko posveti tistim posameznikom, ki imajo težave oz. potrebujejo dodatno pomoč. Ko imajo osnovno znanje, se lahko nalog lotijo »po zgodbah«. Sistem omogoča tudi prijavo in s tem shranjevanje dosežkov. Te so zelo uporabne, ko želimo ponavljati različne koncepte in Tako lahko vsak učenec nadaljuje tam, kjer je ostal, učitelj pa utrjevati znanje ali učence pripraviti na tekmovanje. Nekateri ima s tem pregled opravljenih nalog za vsakega posameznega bodo raje reševali naloge z roboti, drugi naloge z gosenico, za učenca. dekleta bo morda najbolj zanimiva plesalka. V Zgodbah je deset tematsko urejenih poglavij: Pišek, Robot, Ples, Tabornik, Zmajček, Gosenica Eva, Avto, Gasilka, Ladja ter Pišek in želva Slika 44. Sistem omogoča prijavo (Slika 42). Ko učenec zaključi z eno zgodbo, nadaljuje z drugo in se pri tem kljub utrjevanju istih programskih konceptov ne dolgočasi ([2]). Slika 42. Učenci si lahko sami izberejo junaka, s katerim se bodo učili Slika 45. Pregled uspešnosti reševanja Ob seznamu nalog (Error! Reference source not found. ) so različne oznake. Hitro je vidno, ali je naloga v celoti rešena ali delno, vidi se tudi, ali se je učenec naloge že lotil ali pa sploh še ne. 4 Uporaba Piška na OŠ Koseze Slika 43. Sklop Code Week Na OŠ Koseze smo Sistem Pišek začeli uporabljati ob koncu šolskega leta 2018/2019, pri učencih 4. in 5. razreda predvsem V četrtem sklopu so izbrane naloge razvrščene glede na kot utrjevanje že osvojenih konceptov, pri učencih od 7.-9. starostne skupine otrok oziroma težavnost. Kot predlaga že ime razreda pa kot uvod v programiranje. sklopa, je ta v prvi vrsti namenjen izvajanju dejavnosti v okviru V šolskem letu 2019/2020 so učenci 4. razreda s pomočjo Slovenskega tedna programiranja – Code Week, ko učitelji ter Sistema Pišek usvojili koncepta zaporedje ukazov in zanke mentorji prostovoljci iz vse Slovenije poskrbijo, da čim več otrok ponavljaj. Prvo uro, ko so se srečali s sistemom Pišek, smo si spozna programiranje. pogledali, kako je stran sestavljena, kako se delčki sestavljajo, da 3.2 Usmerjanje učencev pri ustrezni izbiri nalog so nekje delčki »skriti« v kategorije ipd. Opozorjeni so bili, da morajo natančno prebrati navodilo naloge in da morajo biti Predvsem ob ponavljanju konceptov lahko pustimo učencem pozorni, na kakšen način se junaki premikajo (Slika 46). Učenci proste roke. Sistem ima naloge zložene tudi po zgodbah, v so na spletni strani http://pisek.acm.si/ izbrali Programski katerih nastopajo različni junaki in vsak učenec gre lahko v svoj koncepti (Slika 40) in Zaporedje ukazov (Slika 41) in reševali domišljijski svet. Pri tem bo občutek, da igra igrico, še večji, naloge. Najprej so morali rešiti prve tri (zato, da so začeli delati čeprav bo sestavljal program in utrjeval programersko in da niso samo pregledovali nalog), potem pa so lahko izbrali razmišljanje. Junakov je na voljo dovolj, deset. V primeru, da katero koli nalogo na seznamu. Malo pred koncem ure so učenci izrazijo željo po novem junaku, lahko stopimo v stik z pokazali, kako uspešni so bili, torej, koliko nalog jim je uspelo ustvarjalci sistema in predlagamo še kakšnega. rešiti (sistem tudi brez prijave beleži uspešnost reševanja kot je prikazano na sliki Slika 45 dokler ne zapremo okna brskalnika). 566 Ker so bili učenci v sistem prijavljeni, so se njihovi rezultati shranili in so lahko naslednjo uro nadaljevali z nalogami, ki jih še niso rešili. Podobno smo naredili pri programskem konceptu Zanke. Učenci 5. in 6. razreda pa so ta dva koncepta ponovili in svoje znanje nadgradili s pogojnim stavkom in senzorji. Zato so izbrali Zgodbe (Slika 40) in si izbrali svojega junaka (Slika 42), naloge pa so morali reševati po vrsti, saj so na seznamu praviloma razporejene po težavnosti. Ko so prišli do nalog, ki jih še niso znali rešiti, so si izbrali drugega junaka. Ker so bili v sistem prijavljeni, so videli, katere naloge so že reševali v prejšnjem šolskem letu in so jih lahko spustili. Ker se je na začetku tako pri četrtošolcih, ki so čisti začetniki, kot pri petošolcih in šestošolcih, ki so se s temi nalogami že Slika 47. Primer Parsonsovega tipa naloge srečali, izkazalo, da imajo težave z razumevanjem načina premikanja junakov, je smiselno, da pred začetkom uporabe Kot smo že omenili, jezik Blockly omogoča avtorjem, da sistema oziroma posamezno pri vsaki od prvih nekaj nalog, dodajajo delčke s čisto novimi ukazi kot npr. "poberi lešnik", učence večkrat opozorimo na način premikanja po mreži, na "naberi med", "izvedi pirueto". S tem se ognemo uporabi funkcij, kateri je zastavljena večina nalog. Na sliki Slika 46 sta prikazana ki so v tem starostnem obdobju še preveč abstraktne. Po drugi dva sklopa ukazov za premikanje – uporabljamo pa lahko tudi strani pa smo opazili, da to pripomore tudi k navajanju na druge, npr. premike glede na smeri neba. Z učenci lahko natančnejše branje navodil. Tako je v nekaterih nalogah dovolj, naredimo tudi vajo »v živo«, tako da se učitelj ali učenec da junak pride na mesto s predmetom in ga s tem samodejno premikata po navodilih kot so na delčkih. Tako si najlažje pobere, v drugih pa mora za to uporabiti ukaz. predstavljajo razliko med »obrni se desno« in »premakni se Sistem se je izkazal za izredno koristnega tudi v času šolanja desno«. na daljavo, saj so učenci lahko reševali naloge, primerne svojemu predznanju, in pri tem takoj dobili povratne informacije. Učitelju so poslali zaslonsko sliko uspešnosti (Error! Reference source not found. ), da je lahko spremljal njihov napredek. Če kakšne naloge niso znali rešiti, so poslali povezavo do naloge in zaslonsko sliko njihove rešitve, učitelj pa jih je usmeril k pravilni rešitvi. Učenci od 4. do 9. razreda, ki obiskujejo neobvezne oz. obvezne izbirne predmete računalništva ali robotiko z elektroniko in elektrotehniko z robotiko, so se v šolskem letu 2019/2020 udeležili dveh poskusnih tekmovanj v programiranju z delčki Pišek. Tekmovanje je zastavljeno tako, da se lahko izvede v času pouka. Ima več kratkih nalog z različnimi Slika 46. Delčki z ukazi za premikanje programskimi koncepti in različnih težavnosti, tako da lahko učenci (in mentorji) dobijo celostno povratno informacijo o Predno se učenci lotijo samostojnega sestavljanja programov, svojem znanju. Ker ima tekmovanje različne kategorije, je je smiselno, da najprej rešijo naloge, kjer so vsi ukazi že podani, primerno za vse starostne stopnje ter za različna predznanja. vendar »razmetani« in jih morajo pravilno zložiti (Slika 47). Ker Mentor ima tukaj pomembno vlogo, da tekmovalca pravilno gre za programiranje z delčki, sintaktične napake niso možne. usmeri v ustrezno izbiro kategorije. Ker je bilo drugo poskusno Učenci pri teh nalogah pogosto zbrišejo že podane ukaze in se tekmovanje ravno v času šolanja na daljavo, je bilo vzpodbujanje programa lotijo »od začetka«. Še posebej se to pojavlja pri in usmerjanje učencev toliko težje. Pojavilo se je tudi nekaj učencih, ki se prej niso srečali s takim tipom nalog, zato v prvih osnovnih težav, ker učenci niso dobro sledili navodilom (termin urah te naloge zahtevajo malo več usmerjanja s strani učitelja. tekmovanja, prijavni podatki, dostop do nalog), kar pa nam je Podobno je pri nalogah tipa popravi napako. Učenec mora dalo dodaten zagon in nove ideje za načrtovanje pouka za ugotoviti, kaj je narobe (npr. lahko manjka ukaz, lahko je kakšno naslednje šolsko leto. število v zanki ali funkciji preveliko). Ker imamo delčke, se res Več o samem tekmovanju si lahko preberete v [3]. ukvarjamo samo z vsebinskimi napakami. Pri vsem tem je treba omeniti, da so učenci ob uri, ko smo 4.1 Primer poučevanja zanke uporabljali sistem Pišek, pogosto rekli, da igrajo igrico. V ilustracijo konkretne uporabe sistema pri pouku, si poglejmo, Opažamo, da jeziki, ki podpirajo programiranje z delčki, kako smo razmišljali pri pripravi na poučevanje koncepta zanke. pripomorejo k lažjemu razvijanju računalniškega mišljenja, Program je zaporedje ukazov. To učenci hitro usvojijo. Prav tako sistemi s povratnimi informacijami pa učitelju olajšajo delo. hitro spoznajo, da je za uspešen program pomemben vrstni red ukazov. Prve težave se pojavijo, ko jih želimo naučiti program optimizirati, torej da namesto štirih enakih ukazov uporabijo zanko »ponovi štirikrat«. Program bo seveda deloval pravilno v 567 obeh primerih, želimo pa si, da bi sistem sam preveril, ali zna Ko se učenci naučijo osnovne uporabe zanke ponavljaj, jo učenec uporabljati zanke. nadgradimo z »zanko v zanki«. Slika 48. Primer osnovne optimizacije Učenci sicer razumejo, da je učinek zgornjih dveh delov programa popolnoma enak. Kljub temu pa se večina, ko pišejo oz. sestavljajo program, ne spomni, da bi sami od sebe uporabili zanko. Pred Piškom smo delali v Scratchu in ker je program Slika 52. Primer naloge z ugnezdenimi zankami deloval ne glede na to, ali so uporabili zanko ali ne, jih veliko tega koncepta ni usvojilo. V sistemu Pišek jih lahko k temu Večina nalog je sestavljena na treh različnih stopnjah. "prisilimo" tako, da sestavimo nalogo, ki ima omejitev števila Različne stopnje preverjajo poznavanje istih programskih delčkov, ki jih lahko uporabijo pri sestavljanju programa. konceptov, razlika je največkrat v dolžini programa. Ko učenec reši stopnjo, se zvezdice obarvajo rumeno (Slika 53), kar omogoča učitelju, da hitro vidi, kako učenec napreduje (da ni kakšne naloge oz. stopnje preskočil). Slika 53. Oznake stopenj 4.2 Preverjanje pravilnosti programa po Slika 49. Primer naloge z omejitvijo števila delčkov korakih Učenec sicer lahko začne z zlaganjem več enakih delčkov, Sistem omogoča tudi, da učenci svoj program preverjajo po vendar bo kmalu ugotovil, da se mora naloge lotiti drugače (Slika korakih, vsak ukaz oz. delček posebej. Tako naj bi hitreje našli 50). Sistem tako omogoča, da je edina prava rešitev, ko učenec napako v svojem programu. Na naši šoli se je pokazalo, da je v uporabi zanko. splošnem za učence osnovne šole to precej težko in si s tem ne znajo pomagati. Pri iskanju napak po korakih potrebujejo veliko vodenja in usmerjanja učitelja. Je pa koristna možnost, da je pri izvajanju po korakih na mreži sproti pokazan učinek, v samem programu pa označen ukaz, ki se bo izvedel naslednji (glej označene dele na Slika 54). Slika 50. Primer reševanja brez uporabe zanke Ko učenec odda program s pravilno rešitvijo in z upoštevanimi omejitvami, dobi povratno informacijo z usmeritvijo za reševanje naslednjih nalog. Slika 54. Izvajanje po korakih Slika 51. Povratna informacija ob pravilni rešitvi 5 ZAKLJUČEK 568 Pri neobveznem izbirnem predmetu računalništvo, ki se izvaja v uporabljamo kot celoto in izkoristimo možnost samodejnega drugi triadi OŠ, se srečujemo z nemalo težavami. Že to, da preverjanja pravilnosti rešitev. imamo lahko skupino 28-tih učencev različne starosti in s popolnoma različnim predznanjem, saj so nekateri pri predmetu prvo leto, nekateri pa že tretje, zahteva od učitelja veliko LITERATURA IN VIRI inovativnosti pri načrtovanju pouka. Kako narediti predmet [1] Anželj, G., J. Brank, A. Brodnik, L. Fürst in M. Lokar. zanimiv in koristen in ne prezahteven, ko pa so si učenci tako 2018. Slikovno programiranje v1.00: E-učbenik za uvod v različni? In to predmet, ki je po eni strani izbirni, po drugi strani programiranje, Blockly. Univerza v Ljubljani. pa uči veščine, ki so nujno potrebne v vsakdanjem življenju. [2] Jerše, G., K. Koren Ošljak, M. Lokar. 2019. Poučevanje V takih situacijah nam je lahko IKT v veliko pomoč, saj nam programskih konceptov: Spletna zbirka nalog s samodejnim res omogoča nujno potrebno individualizacijo in diferenciacijo. preverjanjem. V Informacijska družba, Zbornik 22. S sistemom za avtomatsko preverjanje pravilnosti rešitve pa mednarodne multikonference – IS 2019. učitelju omogoča, da lažje prepozna učence s težavami in mu [3] M. Lokar. M. Mujkić. 2020. ACM Tekmovanja – Pišek: zagotovi čas, ki ga potrebuje za pomoč in usmerjanje. Tekmovanje v programiranju z delčki, V Informacijska Uporaba jezikov, ki omogočajo programiranje z delčki, družba, Zbornik 23. mednarodne multikonference – IS 2020 samemu programiranju seveda ni na neki čarobni način odvzelo [4] Parsons, D., Haden, P.: Parson’s programming puzzles: a zahtevnosti. Vendar opažamo, da je učencem blizu in jih fun and effective learn-ing tool for first programming spominja na igranje igric. In učenje skozi igro je tisto, ki je pri courses. V Proceedings of the 8th otrocih najpomembnejše in gradi osnove za druge, višje oblike AustralasianConference on Computing Education-Volume učenja in razvoj mišljenja. 52. str. 157–163 (2006) Zato so orodja, kot je Sistem Pišek, pomembna. Lahko jih [5] Ericson, B. J., Margulieux, L. E., & Rick, J. 2017. Solving uporabljamo zgolj kot vir idej za naloge in še vedno uporabljamo Parsons problems versus fixing and writing code. V svoj izbrani programski jezik (na primer Scratch) in/ali svoje Proceedings of the 17th Koli Calling International okolje (na primer MakeCode). Lahko pa Sistem Pišek Conference on Computing Education Research (pp. 20-29). ACM. 569 Uporaba IKT pri urah športa kot pripomoček za izboljšanje izvajanja osnovnih elementov pri skokih na mali prožni ponjavi The use of ICT during physical education lessons to improve the performance of basic technical elements on trampoline Janez Malovič Osnovna šola n. h. Maksa Pečarja Črnuška cesta 9 1000 Ljubljana, Slovenija janez.malovic@guest.arnes.si POVZETEK ABSTRACT Prispevek opisuje rabo IKT pri pouku športa. S pomočjo The article describes the use of ICT during sport lessons. elektronske/interaktivne table (v nadaljevanju table), kamere, Students practised on a trampoline and at the same time an interaktivnega projektorja in računalnika so učenci izvajali vaje electronic/interactive board, a camera, an interactive projector na mali prožni ponjavi. Po vsakem skoku so preko programa and a computer were used. After every jump, the students looked Sportswatch delay pogledali svojo izvedbo in sami opazovali at their jump with the help of the Sportswatch delay program. svoje napake. Z vsakim skokom so te napake poskušali odpraviti. They could notice their mistakes and try to correct them in their V prispevku je opis izvedbe ure športa od učnega sklopa next jump. The article describes a PE lesson – giving new podajanja novih informacij, preko utrjevanja, do preverjanja in information, practice, checking and marking. With the help of an na koncu tudi ocenjevanja. S pomočjo interaktivnega projektorja, interactive projector, a board and filming of the lesson, we table in snemanja pouka, izvajamo vizualni in kinestetični stil support the visual and kinaesthetic styles of learning. Students učenja. Pri takem načinu dela učenci sami vrednotijo svoje delo. also evaluate their own work. The role of the teacher is to Vloga učitelja je demonstracija in usmerjanje učencev na bolj demonstrate and guide students to the more important parts of an pomembne dele posameznega elementa. Učenci pri takem načinu individual element. Students get to do more quality repetitions dela opravijo več kvalitetnih ponovitev, kar dvigne kvaliteto which subsequently increases the quality of motoric learning. motoričnega učenja. Seveda je pomemben tudi faktor varnosti. The safety factor of course is also very important. We checked Poskusno smo preverjali tudi znanje in na koncu so se učenci knowledge and at the end of the lessons and students graded each med seboj ocenjevali. V pomoč so jim bile v naprej pripravljene others work with the help of pre-prepared charts. After the preglednice. Po zaključku sklopa gimnastike, ki je opisan v gymnastics lesson, which is described in the article, I have also prispevku, sem poskusno opravil tudi vaje med košarko in tried the same approach with basketball and volleyball. Students odbojko. Učenci na tak način vidijo svoj napredek, kar jih can see their progress which motivates them for future work and motivira za nadaljnje delo in jim dviguje samozavest pri raises their confidence when performing an element. On the izvajanju elementov. Na tabli lahko označimo cilje tudi za manj board we can also mark the goals for students with lower abilities sposobne učence in jim s tem prilagodimo delo. Po končanih urah and thus adjust work for them. After the lessons a conclusion was smo skozi pogovor prišli do zaključka, da so učencem take ure reached through conversation that students like such lessons very zelo zanimive in jih imajo radi. much and that they find them very interesting. KLJUČNE BESEDE KEYWORDS IKT, interaktivna/elektronska tabla, računalnik, interaktivni ICT, interactive/electronic board, computer, interactive projektor, kamera, Sportswatch delay, pouk športa, gimnastika, projector, camera, Sportwatch delay, PE lessons, gymnastics, skoki na mali prožni ponjavi jumps of a trampoline 1 UVOD Uporaba IKT v športu sega že zelo daleč nazaj, seveda v drugačni obliki. Začela se je kot uporaba videokamer pri procesu Permission to make digital or hard copies of part or all of this work for personal or treniranja. Trener je posnel trening in po treningu je bila video classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full analiza. Trener je izpostavil napake in dobro izvedene elemente. citation on the first page. Copyrights for third-party components of this work must Na naslednjem treningu so športniki poskušali te napake be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia odpraviti. Tak način dela smo že pred 25 leti uporabljali v zimski © 2020 Copyright held by the owner/author(s). šoli v naravi. Glede na razvoj tehnologije je področje IKT zelo 570 napredovalo in podoben, seveda naprednejši način dela se je • skok raznožno, prenesel v učilnice. Sedaj imajo nekatere športne dvorane že vse • skok skrčno, pripravljeno za video analize treningov in tekmovanj. Tudi pri • skok prednožno, urah športa se to vse več uporablja [1]. Uporaba je odvisna od • skok z obratom za 180o in za 360o. računalniških zmožnosti posamezne šole in digitalne pismenosti športnih pedagogov. Glede na to, da je IKT vse bolj prisoten v Vsak skok sem na začetku demonstriral, oz, za to uporabil vsakdanjem življenju, se zdi smiselno tudi vključevanje le-tega učenca, ki to zna. Kamera je snemala skoke s 5 sekundnim v poučevanje športa, Prav tako učenje s pomočjo sodobne zamikom. Vsak učenec se je po skoku pogledal, jaz pa sem mu tehnologije učence motivira, popestri pouk in usmerja delo v povedal bistvene napake. Napake, na katere sem jih v prvi fazi hitrejše in kakovostnejše doseganje ciljev. Seveda ga ne smemo ure opozarjal so: enačiti z neposrednim odnosom učitelj-učenec. Kljub vsemu je še vedno prva dobra ustna povratna informacija, ki jo učitelj da • naskok in odriv z MPP, učencu. Uporaba IKT je kot dodaten učni pripomoček, ki dvigne • višina skoka, motorično učenje na višji nivo [2]. • položaj telesa v zraku, • doskok. 2 INTERAKTIVNI SKLOP Ko je vsak opravil po pet ponovitev vsakega skoka, smo vse Komplet učnih pripomočkov, ki jih uporabljamo med poukom skoke posneli in jih skupaj pogledali. Opozoril sem jih na zajema: bistvene napake in pohvalil dobre faze skoka. Za ta del ure smo si vzeli nekaj časa, saj smo posnetek tudi ustavili in analizirali • Interaktivna tabla skok. Po tem so učenci še enkrat izvedli vaje. Uro smo zaključili • Projektor z razteznimi vajami in pogovorom o uporabi kamere. • Spletna kamera Na drugi učni uri smo izvedli utrjevanje naučenih elementov. • Prenosni računalnik Še vedno je na začetku sledila demonstracija posameznih skokov. • Računalniški program Sportswatch delay [3] Potem sem jim na tablo narisal položaj telesa pri posameznem skoku. Pri skoku so učenci poskušali svoj položaj telesa čimbolj Pri pouku lahko uporabljamo seveda tudi ostale oblike približati narisani figuri (slika 3). Figura je bila narisana z zeleno računalniške tehnologije. Dovolj je že kamera in TV. Za barvo. Manjša odstopanja sem narisal z rumeno barvo, večja z kvalitetno delo je dobro, če so omenjeni elementi na voljo v rdečo. Osredotočili smo se predvsem na bistvene napake pri telovadnici in da s postavljanjem ne izgubljamo preveč časa. Naš skokih, to so npr: pripomoček je postavljen na vozičku in s postavljanjem in priključevanjem ne izgubljamo časa. Sklop, ki ga uporabljamo • izteg nog in rok, ravno telo (ne uleknjeno), pri našem pouku je Hitachijev interaktivni sklop. • dvig kolen (pri skoku skrčno), • izteg stopal (špičke), • dvig iztegnjenih nog pri skoku prednožno, • ravno telo, roke in noge pri obratih, • doskok v čep z iztegnjenimi rokami. OCENA/SKOK IZTEGNJENO SKRČNO RAZNOŽNO PREDNOŽNO OBRAT ZELENO - 2 RUMENO - 1 RDEČE - 0 Slika 2: Tabela točkovanja Učenci so po skoku pogledali ali so v zelenem, rumenem ali v rdečem območju. Učence je to zelo motiviralo, saj so se čimbolj želeli približati zeleni barvi. Ta del ure lahko traja dalj časa, učenci so aktivni in izvedejo veliko kvalitetnih ponovitev. Bistvo Slika 1: IKT sklop z interaktivnim projektorjem je, da ne ponavljajo napak. Pri naslednji uri sem učence razdelil v pare. Vsak par je dobil 2.1 Izpeljava učne ure športa z uporabo IKT list s tabelo, na kateri je so bili napisani skoki in v katerem polju Tema učne ure je bila gimnastika – osnovni skoki na mali prožni je izvedel posamezni skok (zeleno, rumeno ali rdeče). Vsak par ponjavi (v nadaljevanju MPP). Postavil sem dve MPP, da so je nalogo izvajal tako, da je en učenec skočil, drugi je zapisal lahko opravili več ponovitev. Na eni je bila postavljena kamera križec v ustrezno barvno polje. Po vsakem skoku sta zamenjala in projektor. Cilj ure je bil, da učenci izvedejo osnovne skoke, se vlogi. Nekateri so to izvajali tako, da je eden izvedel vse pri tem opazujejo in poskušajo izvedbo izboljšati. Osnovni skoki, omenjene skoke, potem sta naredila menjavo. ki smo jih izvajali so naslednji: Ko so končali, je vsak učenec seštel svoje točke. Skok v zeleno polje prinese 2 točki, v rumeno 1 točko in v rdeče polje 0 točk. Ravno tako ne dobi točk, če skoka ne izvede ali izvede • skok iztegnjeno, 571 napačen skok (raznožno namesto skrčno). Tako je maksimalno 2.3 Možnosti za delo v prihodnje število točk 10. Učenci so pri tem načinu točkovanja zelo Po uspešni izpeljavi učnega sklopa skokov na mali prožni skoncentrirani pri vsakem posameznem skoku. Tako se tudi ponjavi, razmišljam o uporabi tudi pri drugih učnih vsebinah. zmanjša verjetnost poškodb, saj ne skačejo »kar tako«. Seveda ne pri vseh in ne vsako uro, vsekakor pa je vizualna 2.1.1 Preverjanje in ocenjevanje povratna informacija pomembna pri kvalitetnejšem delu in Po treh izvedenih urah sem učencem napovedal preverjanje in napredku učencev. ocenjevanje omenjenih skokov. Večina učencev je to z veseljem Možnosti so tudi v različni obliki ure, kjer si del učencev pričakovala, saj so v treh urah izvedli že veliko skokov in so izbere, izvede in posname poljubno vajo, označijo napake, drug vedeli kaj zmorejo. Učenci so se zopet razdelili v pare in dobili del učencev poskuša to ponoviti. liste s tabelami skokov. Enako kot na prejšnjih urah so izvedli Uspešna je bila tudi uporaba pri individualnem delu s slabšimi skoke in sešteli svoje točke. učenci. Na ta način lahko večina učencev dela nekaj drugega, tisti, Ob koncu tega dela ure sem zbral tabele in skupaj z učenci ki določene naloge niso uspešno izvedli, sami vadijo nalogo in smo pregledali točke. se opazujejo. Kriterij, ki smo ga uporabili: 2.3.1 Uporaba interaktivnega sklopa pri drugih učnih Točke Ocena vsebinah 9-10 5 Moje delo z omenjenim interaktivnim sklopom je bilo v začetku 7-8 4 usmerjeno na skoke na mali prožni ponjavi. Uporabil sem ga tudi 5-6 3 pri drugih učnih vsebinah. Nekaj primerov uporabe: 3-4 2 0-3 1 • Košarka, met na koš, opazujemo višino loka žoge in pravilno gibanje roke. Preden sem zapisal ocene, je imel vsak možnost, da ponovno • Odbojka, položaj rok in telesa pri spodnjem odboju. skoči skok, pri katerem je dobil najmanj točk, oz. se mu je skok • Atletika, položaj telesa pri nizkem štartu. ponesrečil. Opazil sem, da se učenci med seboj zelo realno ocenjujejo. Zgodi se, da sem pri katerem učencu podvomil o njegovih točkah, 3 ZAKLJUČEK saj sem jih pri skokih opazoval in sem vedel kako skočijo. Ti Pri uvajanju takega načina dela je potrebno učencem razložiti učenci so opravili še dodaten skok, da sem preveril njihovo zakaj se to uporablja, kaj so prednosti in kako naj to uporabijo izvedbo. Težav pri tem delu ni bilo. pri napredovanju. Izkazalo se je, da skoraj vsi učenci sprejmejo z zanimanjem in željo po napredku. Seveda pri tem učitelj ne sme 2.2 Opažanja in pozitivni učinki biti le kot opazovalec ampak se mora aktivno vključiti v delo in Učenci so se odlično odzvali na tak način dela. Predvsem jim učence še dodatno motivirati. Pomembno je tudi, da s veliko pomeni to, da opazijo lasten napredek. Opazil sem postavitvijo takega interaktivnega sklopa ne izgubljamo časa zavzetost pri delu tudi pri učencih, ki sicer ne vidijo motivacije v med uro. Če je možnost, naj bo že postavljen v dvorani. Lahko lastnem napredku. Težav pri posameznih nalogah ni bilo. Z rečem, da tak način dela uspešno in dinamično popestri ure veseljem so skakali in pisanje točk v tabelo jih je še dodatno športa. motiviralo. Ob koncu ure sme vsak učenec izvesti skok po lastni Nekaj opažanj: izbiri. Pravilo je le, da skok ni prevrat naprej ali preval letno. Vsak skok si ogledamo, kar prinese veliko dobre volje. • Učenci so pri izvajanju skokov napredovali bolj kot pri Opazna je razlika pri takem načinu dela, kot pa pri klasičnih običajnem načinu dela. skokih, kjer učitelj ustano popravlja vsakega učenca posebej. • Skoke izvajajo bolj zavzeto in z večjo koncentracijo. Tudi učitelj ne vidi vseh napak, saj je skok izveden v zelo • Ker se med seboj opazujejo, se bolj potrudijo, da skok kratkem času in lahko opozoriš le na bistvene napake. Učencem izvedejo čim bolje. pa ustne informacije niso tako v pomoč kot če se vidijo. Ravno • Nekateri med seboj tekmujejo, kdo bo večkrat v tako pri takem delu opravijo večje število ponovitev. »zelenem območju«. Za popestritev ure lahko naredimo tudi tekmovanje med • Otroci si med seboj izmenjujejo informacije, ki jih dvema ali tremi skupinami, med posamezniki ali pari. včasih lažje razumejo, kot če jim jih preda učitelj. Učenci so tak način dela zelo dobro sprejeli. Učenci se s takim delom vključeni v vrednotenje lastnega znanja, kar jih še dodatno VIRI IN LITERATURA motivira. Pri slabših ocenah se ne pojavi slaba volja, saj je ocenjevanje [1] Štuhec Tivadar D. (2015) Uporaba kamere in programa za zelo pregledno. Tudi učenci, ki zberejo nižje število točk, vidijo, zamik predvajanja pri pouku športne vzgoje. V: Posodobitev pouka v osnovnošolski praksi (str. 92-100) da je temu tako. Na splošno se zelo redko pojavi nižja ocena od Dostopno na naslovu: https://www.zrss.si/pdf/pos-pouka- 3. os-sport.pdf Kljub vsemu ni bil glavni namen uporabe IKT ocenjevanje, temveč kvalitetnejše delo, motivacija učencev in napredek v [2] Univerza v Mariboru, Pedagoška fakulteta, didaktika športa 2, motorično učenje (2018). Dostopno na znanju. 572 naslovu;https://studentski.net/gradivo/umb_pef_rp1_ds2_s [3] Sportswatch delay: Natrisoft – Hoofdstraat 30 – 9443 TK no_motoricno_ucenje_01 Schoonloo . Nederland. Dostopno na naslovu: https://www.natrisoft.nl/sportswatch/en/sportswatchdelay. html 573 Uporaba aplikacije mCOBISS v 8. razredu Using the mCOBISS application in 8th grade Lidija Mazgan Osnovna šola Dušana Flisa Hoče Šolska ulica 10 2311 Hoče, Slovenija lidija.mazgan@os-hoce.si POVZETEK modern information and communication technology (ICT) and thus show students the possibilities of using new electronic Sodobni čas in napredna tehnologija zahtevata od knjižničarja devices for educational purposes. In the lesson presented we used sodobni pristop pri delu z učenci. Kar pomeni, da tudi knjižničar mobile phones with the 8th grade students of primary school and uporablja sodobno informacijsko in komunikacijsko tehnologijo so they got to know the mCOBISS application (mobile Co- (IKT) in s tem učencem pokaže možnosti uporabe novih operative online bibliographic system and services; is a mobile elektronskih naprav v izobraževalne namene. V učni uri, ki sem application that provides access to information about the material jo izvedla v 8. razredu osnovne šole, sem z učenci uporabila in the library). Students brought phones (android or iPhone) with mobilni telefon, s pomočjo katerega smo spoznali aplikacijo them and learned about the possibilities of using this application. mCOBISS (mobilni Kooperativni online bibliografski sistem in I had previously prepared all the relevant material to keep the servisi; je mobilna aplikacija, ki omogoča dostop do informacij lesson running smoothly. First it was necessary to arrange the o gradivu v knjižnici). Učenci so s seboj prinesli telefone internal wi-fi and password, in the OSDFHO catalog (an (android ali iPhone) in vodeno spoznavali možnosti uporabe te acronym for the internal database of the OŠ Dušana Flisa Hoče) aplikacije. Predhodno sem pripravila vse ustrezne elemente, da database the passwords of all students, with whom I led this je učna ura potekala tekoče. Najprej je bilo potrebno urediti lesson, were organized. However, each student needed to have a interni wi-fi in geslo, nato v kataložni bazi OSDFHO (akronim membership card with the number of the school library user. interne baze Osnovne šole Dušana Flisa Hoče) urediti gesla vsem Only after all these preparations it was possible to register in the učencem, s katerimi sem to uro izvedla. Predpogoj za vse pa je application. Students quickly and easily accessed the application: bila članska izkaznica s številko uporabnika šolske knjižnice. installed it and registered. The use of the application itself was Šele po vseh teh pripravah je bila mogoča registracija v aplikaciji. also interesting to them and they skillfully browsed through it Učenci so hitro in brez večjih težav dostopili do aplikacije: jo and learned about the possibilities it offers. The purpose of the namestili in se registrirali. Tudi sama uporaba aplikacije jim je lesson presented was for the student to independently find the bila zanimiva in so spretno brskali po njej ter spoznavali book first in the application, then access the bookshelves and find možnosti, ki jim jih ponuja. Namen uporabe je bil, da učenec the appropriate book. To achieve this goal, students needed samostojno poišče knjigo najprej v aplikaciji, nato pa pristopi do knowledge about where literature and educational literature in knjižnih polic in poišče ustrezno knjigo. Pri tem mora poznati the library could be found. I also acquainted them with the tudi način postavitve leposlovja in poučne literature. Seznanila possibilities in the application that they do not have in the school sem jih tudi z možnostmi v aplikaciji, ki jih sicer v šolski library: how to extend the library books, with the settings of push knjižnici nimajo: s podaljševanjem gradiva, z nastavitvami notifications and with the possibility of membership in various potisnih informacij ter z možnostjo članstva v različnih libraries. knjižnicah. KLJUČNE BESEDE KEYWORDS Library information knowledge, material search, COBISS +, Knjižnično informacijska znanja, iskanje gradiva, COBISS+, mobile phones (android, iPhone), mCOBISS application mobilni telefoni (android, iPhone), aplikacija mCOBISS ABSTRACT 1 UVOD Modern times and advanced technology require the librarian to take a modern approach to working with students. Librarians use Pouk v osnovni šoli je potrebno prilagoditi družbenim razmeram, spremembam vzgoje in posledično spremenjeni populaciji učencev, napredku sodobne tehnologije in drugim sferam sodobnega življenja. Strokovni delavci v vzgoji in izobraževanju Permission to make digital or hard copies of part or all of this work for personal or se zavedamo lastnega permanentnega izobraževanja, da lahko classroom use is granted without fee provided that copies are not made or distributed sledimo novim generacijam učencev, ki so »zahtevnejši«, bolj for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must obdani z informacijami, uporabljajo sodobno tehnologijo že od be honored. For all other uses, contact the owner/author(s). malih nog in preživijo del svojega življenja tudi v virtualnem Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia svetu. © 2020 Copyright held by the owner/author(s). 574 Da bi se v njem lažje znašli, da bi znali presojati informacije uporabljajo zgolj za iskanje informacij ali samo za učenje. Večji in uporabljati tehnologijo tudi v izobraževalne namene, del uporabe interneta je namenjen komunikaciji med prijatelji, potrebujejo učitelje, knjižničarje in druge strokovne delavce na znanci in sošolci, nalaganju glasbe s spleta in igranju iger. Splet šoli, da jim pri tem pomagamo. Tako sem v eni izmed uporabljajo bolj ustvarjalno in bolje kot njihovi starši in učitelji, medpredmetnih učnih ur v okviru Knjižnično informacijskih vendar le v določene namene. znanj in slovenščine izvedla učno uro, v kateri so učenci spoznali V eni od raziskav o védenju mladih ljudi pri iskanju in uporabljali mobilno aplikacijo mCOBISS. informacij se je pokazalo, da to védenje pri mlajših ni večje kot Aplikacija je zelo priročna in uporabna, saj nudi hiter dostop pri odraslih ljudeh ter da so tako mladi kot starejši uporabniki do knjižničnega gradiva, kar pa je za današnji čas zelo postali nagnjeni k površnosti. Naslednja raziskava pravi, da pomembno. V sedanjem in nadaljnjem izobraževanju bodo mladi težko ločijo dobre vire od slabših. Po navadi to počno zgolj učenci potrebovali še mnogo knjižničnega gradiva za usvajanje površno, niso pa pripravljeni podati natančne ocene. Torej znanje znanj z različnih področij. Da bi čim hitreje prišli do informacij, o iskanju informacij se pri mladih ni izboljšalo, kar je pogojeno si lahko pomagajo tudi s to aplikacijo. Namestitev, dostop in s preprostostjo uporabe digitalnih sistemov. In ker mladi ne vedo, uporaba so enostavni. Učencem je dostop do virtualnih vsebin kako so informacije med seboj povezane (povezanost z logičnimi blizu, saj jih nenehno uporabljajo. operaterji) in ne ločijo med pomembnim in nepomembnim, pri iskanju po spletu niso preveč uspešni. Za iskanje na internetu je zato potrebna solidna osnovna izobrazba in predznanje na 2 IZOBRAŽEVALNE USTANOVE V področju, na katero je usmerjeno iskanje, sicer tudi Google ne bo DIGITALNI DOBI v pomoč. Tisti, ki pa nasprotno že veliko vedo, si lahko z Veliko je govora o tem, da so izobraževalne ustanove zastarele Googlom le še pomagajo do zadnje informacije, ki je še potrebna. in da je potrebno vnesti korenite spremembe, da ne bi izgubile Na osnovi dobrega predznanja lahko tako izmed številnih pomen in veljavo. Don Tapscott in Anthony Williams v svoji zadetkov na iskalniku izločijo take, ki so pomembni in vodijo k kratki razpravi Univerzo 21. stoletja je treba na novo iznajti: uspehu. Skrajni čas je že. [6] poudarjata, da splet nezadržno postaja Na koncu še spoznanje o tem, da nam zavest, da lahko prevladujoča infrastruktura znanja. Pojavi se izraz digitalni vsakršno informacijo hipoma najdemo na spletu, preprečuje, da domorodci, ki poimenuje generacije ljudi, rojenih po letu 1980 bi shranjevali podatke v možgane. Kar je škodljivo, ker se tako in ki so zrasli skupaj z računalnikom in internetom kot strokovnega védenja naučimo bistveno manj kot nekdo, ki ni samoumevnima sestavinama okolja. Digitalni domorodec ima tako naravnan pri iskanju informacij. svojo domovino v digitalnem svetu sodobne informacijske Rowlands [6] pravi, da pri generaciji digitalnih domorodcev tehnike. ne gre za izvedence na področju iskanja informacij in da ti nimajo Za nove generacije to pomeni povsod dostopne in na internetu boljših (tudi ne slabših) sposobnosti, kako ravnati z sloneče tehnologije in aktivno ukvarjanje s temi novimi informacijami, ampak da gre po mnenju avtorjev študije za tehnologijami. Tipično zanj je, da je večino časa na spletu, z generacijo »cut and paste«. drugimi komunicira po e-pošti, z SMS-i in na socialnih omrežjih. Pogosto posluša glasbo poleg drugih opravil, zvečer igra video igrice ali gleda televizijo, zjutraj pa mu namesto budilke zvoni 4 SPLET V IZOBRAŽEVALNE NAMENE mobilni telefon. Spitzer [6] pravi, da glede na upoštevanje Izhajajoči iz prejšnjih raziskav, lahko ugotovimo, da mladi delovanja možganov zagotovo sledi, da bo to pustilo posledice vseeno še potrebujejo voden izobraževalni proces, v katerem na življenju digitalnega domorodca. pridobijo osnove za nadaljnjo uporabo spletnih vsebin. Vendar Anderson in Rainie sta optimistična in govorita o pozitivnih pa mora ta proces vključevati sodobne učne oblike in metode, s posledicah: možgani bodo leta 2020 večopravilno vodenih katerimi učencem približamo izobraževalne vsebine. najstnikov in mlajših odraslih »ožičeni« povsem drugače kakor Ena izmed sodobnih učnih oblik je ravno uporaba novih možgani ljudi starejših od 35 let. Ti naj bi se več naučili in zato naprednejših tehnologij in spletnih vsebin oz. storitev, ki bili bolj sposobni najti odgovore na globoka vprašanja, ker so omogočajo hitrejši dostop do informacij. V našem primeru gre učinkovitejši pri iskanju informacij na spletu. Torej spremembe za uporabo računalnika in lastnih telefonov ter knjižničnega v učnem vedenju in mišljenju mladih po njegovo vodijo do kataloga COBISS z različnimi storitvami, ki se iz leta v leto pozitivnih učinkov in če bi omejili mobilnost mladih, bi izpopolnjujejo in nadgrajujejo. zmanjšali njihovo sposobnost razvijanja socialnih spretnosti. Za osnovnošolce, ki kmalu vstopajo v srednješolsko Seveda pa obstajajo mnenja in dokazi tudi v nasprotno smer: o izobraževanje, so primerne predvsem naslednje storitve: propadu osnovnega mišljenja, resničnega zanimanja in socialnih COBISS+ - omogoča online dostop do naslednjih baz spretnosti v stvarnih osebnih odnosih ter o odvisnosti od tehnike. podatkov: [6] • vzajemna bibliografsko-kataložna baza podatkov COBIB.SI – skupni katalog slovenskih knjižnic, ki sodelujejo v sistemu COBISS.SI, 3 MLADI IN SPLET • lokalne baze podatkov – katalogi knjižnic v sistemu Mlajši predstavniki digitalnih domorodcev (rojeni po letu 1993) COBISS.SI. ne poznajo časa brez računalnikov in spleta. So »generacija Moj profil COBISS/Moja knjižnica – je vezan na posamezno Googla« in imajo posebne sposobnosti in spretnosti pri rabi knjižnico, in uporabniški profil, ki omogoča številne nastavitve informacijske in komunikacijske tehnike (IKT). Spleta ne uporabniškega vmesnika ter druge prilagoditve. 575 mCOBISS – je različica COBISS+, ki je prilagojena ki imajo androide dostopajo preko google trgovina play. mobilnim napravam. Aplikacija izkorišča prednosti sodobnih Registrirajo se tako, da vpišejo akronim knjižnice OSDFHO, telefonov, ki delujejo na sistemih Android (npr. Samsung Galaxy, številko članske izkaznice in geslo (Slika 1). V ta namen Sony Xperia, HTC One), iOS (iPhone, iPad in iPod Touch) in učencem razdelim članske izkaznice, ki so sicer shranjene v Windows. knjižnici in jih ne odnašajo domov, ker bi jih sicer večina V učni uri, ki je predstavljena v nadaljevanju, je bila izgubila. Predhodno sem jim v računalniku dodelila gesla. Ta so uporabljena predvsem storitev mCOBISS, seveda pa se ni dalo najmanj 8 mestna, in sicer vsebujejo številke ter velike in male izogniti storitvi COBISS+, ki je osnova za način iskanja črke. Gesla sem jim zapisala na samolepilni listič in prilepila na informacijskih virov. Storitev Moja knjižnica je bila učencem izkaznice. Ob koncu ure so mi izkaznice z gesli vrnili. Učiteljica predstavljena zgolj informativno in se bodo z njo srečali pomaga pri nastavitvah. kasneje. 5 UPORABA APLIKACIJE MCOBISS V 8. RAZREDU OŠ Učna ura je bila izvedena v 8. razredu osnovne šole. Namen te učne ure je bil, da učenec: spozna globalno informacijsko omrežje, pojmuje knjižnice kot del globalne informacijske mreže, spozna različne dostope do katalogov, spozna vzajemni katalog COBISS/OPAC, uporablja signaturo za iskanje knjižničnega gradiva v prostem pristopu, pozna osnovne bibliografske podatke, pomembne za pridobitev vira, spozna organizacijo informacij v katalogu in ga uporablja za osnovno informiranje o izbiri in dostopnosti virov, uporablja storitve na informacijskem omrežju (COBISS+), uporablja storitev mCOBISS. Učencem najprej na kratko predstavim COBISS. Razložim, da je to vzajemna baza slovenskih knjižnic, da je vanj vključenih večina knjižnic po Sloveniji in da lahko v njem pridobijo podatke o knjižničnem gradivu vseh knjižnic polnopravnih članic COBISS-a. Povem, da je tudi naša knjižnica del tega sistema. Na i-tabli predstavim spletno stran COBISS – storitve COBISS+, Moj COBISS, Moja knjižnica. Večina učencev že pozna te storitve, nekateri so zanje slišali, drugi jih že uporabljajo. Slika 1: Uporaba aplikacije mCOBISS na lastnih telefonih S pomočjo računalnika in projekcije na i-tabli hitro preletim osnovno in izbirno iskanje po COBISS+, ki je osnova za naše Ko učenci dostopijo do virtualne knjižnice, se jim najprej nadaljnje delo. Nato pokažem še, kako izgleda okolje Moje odpre seznam izposojenega gradiva. Ta seznam je zelo dolg, ker knjižnice in katere možnosti ponuja. Žal jim nekatere storitve imajo seveda izposojene tudi učbenike. Učenci so začudeni, preko šolske knjižnice niso omogočene, če pa so člani še kakšne presenečeni, opažajo, da imajo v zgornjem delu ekrana vsi sliko druge knjižnice npr. Mariborske knjižnice, pa bodo to lahko fanta, čeprav so prisotna tudi dekleta. Na vse načine želijo uporabili. Gre za storitve kot so podaljšanje in rezerviranje spremeniti sliko. gradiva, aktivacija obveščanj o poteku roka izposoje, o prispelem Vodeno brskajo po aplikaciji in spoznavajo možnosti rezerviranem gradivu itd. uporabe: Osrednja tema te učne ure pa je namestitev aplikacije 1. Članstvo – Najprej si pogledajo članstvo. Povem, da mCOBISS in njena uporaba. Učenci so zato s seboj prinesli je lahko za druge knjižnice, razen šolske zelo uporabna mobilne telefone. Sicer je uporaba na šoli prepovedana, vendar storitev, saj ne potrebujejo s seboj izkaznice, ker imajo jih občasno uporabimo v učne namene. na telefonu kodo članske izkaznice. Tudi nastavitve Pripravila sem učni list, na katerem so zbrane informacije o potisnih sporočil so zelo uporabne, saj nas spomnijo na tem, kaj je mCOBISS, kaj omogoča in kako izgleda virtualno pravočasno vračanje izposojenega gradiva in prevzem okolje (Priloga 1). rezerviranega gradiva, na potek članstva itd. Prikažejo Razdelim učni list, kjer si učenci pogledajo, kaj vse jim se na ikoni v spodnjem delu ekrana na zvoncu. 2. Zgodovina – Ker rezervacije niso možne v šolski omogoča ta storitev in kako izgleda virtualno okolje. knjižnici, to rubriko preskočimo in gremo na Nato najprej uredijo dostop do interneta – poiščejo ustrezni zgodovino, kjer si pogledajo, kaj so brali do sedaj. wi-fi in vpišejo geslo. Predhodno sem pripravila interni brezžični Lahko tudi iščejo po zgodovini in omejijo datum router, ki ga na šoli uporabljamo za učne namene. Sicer imamo izposoje. vse učilnice in knjižnico povezane na Eduroam. Vendar če bi 3. Iskanje gradiva - Nato pogledamo v zgornji del učencem zaupali geslo, bi učenci skrivoma uporabljali telefone ekrana in se osredotočimo na iskanje gradiva, kar bo in internet ter bi preveč obremenili omrežje. naša osrednja naloga v tej učni uri. Razložim, da s tem Po mojih navodili si namestijo mobilno aplikacijo. Učenci z splošnim brskalnikom iščemo gradivo po celotni iPhoni dostopajo do aplikacije preko App Store, medtem ko tisti, COBIB bazi, zato bomo raje uporabili puščico v desno 576 in prešli na podrobno iskanje. Iščemo po naši knjižnici Z njim sem ugotavljala, kako so bili učenci zadovoljni z OSDFHO, v oddelku Knjižnica, ker imamo še oddelek izvedbo učne ure, ali je aplikacija zanje uporabna ali ne, kar so podružnična šola in dva oddelka v vrtcih. Nato morali tudi utemeljiti, in kaj bi lahko bilo drugače. poiščemo knjigo, ki jo bodo imeli za naslednje domače Rezultati so bili nekako pričakovani, vendar v določenih branje. Iščemo po naslovu in avtorju, omejimo vrsto segmentih presenetljivi. Anketo je izpolnilo 61 učencev. Od tega gradiva na knjige ter jezik na slovenski (Grafenauer, Skrivnosti, knjige, slovenski). Dobimo več zadetkov. jih je bilo 60% zelo zadovoljnih z učno uro, 35% zadovoljnih in Učenci povedo, kaj pomenijo ti zadetki – število enot 5% nezadovoljnih. Največ jih je odgovorilo, da je aplikacija ali različne izdaje. Nato odpremo enega od zadetkov. srednje uporabna, in sicer 64%, 30% jih meni, da je zelo Razložijo bibliografske podatke, ki jih vidijo, nato uporabna in le 6, da je neuporabna. Najbolj pa me je presenetil povedo koliko enot imamo te izdaje, koliko je prostih, podatek, da aplikacije 70% učencev po tej učni uri ni več koliko izposojenih. Nazadnje si pogledamo oznako uporabljalo. Tisti, ki so jo še uporabljali, so jo največ uporabili postavitve ali signature (Knjižnica otroci 82-1 za pregled izposojenega gradiva ter za iskanje knjig, veliko manj GRAFENAUER N. Skrivnosti IN:000000213). za ostale navedene možnosti. Pojasnim, da je knjižnično gradivo ločeno za učence in Glede na rezultate bi bilo smiselno, da bi se učno uro izvedlo učitelje, zato je na prvem mestu lahko Knjižnica otroci v prihodnje v 9. razredu, ob koncu šolskega leta, da bi znanje o – za učence ali Knjižnica strokovna – za učitelje in druge strokovne delavce. Postavitev 82-1 pomeni tej aplikaciji dobili časovno čim bližje srednješolskemu poezija, kar si pogledamo tudi na oznaki na knjižnih izobraževanju, saj bo verjetneje v srednješolskih letih in kasneje policah. Nato sledi priimek avtorja, ker leposlovje v študijskih letih aplikacija pogosteje uporabljena. iščemo po začetni črki avtorjevega priimka, ter naslov in inventarna številka. Učenci sedaj samostojno poiščejo vsak svoje leposlovno književno delo, najprej 7 SKLEP s pomočjo aplikacije, nato prosto pristopijo k knjižnim Z učno uro so učenci pridobili veščine uporabe mobilne policam in po pravilih s pomočjo kazalke poiščejo aplikacije mCOBISS. Spoznali so različne možnosti, ki jih knjigo ter označijo mesto na polici. Knjigo prinesejo k mizi in primerjajo signaturo na zaslonu in na nalepki. ponuja aplikacija, kot so pregled izposojenega gradiva, 4. Deli - Nato odprejo ikono tri modre pike povezane z zgodovino izposojenih enot, možnost rezervacije v drugih dvema črtama in pomeni deli. Razložim, da si vrstniki knjižnicah, iskanje virov v knjižničnem katalogu COBISS, pogosto med seboj izmenjajo informacije o zanimivih kreiranje Moje police z lastnim izborom knjig ter deljenje knjigah. Eden izmed načinov je tudi preko te storitve. zanimivih naslovov knjig s prijatelji. Vse te možnosti so Dobijo nalogo, da to knjigo, ki jo imajo pred seboj z praktično preizkusili z uporabo lastnih telefonov, številko nekom v skupini podelijo preko katerekoli storitve izkaznice in dodeljenim geslom. Dobili so tudi geslo za interni (SMS, Facebook, Tweet, Viber idr.) Pogledajo, kako wi-fi, ki je posebej namenjen izobraževalnemu procesu na šoli. izgleda sporočilo, ki so ga prejeli. Opozorim, da lahko Pridobljena znanja bodo lahko nadalje uporabili pri iskanju v sporočilu zapišejo tudi nekaj spremnih besed. virov za seminarske naloge, referate, domača branja ipd. Kot 5. Moja polica – Učence povabim, da si ustvarijo svojo polico, na katero bodo nanizali knjige, ki so jih z člani večjih knjižnic bodo lahko spremljali sezname veseljem prebrali. Odprejo tretjo ikono spodaj, storitev izposojenega gradiva po posameznih enotah in potek roka Moja polica. Desno zgoraj imajo tri bele krogce, ki jim izposoje. V drugih knjižnicah bodo lahko gradivo tudi rezervirali pomagajo pri ureditvi police. Kliknejo nanje in ali podaljšali. ustvarijo novo polico, tako da zapišejo ime police. Ponovno poiščejo knjigo, ki jo imajo pred seboj in z enakim znakom kot prej dostopajo do police ter nanjo PRILOGI namestijo knjigo. 6. Lokacija – Pogledamo še uporabnost zadnje ikone v spodnjem delu ekrana. Pod njo se skrivajo telefonska številka, mail, spletni naslov in lokacija na zemljevidu. 7. Članstvo v različnih knjižnicah - Povem še, da lahko dostopajo tudi do drugih knjižnic, npr. Mariborske knjižnice, le da si morajo pridobiti člansko izkaznico in geslo. Učenci lahko vprašajo, če je še kaj nejasnega, če si kakšnega koraka niso zapomnili. Sicer jih povabim, da čim več uporabljajo aplikacijo in zaključim učno uro. Učenci pospravijo knjige na police, kazalke na svoje mesto in seveda izklopijo in pospravijo telefone, da ne bo kakšnih nevšečnosti pri naslednjih urah pouka. 6 VREDNOTENJE UČNE URE IN UPORABNOST APLIKACIJE MCOBISS Po izvedbi učne ure v vseh oddelkih sem pripravila tudi anketni vprašalnik za učence (Priloga 2). Priloga 1: Učni list 577 [2] COBISS+ (Febr. 2020). DOI= https://plus.cobiss.si/opac7/bib/search [3] INFORMACIJSKO opismenjevanje: priročnik za delo z informacijskimi viri (2004). Ljubljana: Zavod Republike Slovenije za šolstvo, str. 105 – 116. [4] MOJA KNJIŽNICA (Febr. 2020). DOI= https:/ plus.si.cobiss.net/opac7/user/login [5] POSODOBITVE pouka v gimnazijski praksi. Knjižnično informacijsko znanje (2010). Ljubljana: Zavod Republike Slovenije za šolstvo. DOI= https://www.zrss.si/projektiess/gradiva/posgim/GRA_Knji znicno_informacijsko_znanje.pdf [6] SPITZER, Manfred (2016). Digitalna demenca: kako spravljamo sebe in svoje otroke ob pamet. Celovec: Mohorjeva, str. 185 – 201. Priloga 2: Anketni vprašalnik [7] SPODBUJANJE aktivne vloge učenca v razredu: zbornik prispevkov (2005). Ljubljana: Zavod Republike Slovenije VIRI IN LITERATURA za šolstvo, str. 146 – 164. [1] COBISS (Febr. 2020). DOI= ht ps://www.cobiss.si/ [8] UČENJE in poučevanje s knjižnico v osnovni šoli (2002). Ljubljana: Zavod Republike Slovenije za šolstvo, str. 10 – 16. 578 Veščine poučevanja na daljavo in praktični nasveti Distance learning skil s and practical advice Miroslava Minić Osnovna šola Dobje Dobje pri Planini 20 a 3224 Dobje pri Planini, Slovenija mira.minic@osdobje.si POVZETEK but it doesn’t matter because we can achieve our goals in a number of different ways. V obdobju učenja na daljavo je mnogim učiteljem težko zasnovati in organizirati svoje delo. Kako učence motivirati za KEYWORDS učenje matematike na daljavo ter jim učenje le-te tudi osmisliti? Kaj zanima učence in kako jih napeljati, da so zainteresirani za Learning, distance learning, ICT, tools, learning materials, samostojno izvrševanje nalog in aktivno komunikacijo? Ta motivation, communication vprašanja so me pripeljala do iskanja novosti in inovativnosti pri poučevanju v danih okoliščinah. 1 UVOD Priprava pouka na daljavo ima svoje posebnosti, učitelji pa lahko Pouk na daljavo nas je naučil veliko novega. Poleg tega, da smo imajo težave z neizkušenostjo pri uporabi IKT orodja ali učitelji imeli priložnost, da utrdimo svoje IKT kompetence, smo nezmožnostjo aktivnega vključevanja učencev. V tem prispevku v obdobju pouka na daljavo zelo hitro ugotovili, da ne obstaja je nekaj razmišljanj o teh težavah in osebnih izkušnjah uporabe perfektno digitalno okolje ali edinstveno IKT orodje, ki bo lahko orodij in priprave učnih gradiv, ki sem jih predstavila kot krožni rešilo vse naše učiteljske pomisleke in ki se bo lahko univerzalno proces učenja. Skratka, ni orodja, ki bi delovalo točno tako, kot uporabilo pri vseh učnih področjih - predmetih. želimo, vendar to tudi ni pomembno, ker svoje cilje lahko Pripombe staršev, da je otrokom težko slediti pouku na več dosežemo na več različnih načinov. različnih okoljih, temeljijo predvsem na nezadostni obveščenosti staršev in začetnem, pogosto neutemeljenem strahu, da se niti KLJUČNE BESEDE starši niti otroci ne bodo mogli spoprijeti z morjem različnih Učenje, poučevanje na daljavo, IKT, orodja, učna gradiva, informacij. motivacija, komunikacija Ta strah je popolnoma legitimen - imamo ga tudi učitelji. Vendar je zelo pogosto neutemeljen. ABSTRACT Naloga učitelja je, da razišče in se seznani s tehnološkimi in During the period of distance learning, many teachers find it avdiovizualnimi komunikacijskimi viri in orodji ter različnimi difficult to design and organize their work. How to motivate tehnikami in jih na smiseln način uporabi v razredu. Pestra students to learn mathematics at a distance and make their ponudba orodij lahko naredi učitelja sposobnega učenja z learning meaningful? What interests students and how to uporabo različnih pripomočkov [1]. persuade them to be interested in independent task performance Kaj potrebujemo, da bomo začeli učiti matematiko na and active communication? These questions led me to search for daljavo? Kako ustvariti dobro zgodbo in urediti svoje lastno IKT news and innovation in teaching in given circumstances. okolje, ki bo dobro funkcioniralo? Poleg tega obstajajo primeri, kako je IKT orodje že bilo uporabljeno v učnem okolju, kot tudi The preparation of distance learning has its own peculiarities, predloge o tem, kako uporabiti različna orodja. and teachers may have problems with inexperience in using ICT tools or the inability to actively involve students. In this paper, I bring some reflections on these problems and personal 2 DOBER RAZLOG ZA KAKOVOSTNO IKT experiences of using tools and preparing learning materials, UČENJE NA DALJAVO which I have presented as a circular learning process. In short, there are no tools that works exactly in the way we want them to, Eden izmed parametrov za ocenjevanje kakovosti šolskega pouka je uporaba različnih učnih metod. Enako mora kakovostni učni proces vključevati različna IKT okolja za učenje in uporabo različnih spletnih orodij. Pri izbiri okolja in orodij je bistveno predvsem, kako preprosta je njihova uporaba, seveda pa jih Permission to make digital or hard copies of part or all of this work for personal or prilagajamo predvsem predmetu in učni temi. Vsi se izogibamo classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full orodjem, kjer je potrebna dolga registracija, nato pa še citation on the first page. Copyrights for third-party components of this work must oblikovanje nekega močnega dolgega gesla in podobno. Prav be honored. For all other uses, contact the owner/author(s). tako nekatera okolja delujejo kot nadzorna plošča "vesoljske Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 579 ladje", kjer se prvotno navdušenje v petih minutah spremeni v na omejen le na splet-posta- razočaranje, saj ne vemo, kje naj začnemo. dostopnos učence strezniki/arnes ti in -ucilnice/ varnosti; 3 PRIMER UČNEGA PROCESA Objava GOOGLE Različne https://classro Skratka, ni orodja, ki bi delovalo točno tako, kot si želimo, ampak gradiv, okolje vsebine, om.google.co sploh ni pomembno, ker lahko lastne cilje dosežemo na več obvestil istočasno m/u/0/h načinov [2]. Vizualno lahko celoten postopek od ideje do izvedbe … Google sodelovanje – in uporabe materialov prikažemo kot ponavljajoči se proces. S Classroom v povezavi z ponavljanjem in eksperimentiranjem obenem izboljšujemo svojo Google Drive, https://www.g prakso. Google Doc, oogle.com/dri Načrtovanje dela (Slika 1): Google Google Meet Drive in ostalimi ve/ • Izbira IKT okolja (v katerem boste vi in učenci Dropbox Googlovimi https://www. nemoteno komunicirali) aplikacijami – dropbox.com/ • Metodološko-didaktična in strokovna priprava sodelovanje učitelja in spremljanje • Izbira IKT orodij ali orodja (ki bo uporabljeno pri podatkov v določeni enoti ali v širšem pomenu - pri oblaku določenem predmetu) Microsoft Različne https://www. • Priprava poteka dela in predvidevanje možnega okolje vsebine – v microsoft.com scenarija povezavi z /sl- • Izdelava samega gradiva (MS Microsoftovi • Komunikacija z učenci in povratna informacija si/microsoft- Teams mi orodji – 365/microsoft OneNote Ekipe, -teams/group- o365) OneNote, chat-software 1. UČNO Microsoft OKOLJE 6. Whiteboard, KOMUNIKACIJA 2. Z UČENCI IN STROKOVNA Sway … https://www. POVRATNA PRIPRAVA INFORMACIJA Spremljanje microsoft.com podatkov in /sl- istočasno si/microsoft- 5. IZDELAVA 3.IZBIRA IKT GRADIVA ORODIJ sodelovanje 365/onenote/ 4. POTEK digital-note- DELA IN PREDVIDEV ANJE taking- MOŽNIH OVIR app?ms.url=o nenotecom&rt Slika 1. Koraki pri postopku izdelave gradiv za pouk na c=1 daljavo https://www. 4 IZBIRA UČNEGA OKOLJA microsoft.com Najprej naj povem, da je na začetku najbolj pomembna izbira /sl- nekega splošnega okolja, v katerem bo pouk na daljavo sploh si/microsoft- potekal. Organizacijska IKT okolja ali platforme pomagajo vsem 365/onedrive/ učencem šole ali enega razreda (ožje – v okviru enega predmeta), online-cloud- da se zberejo in sodelujejo na enem mestu. Uporabniki morajo storage biti vpisani v določeno okolje (povezava in dostop sta lahko Web Enostavno https://wordp omejena). Obvestila, vsa gradiva in povratne informacije so na stranica objavljanje ress.org/ določenem mestu dostopna za vse deležnike. V preglednici (WordPres vsebin predstavljam nabor največkrat uporabljenih okolji s, (Preglednica 1). HTML) Preglednica 2. Primer – največkrat uporabljena IKT okolja YouTube Okolje za https://www.y OKOLJE TIPI / OPIS POVEZAVA objavo video outube.com/ MODELI posnetkov Organizac Moodle Številne in https://moodl ija, različne e.org/?lang=sl splošne Arnes vsebine – 5 STROKOVNA PRIPRAVA UČITELJA lastnosti dostop https://www.ar Ne glede na vrsto poučevanja, na katero se pripravljamo (na temeljijo nes.si/storitve/ daljavo ali v živo), je najpomembnejša strokovna priprava, ko 580 razmišljamo, katere cilje želimo doseči. V mojem primeru gre za Quizziz, Izdelava on-line kvizov https://quizizz.c pripravo matematičnih vsebin za učence. Pripravo oblikujemo na Kahoot om podlagi že obstoječih gradiv (stare priprave, spletna gradiva, Plickers učbeniki). Velikokrat si pri določeni temi pomagamo z https://kahoot. izkušnjami (npr. kakšne težave so učenci imeli pogosto pri com obdelavi določene snovi). Veliko matematičnih gradiv najdemo https://get.plick lahko tudi, če preprosto o določeni snovi pobrskamo na spletu. ers.com/ Potem že obstoječe priprave prilagodimo in popestrimo z določenimi primeri glede na potrebe učencev. Izkušnje so mi Google Obdelava besedila (online in https://www.go pokazale, da ima vsaka vsebina določeno stopnjo možnosti, da Docs offline) ogle.com/docs/ postane uporabna za učence v primeru, če dobro določimo, kaj je MS Word about/ v tej vsebini bistveno za naše učence. Znotraj določene snovi Meeting https://www.mi lahko pripravimo dodatne izzive za učence s pomočjo različnih Word crosoft.com/sl- orodij (papir, tabla, igra, kviz, vprašalnik, interaktivna si/microsoft- predstavitev ipd.). Ne smemo pozabiti, da če je določena snov 365/word dolgočasna za učitelja, je tudi učencem, kot poslušalcem, gotovo http://meetingw manj zanimiva. ords.com/ Prezi Predstavitve (online in https://prezi.co 6 IZBIRA IKT UČNIH PRIPOMOČKOV Sway offline) m/ Ko so osnovnošolci seznanjeni in navajeni IKT okolja, v Padlet https://sway.off katerem izmenjujemo informacije, lahko dodajamo oz. MS ice.com/my uporabljamo še določene interaktivne dodatke. Znotraj Powerpoi https://padlet.c določenega in znanega okolja za učenje je to lažje. V mojem nt om/ primeru sem uporabljala okolje MS Teams znotraj o365 za https://www.mi izmenjavo informacij z učenci, oddajanje obvestil, crosoft.com/sl- videoposnetkov, reševanje domačih nalog, komunikacijo itd. Za si/microsoft- obogatitev samih učnih vsebin pa sem izbirala med številnimi 365/powerpoint spletnimi učnimi pripomočki (npr. Geogebra, Excelove preglednice, Google Sheets, MS Forms, Quizziz, Kahoot, Padlet Classtools Spletno mesto za https://www.cl …) (Preglednica 2). ustvarjanje izobraževalnih asstools.net/ Preglednica 2. Različni primeri pogosto uporabljenih IKT iger, testov in kvizov orodij/pripomočkov/aplikacij MS Forms Izdelava kvizov in https://forms.of IKT učni OPIS POVEZAVA preizkusov znanja fice.com/Pages/ pripomoč DesignPage.asp ki Google x obrazci Geogebra Prosto dostopna aplikacija https://www.go za predstavljanje https://www.ge ogle.com/intl/sl matematičnih grafov, 3D ogebra.org/?lan _SI/forms/abou modelov, geometrije … g=sl t/ MS Excel Matematične preglednice, https://www.mi Showme Izdelava predstavitve s https://www.sh ustvarjanje formul za crosoft.com/en- snemanjem glasu, pisanjem owme.com/ računanje … us/microsoft- in risanjem 365/excel#pivot MS https://www.mi -forPersonal Whiteboa crosoft.com/sl- rd si/microsoft- Google Sodelovanje pri delu https://docs.go 365/microsoft- Sheets ogle.com/sprea Google whiteboard/digi dsheets/u/0/ jamboard tal-whiteboard- app https://edu.goo gle.com/produc ts/jamboard/? modal_active=n one 581 7 POTEK DELA IN PREDVIDEVANJE 9 KOMUNIKACIJA Z UČENCI IN MOŽNIH OVIR POVRATNE INFORMACIJE Ko začnemo pripravljati določeno učno snov za učence, sledi Komunikacija z deležniki in povratne informacije sta bistveni del strokovna in tehnična priprava za izdelavo gradiv. Če ustvarjamo v tem učnem ciklu. Kar smo naredili, podelimo z učenci in video, se moramo bolj natančno pripraviti, kot če stojimo v čakamo na povratne informacije in odzive. Zato moramo biti razredu pred tablo. Predvidevati moramo, kaj bomo natančno najprej prepričani, da je postavljeno okolje za delo dostopno in povedali. Skrbeti moramo za kratko, jasno in jedrnato izražanje razumljivo vsem sodelujočim. Z ustvarjenim poskušamo ter za uporabo barv, slik in drugih podrobnosti. Predvidevati motivirati učence in tudi spodbuditi njihovo radovednost. Če moramo tudi odzive učencev na podano snov in jim znotraj tega nam to uspe, je učenje učinkovitejše, dolgotrajnejše in na koncu ponuditi priložnost za samostojno razmišljanje, raziskovanje in bolj prijetno. Tekmovalno učenje je včasih učinkovito, prisilno aktivno učenje [3]. učenje pa v takšnem okolju skoraj nemogoče. Če pripravljamo kviz ali kratko preverjanje znanja, gremo Radovednost in aktivno sodelovanje učencev lahko skozi fazo načrtovanja, predvidevanja in izdelave. Nekatera IKT spodbudimo z zanimivo temo ali igro, vendar se moramo nujno orodja imajo bogate lastnosti in včasih med načrtovanjem zavedati, da so pri učencih lahko prisotne različne ovire, ki so odkrijemo, da lahko naredimo veliko bolje, če spremenimo načrt. zunaj našega dosega in moči: utrujenost, stres, zasebne težave … Včasih je izbrano orodje takšno, da ugotovimo, da ni možno, da Koliko smo resnično uspešni, lahko ugotovimo, če izpeljemo to, kar smo si zastavili. To je tudi del učenja in tolaži priskrbimo povratne informacije [5]. Te se lahko pridobijo v me, da ob izkušnjah z določenimi orodji (npr. MS Forms ali obliki klepetov, video komentarjev, anket, e-poštnih sporočil, Google obrazci) postopek postane lažji (Slika 2). krajših preizkusov ali vprašalnikov (Slika 3). Moja izkušnja je, da so videokonferenčna srečanja z razredom oz. skupinami učencev in učiteljem najboljši nadomestek poučevanja v živo. Neposredna komunikacija je bolj spontana in zmanjšuje psihološko nepripravljenost postavljanja vprašanj. Pri meni se je dobro pokazala uporaba videokonferenčnega srečanja v kombinaciji z deljenjem namizja in bele table obenem. Na ta način so bili učenci direktno vključeni v razlago snovi in so lahko komentirali ter obenem sodelovali pri pisanju na tablo, kot v razredu pri pouku v živo. Na podlagi takšnega sodelovanja nisem imela večjih težav tudi pri samem ocenjevanje takšnega dela. Zdi se mi pomembno prisluhniti pripombam in kritikam vseh, ki so deležni učnega procesa. Učenje na daljavo je Slika 2. Delitev posnetka z učenci znotraj določenega IKT zagotovo priložnost za krepitev vezi med učiteljem in učencem z okolja namenom iskanja in zadovoljevanja skupnega cilja - pridobivanja znanja. Pri samem ocenjevanju učencev se mi zdi pomembno, da v ospredje postavimo cilj: učenje iz radovednosti 8 IZDELAVA GRADIV s ciljem pridobivanja znanja in poskušamo motivirati čim več Pri izdelavi gradiv moramo biti pozorni na cilj, da želimo učencev k čim večji ažurnosti in vključenosti. pritegniti in zadržati pozornost naših učencev. Pomembna je kvaliteta narejenega gradiva [4]. Npr. pri posnetku je zelo pomembna tudi kakovost tona in slike, hitrost govora, naš glas, 10 ZAKLJUČEK rokopis, pavze, ponavljanja in tudi morebitne napake. Potrebno Pri poučevanju na daljavo se srečujemo z različnimi preprekami. je vnaprej pripraviti določene pripomočke za snemanje in jih Največja težava pri poučevanju na daljavo je pomanjkanje vnaprej preizkusiti. Primerno je narediti nekakšen seznam nalog spremljanja direktnega oz. osebnega odziva učencev ter direktno in primerov, ki jih bomo obdelali. Pripraviti je potrebno še spremljanje učenčeve motivacije. Pri izvedbi pouka na daljavo se podrobne rešitve in dodatne opombe. moramo v prvi vrsti zavedati sposobnosti učencev. V razredu imamo zelo različne učence, ki živijo v različnih domačih okoljih. Pri tem se držimo načela manj je več v okviru učnih načrtov. Ne smemo pa pozabiti tudi na bolj vedoželjne učence za katere je pomembno pripraviti kakšno dodatno nalogo ali izziv. Učenci morajo kljub temu, da se šolajo na daljavo, redno spremljati pouk in sodelovati na način predpisan s strani učitelja ali šole. Pred pričetkom dela mora učitelj preveriti IKT kompetence učenca. Šele, ko ima vpogled, kakšne so situacije pri učencih, lahko načrtuje izvedbo pouka s pomočjo predstavljenih IKT oblik okolja in izbranih IKT pripomočkov. Pri samostojnem delu je pomembno, da učitelj poda jasna, konkretna navodila in da učence vodi pri njihovem delu na način, da sprotno preverja njihovo delo in jim daje redne povratne informacije, ki bodo Slika 3. Primer zastavljanja nalog za učence v okolju Teams učencu omogočale napredovanje po njihovih zmožnostih. To je 582 tudi pomembno za učence, ki ne znajo načrtovati svojega časa https:/ www.zrss.si/strokovne-resitve/ponudba- učenja in so za učno delo manj motivirani. resitev/jazon. [3] Suban, M., Gorše, P. M., [et al.], 2018. Formativno spremljanje pri matematiki : priročnik za učitelje. Zavod Republike Slovenije za šolstvo. VIRI IN LITERATURA [4] Evropska spletna platforma za šolsko izobraževanje. 2020. [1] Bregar, L., Zagmajster, M., 2000. Izkušnje pri razvoju in Prehod na spletno poučevanje: sprint do poučevanja na uvajanju študija na daljavo na Ekonomski fakulteti. daljavo! . Gradivo za učitelje. Priročniki., Univerza v Ljubljani. Ljubljana : Nacionalna projektna https://www.schooleducationgateway.eu/sl/pub/resources/t enota za študij na daljavo, 2000, utorials/moving-your-teaching-online.htm. http://www.mirk.si/snd/analize/Opravljena_analiza.html. [5] Zavod Republike Slovenije za šolstvo. 2020. Podpora [2] Zavod Republike Slovenije za šolstvo. 2020. Stokovne učiteljem za izobraževanje na daljavo. rešitve – Izobražujmo na daljavo. https://www.zrss.si/objava/podpora-uciteljem-za- izobrazevanje-na-daljavo. 583 Izdelovanje preprostih zemljevidov s programom Google Earth pri pouku geografije Simple map making using Google Earth program in teaching geography Nataša Mrak OŠ dr. Janeza Mencingerja Bohinjska Bistrica Savska cesta 10 4264 Bohinjska Bistrica, Slovenija natasa.mrak@guest.arnes.si POVZETEK Earth offers an interesting Earth exploration experience. Each student uses their own computer, they can adjust the pace of work Pri poučevanju geografije so zemljevidi zelo pomembni, morda as needed, with the emphasis on every student being responsible celo najbolj. Z njimi prikazujemo pomanjšano in posplošeno for completing the work in the designated time and being able to ponazoritev celotne Zemlje ali njenih izbranih delov. Na ta način do some of the tasks independently later. The teacher also needs lahko učencem približamo oddaljene kraje, ki so nam v obliki to address the issue of internet safety. šolskega dela (in tudi sicer) pogosto nedosegljivi. Opazovanje je namreč temeljna metoda dela v geografiji, ki jo izvedemo KEYWORDS posredno, kadar neposrednega opazovanja ni mogoče izvesti. Eden od pomembnih ciljev geografije je razvijanje orientacije in Map, Google Earth, geography, cross-curricular integration, kartografske pismenosti. Pri tem je smiselno, da osnovne digital competences spretnosti orientacije in risanja zemljevidov nadgradimo z digitalno obliko, ki je pravzaprav današnji jezik mladih. 1 UVOD Izdelovanje zemljevidov v Google Earth programu nudi zanimivo izkušnjo spoznavanja Zemlje. Delo poteka Raziskovanje Zemlje je že od nekdaj privlačilo človeka. Svoje individualno, vsak učenec uporablja svoj računalnik, tempo dela poti in spoznanja je beležil sprva s preprostimi skicami in si po potrebi prilagaja. Poudarek je tudi na odgovornem pristopu risbami, kasneje pa so nastali zemljevidi, kot jih razumemo posameznika do dela, da pravočasno in natančno opravi osnovne danes. »Vsem zemljevidom, starim ali najsodobnejšim, naloge in zmore kasneje določene naloge izdelati samostojno. Pri elektronskim in interaktivnim je skupno, da prikazujejo delu je pomembno opozoriti tudi na varno in odgovorno rabo pokrajino na poseben geografsko-kartografski način.« [1] interneta. Spoznavanje in doživljanje neke pokrajine v živo je nemogoče menjati zgolj z opazovanjem satelitskih posnetkov in KLJUČNE BESEDE zemljevidov, so pa ti odlično sredstvo za popestritev in Zemljevid, Google Earth, geografija, medpredmetno spoznavanje sveta pri geografiji. Vsebine, ki jih na zemljevidih povezovanje, digitalne kompetence prikažemo, so lahko tudi tematske in služijo spoznavanju obravnavane teme pri določenem predmetu (pogosto zgodovini, ABSTRACT lahko tudi angleščini, slovenščini, gospodinjstvu ipd.). Tak način Maps are very, if not most important in teaching geography. medpredmetnega povezovanja je predstavljen tudi v prispevku. They are used as a generalized illustration of the entire Earth or S pomočjo programa Google Earth lahko učenci raziskujejo its selected parts. Using maps, we can bring distant, inaccessible Zemljo in izbrana območja ter izdelajo lastne digitalne places closer to students. Observation has always been a zemljevide, na katerih prikažejo vsebine, ki jih želijo predstaviti. fundamental method in geography and can be performed Prednost takega načina je, da lahko na prikazan zemljevid indirectly when direct observation cannot be used. One of the nanizamo poljubne elemente, jih po potrebi skrijemo, dodajamo, important goals of geography has been to develop orientation and spreminjamo, dokler nismo s svojim izdelkom zadovoljni. cartographic literacy. It makes sense that the basic map Končni izdelek je lahko del predstavitve ali zaključen zemljevid orientations are upgraded with a digital form, which is actually (slika), ki ga lahko natisnemo, posredujemo, prav tako pa lahko today's language of young people. Creating maps in Google posredujemo tudi samo posamezne elemente zemljevida (točke, območja, črte). 2 METODE DELA Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed Geografija je v program osnovne šole umeščena zato, da učencu for profit or commercial advantage and that copies bear this notice and the full pomaga pridobiti znanje, sposobnosti in spretnosti, s katerimi se citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). lahko orientira. Pri pouku geografije učenci razvijajo sposobnosti Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia za uporabo preprostih geografskih raziskovalnih metod, s © 2020 Copyright held by the owner/author(s). 584 katerimi pridobivajo informacije o okolju. Usposabljajo se za začetku precej zahtevna. Niso navajeni perspektive, zato je rabo različnih sredstev in medijev, pri čemer je še posebej interpretaciji takih slik in pri risanju zemljevidov na tako podlago pomembna informacijska tehnologija. Učenci z IT tudi potrebno posvetiti precej pozornosti. Po njihovi uporabi je samostojno zbirajo in obdelujejo geografske informacije in jih učencem veliko lažje razumeti zemljevide z njihovimi predstavljajo. [2] abstrakcijami in simboli. [3] V članku je predstavljeno delo s programom Google Earth V nadaljevanju je prikazan postopek za izdelavo zemljevidov (Google Zemlja), ki omogoča učencem spoznavanje in v Google Earth programu. raziskovanje območij Zemlje, ki jim sicer ne bi bila dostopna. Kadar ne moremo neposredno opazovati obravnavane pokrajine, poskušamo ustvariti predstave s pomočjo projekcije, ki je ena 3 POTEK DELA temeljnih metod pri pouku geografije. Za izdelavo zemljevidov v Google Earth programu uporabimo grafično metodo. Učne 3.1 Izvedba ure metode razumemo kot najboljše poti in načine pridobivanja Ura je v celoti izvedena v računalniški učilnici, kjer vsak učenec znanja, sposobnosti in navad z dobrim sodelovanjem učitelja in lahko dela na svojem računalniku. Če je računalnikov manj in učenca. Obe metodi uvrščamo v metode posrednega opazovanja. delo poteka v paru, vsak učenec opravi nekaj nalog. Program [3] Google Earth je že naložen na računalnikih, učenci pa si ga doma lahko naložijo sami. 2.1 Metoda projekcije Učencem predstavimo končni cilj: izdelan zemljevid z vsemi Opazovanje je temeljna metoda dela v geografiji. Med sodobna osnovnimi podatki, ki ga shranijo v obliki slike. Za učence sredstva, s katerimi opazujemo in raziskujemo pokrajino našega sedmega razreda, ki se običajno prav pri geografiji prvič srečajo planeta, uvrščamo tudi letalske in satelitske posnetke. Slednji so z izdelovanjem digitalnega zemljevida, je to dovolj. Učenci nam na voljo v Google Earth. Satelitski posnetki, ki jih omogoča osmega razreda pa se naučijo oziroma obnovijo izdelavo program, razširjajo paleto geografskih didaktičnih sredstev. zemljevida in nato pripravijo svoj zemljevid, ki je del Google Earth ali Google Zemlja je program, ki je večini zelo predstavitve (govornega nastopa). dobro poznan. Uporablja se ga za iskanje in načrtovanje poti, Cilj je, da učenci v eni uri uspejo po navodilih izdelati prikazovanje pokrajin, pogled na svet v 3D tehniki. Najbolj zemljevid, se naučijo samostojno delati s programom in ustrezno zanimiv za učence je ulični (street view) pogled, možno pa je shranijo svoj izdelek. izdelati tudi prava potovanja (povezati določene točke in slike v Ura je zasnovana kot del medpredmetnega povezovanja: v nekakšen video posnetek) in preproste zemljevide. sedmem razredu na temo Grkov, v osmem razredu Amerike Z uporabo satelitskih posnetkov lahko učenci samostojno (slika 1), v devetem razredu aktualnih dogodkov (30 let padca raziskujejo določeno območje. Smiselno pa je, da jih vsaj od berlinskega zidu ipd.). Vsebine, ki jih prikažemo na zemljevidu, začetka pri tem usmerjamo, saj je informacij ogromno. Učenčevo se navezujejo na snov zgodovine, kulture, športa in drugih opazovanje naj ne bo samo preprosto gledanje, ampak zavestna predmetov, obenem pa z njimi vsebinsko sledimo učnemu načrtu dejavnost. Projekcija je najpomembnejša pri usvajanju znanja, geografije (Sredozemlje, Amerika, Slovenija v Evropi in saj z njo oblikujemo jasne, pravilne predstave o pokrajinah, ki jih mednarodne povezave …). Pomembno je dobro sodelovanje med nismo nikoli videli. [3] učitelji, da se obravnavane vsebine drugih predmetov geografsko umestijo v prostor in obenem na zemljevid v obliki ustreznih 2.2 Grafična metoda (risanja) simbolov (sličic). Tudi metoda risanja je za geografijo zelo pomembna. Omogoča Ura se lahko izvede samostojno za poučevanje različnih nazornost, preglednost, pri pouku geografije ne moremo mimo geografskih vsebin. uporabe različnih prostorskih prikazov. Metoda risanja omogoča hitrejše in lažje razumevanje geografskih vsebin. Med temeljno risanje spada tudi risanje geografskih zemljevidov. [3] Zemljevid je pomanjšana podoba Zemljinega površja, narisana na ravno podlago, največkrat na papir. Kartografi izdelujejo zemljevide s pomočjo računalniških programov in letalskih oziroma satelitskih posnetkov površja. Ti jim služijo kot vir podatkov in osnova za risanje v ptičji perspektivi, v kateri je narisana večina zemljevidov. Vsak zemljevid mora biti ustrezno opremljen z naslovom, merilom in legendo, ki je potrebna, da simbole razume vsak, ki zemljevid uporablja. [1] Pri izdelavi zemljevida poskrbimo, da učenci čim bolj pravilno in natančno izdelajo svoj zemljevid. Zemljevidi morajo ustrezati razvojni stopnji učencev, ne smejo biti preveč posplošeni, upoštevati pa moramo tudi estetskost pri oblikovanju. Slika 1. Izdelovanje zemljevida pri obravnavi Amerike Satelitski posnetki, ki jih omogoča program Google Earth, omogočajo pogled na pokrajino, jo povezujejo z zemljevidom, zato jih lahko uporabljamo tudi kot pomoč pri uvajanju v razumevanje zemljevidov. Uporaba slik iz zraka je za učence v 585 3.2 Prvi koraki za izdelovanje zemljevida v Google Earth Učenci program že uporabljajo za iskanje lokacij, poti in uličnega ogleda (street view), ne poznajo pa vseh možnosti, ki jih ponuja. Učencem najprej predstavimo stransko vrstico, ki vsebuje Iskalnik, Mesta (shranjevanje lastnih vsebin) in Sloje (izbiranje že vnesenih vsebin: meje, imena držav, ceste …). Če je stranska vrstica skrita, jo prikličemo s klikom na prvo ikono v orodni vrstici (Prikaži stransko vrstico) ali poiščemo in odkljukamo v zavihku Pogled. Nekateri učenci se hitro znajdejo in poiščejo sami, za tiste manj spretne pa je pomembno, da podajamo navodila postopno ob hkratni projekciji na tablo (delamo skupaj z učenci). Pisanje navodil ni potrebno, saj si največ zapomnijo s tem, ko delajo sami. Na zemljevid postopno vrisujemo točke (Doda oznako položaja), meje (Doda pot), Slika 3. Uporaba funkcije Doda mnogokotnik za prikaz pobarvamo območja držav ali druga izbrana območja (Doda območja Yellowstonskega parka mnogokotnik). Podobno se lotimo tudi ostalih vsebin, pri čemer smiselno V sedmem razredu pri spoznavanju Grčije označijo lokacije, povečujemo težavnost. V devetem razredu lahko že raziskujemo ki so povezane s Starimi Grki: Atene, Knosos, goro Olimp, mikrolokacije: na primeru berlinskega zidu (Brandenburška Olimpijo, Delfi ipd. (slika 2). Označijo tudi morji, ki Grčijo vrata, Potsdamski trg, Checkpoint Charlie, potek avtoceste 115). oblivata (Egejsko in Jonsko morje). Pomembno je, da neko Nadaljnje vnose učenci naredijo samostojno, delo pa območje ne samo vtipkajo v iskalnik, dodajo oznako in nadaljujejo doma ali po dogovoru v šoli. Med sabo si lahko poimenujejo, ampak si ga tudi podrobneje ogledajo, oznako pa pomagajo: spretnejši pomagajo tistim učencem, ki niso najbolj postavijo zelo natančno npr. za Atene na Partenon, za Knosos na vešči dela z računalnikom. arheološko najdišče palače, za Olimpijo na stadion. Pri tem 3.3 Urejanje in shranjevanje zemljevida spoznajo, da se Olimpija (prizorišče prvih olimpijskih iger) in gora Olimp (sedež grških bogov in najvišja gora Grčije) nahajata Za večjo preglednost našega dela je potrebno urediti vnose, saj daleč narazen. Na zemljevid vnesemo tudi današnjo mejo Grčije se v programu shranjuje delo vseh učencev. V Mestih se z ukazom Doda pot. V slojih moramo imeti vklopljen sloj postavimo na Moja mesta in z desnim klikom dodamo mapo, ki državne meje. Omejimo se samo na celinsko mejo, zato začnemo jo ustrezno poimenujemo (Stari Grki, Amerika …). Vse vnose, z dodajanjem točk (klikanjem) na eni strani in zaključimo na ki se nanašajo na določeno temo, prenesemo (z levim klikom) v drugi. Če želimo mejo popraviti ali smo naredili napako, lahko izbrano mapo. Če mapo ustvarimo že takoj na začetku, se vnosi posamezne točke premikamo, dodajamo, izbrišemo, dokler meje avtomatično shranjujejo vanjo. (oziroma poti) ne shranimo. Vsako shranjeno oznako, mejo, mnogokotnik lahko poljubno urejamo. Z miško se postavimo na izbran vnos, s klikom na desni gumb se nam ponudijo možnosti, kjer izberemo spodnjo Lastnosti. Odpre se nam okno, v katerem lahko urejamo ime, velikost, barvo, prosojnost (primerno za označevanje območij/mnogokotnikov) in tudi simbol. S klikom na standardni žebljiček poleg imena se nam odpre novo okno, v katerem lahko izberemo številne druge simbole (za promet, poklice, restavracije …), lahko pa dodamo svoj simbol/sličico, če izberemo Dodaj ikono po meri. Namesto običajnega žebljička lahko za Olimp dodamo Zevsa, za Atene boginjo Aten ipd. Za enkratno uporabo je dovolj, da na spletu poiščemo ustrezno sliko in povezavo prilepimo v polje. Če pa želimo, da slike ne izginejo (shranjevanje poti), jih je bolje najprej shraniti v datoteko na računalniku in izbrati ukaz Prebrskaj ter nato poiskati shranjeno sliko. Slika 2. Shranjevanje vnesenih vsebin v stranski vrstici Ko so vsi vnosi urejeni, zemljevid orientiran proti severu (na Mesta kompasu zgoraj desno kliknemo na oznako N za sever), je V osmem razredu pri spoznavanju Amerike poleg vrisovanja potrebno zemljevid opremiti tudi s potrebnimi podatki in shraniti. točk in mej označijo posamezna območja parkov, prerij, Najprej pripravimo območje, ki ga želimo na zemljevidu tornadov ipd., za kar je potrebno uporabiti funkcijo Doda prikazati. Poskrbimo, da bo dovolj prostora za dodajanje naslova, mnogokotnik (slika 3). Tako kot za mejo države dodajamo točko legende, podatkov o avtorju ter datumu izdelave. Odstranimo vse za točko, program pa sočasno riše območje. Paziti moramo, da nepotrebne in moteče podatke: v Slojih izklopimo fotografije, točk ne rišemo preko že obarvanega dela, saj s tem brišemo ceste, oznake, meje, v iskalniku izbrišemo vse zadetke. območje. Vsak zemljevid potrebuje tudi merilo, ki spada med osnovne matematične elemente karte. Najbolj običajen zapis je številčno 586 merilo, lahko je tudi opisno, Google Earth pa nam ponuja grafično ali dolžinsko merilo. Gre za črto razdeljeno na več enakih delov pri čemer je dolžina posameznega dela odvisna od merila karte. [4] V zgornji orodni vrstici izberemo ukaz Shranjevanje slike, pri čemer se nam odprejo nova okna. V prvo okno vpišemo naslov zemljevida, pri opisu dodamo ime avtorja ter kraj in leto izdelave. Slika 5. Primer zemljevida z manj nasičenimi barvami Nekaj časa in potrpežljivosti zahteva ugotavljanje prave velikosti vstavljenih oznak, napisov, odstranjevanje nepotrebnih podatkov ter končno shranjevanje zemljevida. Če želimo doseči kakovosten izdelek, je potrebno izdelati več različic in iskati izboljšave. 4 REZULTATI Slika 4. Urejanje naslova in legende zemljevida S predstavljenim načinom dela so uspešno doseženi številni cilji, V drugem oknu urejamo legendo (slika 4): morebitne ki jih predvideva tudi učni načrt za geografijo: učenci uporabljajo odvečne simbole izbrišemo, napačno zapisana imena (šumnike) različne načine prikazovanja geografskih informacij, se popravimo. Obe okni lahko poljubno prestavljamo po zemljevidu. orientirajo na zemljevidu, se usposabljajo za uporabo različnih S klikom na Možnosti zemljevida urejamo elemente, ki jih vrst zemljevidov, razvijajo poznavanje lokacij in prostorov ter želimo prikazati: poleg naslova in legende dodamo še merilo, poskušajo nacionalne in mednarodne dogodke postaviti v kompas pa lahko izklopimo, saj smo zemljevid že poravnali proti geografski okvir, pridobljeno znanje medpredmetno poglabljajo. severu. Če želimo, da naši vnosi pridejo bolj do izraza, pri [2] Cilje dosegamo z aktualnim izbiranjem vsebin, s sodobnimi Prilagajanju sloga izberemo zemljevid z manj nasičenimi učnimi oblikami in metodami, pri tem upoštevamo potrebe in barvami (slika 5). S klikom na Shrani sliko zemljevid interese učencev in posegamo po uporabi sodobnih tehnologij. poimenujemo in shranimo na ustrezno mesto v računalniku. Učenci lahko svoje kompetence razvijajo le, kadar imajo 3.4 Navodila za delo priložnost biti aktivni. Učijo se samostojnega dela: uporaba programa za izdelavo zemljevidov. Učijo se sistematičnosti in Učenci za izdelavo zemljevida čim bolj sledijo naslednjim organizacije dela: iskanje in shranjevanje slik, vnos vsebin na navodilom. zemljevid, urejanje in izvoz zemljevida. Učijo se estetskega oblikovanja. Učijo se tudi potrpežljivosti in vztrajnosti, zlasti pri - Zemljevid je izdelan v ustrezni velikosti in prikazuje risanju večjih površin npr. držav, celin. Nekateri učenci svoje obravnavano območje v celoti. znanje uporabijo tudi pri drugih predmetih, pri raznih projektih - Zemljevid je pravilno orientiran (sever zgoraj). (slika 6) ali v osebnem življenju. - Nepotrebni podatki so odstranjeni (izključeni). Za geografijo je ključnega pomena neposredno opazovanje, - Zapis geografskih imen je pravilen (upoštevanje ki pa ga uspešno nadomestimo z dobrimi posnetki. Analiza velikih začetnic in razmakov). satelitskih posnetkov razvija opazovanje, omogoča predstavo in - Med ponujenimi zadetki v iskalniku so izbrani pravilni. učenca usposablja, da prostor razume razvojno. [3] Učenci z - Vrisani podatki (točke, linije …) so natančno umeščeni analizo satelitskih posnetkov in izdelavo lastnih zemljevidov v prostor (zemljevid). razvijajo orientacijo in prostorsko predstavo. Če vključimo še - Zemljevid je ustrezno opremljen: naslov, merilo, medpredmetno povezovanje, učenci pridobljene informacije legenda, podatki o avtorju in letu izdelave. poglobijo in jih prostorsko umestijo. - Izbrani simboli so ustrezni in nazorni, lahko so nadomeščeni tudi z drugimi sličicami. - Oznake in napisi so ustrezne velikosti in barve, pomembna je preglednost in estetskost. - Končni zemljevid je izvožen in shranjen kot slika v .jpg obliki. 587 izdelovanje zemljevidov nadgraditi z delom v ArcGIS programu, ki se uporablja kot osnova za delo na številnih delovnih mestih. Pomembne so tudi digitalne kompetence, ki jih učenec pridobi s takim načinom pouka, še zlasti v času, ki nas sili, da ne uporabljamo šolskih atlasov (epidemija). Navodila za izdelavo zemljevida je na podoben način možno podati tudi prek video srečanj ali video vodičev v primeru učenja na daljavo. Tako učencem kljub omejitvam gibanja omogočimo zanimivo raziskovanje Zemlje Slika 6. Predstavitev Erasmus+ držav s pomočjo Google Earth programa VIRI IN LITERATURA [1] Atlas Slovenije za osnovne in srednje šole [Kartografsko 5 ZAKLJUČEK gradivo]. 2014. Ljubljana. Mladinska knjiga . [2] Učni načrt. Program osnovna šola. Geografija, 2011. Izbrani način dela zahteva dobro učiteljevo pripravo: poznavanje Ljubljana: Ministrstvo za šolstvo in šport: zavod RS za možnosti za delo v programu in preizkus možnosti, preverjanje šolstvo. nameščenosti in delovanja programa na računalnikih. Izdelavo [3] Brinovec, S., 2004. Kako poučevati geografijo: didaktika zemljevida je potrebno preizkusiti tudi v šolski računalniški pouka. Ljubljana. Zavod Republike Slovenije za šolstvo. učilnici, da se prepričamo o delovanju programa. Učenci se programa hitro priučijo, saj je narejen za široko [4] Lovrenčak, F., 1996. Matematična geografija. Ljubljana. uporabo. Smiselno ga je uporabiti večkrat, da se znanje ne izgubi. Filozofska fakulteta, Oddelek za geografijo. V devetem razredu in kasneje v srednji šoli bi bilo možno 588 IKT po vertikali pri pouku matematike Vertical ICT in mathematics lessons Vesna Mrkela Osnovna šola Draga Kobala Maribor Tolstojeva ulica 3 2000 Maribor, Slovenija vesna.mrkela@osdk.si POVZETEK development. In the coming years we will upgrade and expand our work so that students will not only have mathematical V prispevku je predstavljen razvoj IKT pri pouku matematike po knowledge but will also be able to use information and vertikali. Izkazalo se je, da veliko učencev ne obvlada niti communication technology to solve problems. osnovnega pripomočka za matematiko, kot je kalkulator. Kot učiteljica matematike in vodja aktiva matematike na Osnovni šoli KEYWORDS Draga Kobala Maribor sem spoznala, da učenci potrebujejo osnovne veščine IKT, ki jih lahko naučimo pri matematiki. ICT, matemtics, digital competence Sklicala sem učiteljice matematike po vertikali in izdelale smo načrt vpeljevanja IKT po vertikali pri pouku matematike. 1 UVOD Vpeljale smo različne didaktične metode poučevanja s pomočjo IKT in tako začele digitalno opismenjevati učence od prvega do Razvijanje različnih kompetenc: bralnih, pismenih, digitalnih in devetega razreda. Izkazalo se je, da so učenci sedaj dosti bolje drugih se dandanes že pričakuje na vsakem predmetnem digitalno pismeni in z zagotovostjo lahko trdimo, da bodo naši področju. V času dela na daljavo nas je marsikaj presenetilo in učenci odšli iz šole digitalno pismeni, saj se trudimo vsaj pri spoznali smo, kje smo pri matematiki dobri in kaj lahko še matematiki nameniti kar nekaj ur za njihov digitalni razvoj. V izboljšamo. Na aktivu matematike smo ugotovili, koliko prihajajočih letih bomo svoje delo še nadgradile in razširile, tako izboljšav pri pouku samem lahko še naredimo. Na nivoju šole da učenci ne bodo imeli le matematičnega znanja, ampak si bodo smo imeli izdelan načrt razvijanja digitalnih kompetenc, a pri reševanju problemov znali pomagati tudi z informacijsko ugotovili smo, da to ni dovolj. Naredili smo načrt usvajanja komunikacijsko tehnologijo. digitalnih kompetenc pri matematiki in jih razdelili po vzgojno- izobraževalnih obdobjih. Pregledali smo učni načrt za KLJUČNE BESEDE matematiko in iskali možnosti, kako razvoj digitalnih kompetenc IKT, matematika, digitalne competence smiselno vključiti v pouk matematike. ABSTRACT 2 PREGLED STANJA The paper presents the development of ICT in the teaching of mathematics vertically. It turns out that many students do not V času dela na daljavo smo spoznali, kako malo digitalnih even master a basic math tool such as a calculator. As a kompetenc učenci razvijejo v času pouka. Čeprav smo že mathematics teacher and head of the mathematics department at pretekla leta razvijali digitalne kompetence pri matematiki, smo the Draga Kobala Elementary School in Maribor, I realized that ugotovili, da to ni dovolj in da moramo naše načrte razvoja students need basic ICT skills that we can learn in mathematics. digitalnih kompetenc posodobiti in razširiti. S pomočjo anket I organized a meeting of all math teachers from 1st to 9th grade smo ugotovili, kaj je učencem delalo težave in prav na teh and we made a plan to introduce ICT vertically in math lessons. podatkih smo začeli pregled stanja pri matematiki. Ugotovili We introduced various didactic methods of teaching with the smo, da nekaj stvari že dobro izvajamo, a bi jih morali vsako leto help of ICT and therefore began to digitally educate students ponavljati in utrjevati ter nadgrajevati. Na šoli začno učenci from the 1st to the 9th grade. It turned out that students are now spoznavati BEE-BOOTke že v prvem razredu, kjer dobro much more digitally literate and we can say with certainty, that pridobijo in utrdijo orientacijo v ravnini in prostoru [2]. our students will leave school digitally literate, as we try to Ugotovili smo, da imamo na šoli veliko število tablic in devote at least a few hours in mathematics to their digital računalnikov, ki jih v prvem izobraževalnem obdobju ne uporabljamo, pa bi jih lahko. V drugem izobraževalnem obdobju učenci dobijo svoje digitalne identitete, za katere je pomembno, da jih neprestano uporabljajo, in da jih opozarjamo na varnost ter Permission to make digital or hard copies of part or all of this work for personal or pomembnost identitete. Na šoli imamo ustvarjene spletne classroom use is granted without fee provided that copies are not made or distributed učilnice že v drugem izobraževalnem obdobju, a jih pri pouku for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must matematike ne uporabljamo. Za vajo v računanju uporabljamo le be honored. For all other uses, contact the owner/author(s). delovne zvezke in učne liste, bi pa lahko učence začeli navajati Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). na različne spletne strani, ki omogočajo nadgrajevanje v znanju 589 računanja in raziskovanje novih računskih operacij. Ugotovili učence že začeli opismenjevati tudi s programi za delo s smo, da učencem pri geometriji prikažemo le konkretne modele, preglednicami. Ker smo ugotovili, da učencem dela znanje lahko bi te predstave nadgradili s prikazi na spletu. Pričeli bi poštevanke velike težave, smo zamenjali vrstni red poučevanja lahko uporabljati tudi programe za geometrijo, ki so prevedeni in bomo poštevanko spoznavali že v začetku tretjega razreda in tudi v slovenščino in tako mlajši učenci ne bi imeli težav pri jo utrjevali vse do konca razreda, za kar bomo uporabljali tudi razumevanju. V tretjem izobraževalnem obdobju vsaka učiteljica interaktivne spletne vaje. Seveda bomo učence tako začeli po svojih močeh razvija digitalne kompetence, kar smo navajati na obnašanje na spletu in jih opozarjati, kako pomembna ugotovile, da bi morale poenotiti in prevetriti. V tretjem je varnost na spletu in oblikovanje pozitivne digitalne identitete. izobraževalnem obdobju začno učenci uporabljati spletne učilnice, elektronsko pošto in nekatere programe za geometrijo in računanje, kar bi morali učenci začeti uporabljati že veliko prej in tako ne bi izgubljali časa s poučevanjem osnov programov ter uporabe računalnika v sedmem razredu. Skratka. Pri hitrem pregledu smo ugotovile, da lahko veliko še dodamo in razvijemo pri samem pouku matematike. Osredotočiti pa se moramo tako na splošne digitalne kompetence kot tudi na tiste, ki podpirajo sam pouk matematike. Seveda pa ne smemo pozabiti na matematiko samo. 3 RAZVOJ KOMPETENC PRI MATEMATIKI NA OSNOVNI ŠOLI DRAGA KOBALA MARIBOR Po pregledu stanja na šoli smo pregledali učne načrte in izdelali tabelo razvoja digitalnih kompetenc pri pouku matematike. Odločili smo se, da moramo znanje iz usvojenih digitalnih Slika 55: Uporaba BEE-BOOTov pri pouku matematike kompetenc neprestano utrjevati, da jih učenci ponotranjijo in 3.2 Drugo vzgojno izobraževalno obdobje postanejo le-te del njihovega vsakdana. Odločili smo se, da razvoj kompetenc razdelimo po vzgojno-izobraževalnih V drugem vzgojno-izobraževalnem obdobju postane delo z BEE- obdobjih, znotraj le-teh pa še dodatno po razredih. Ker smo se BOOti večini učencem nezanimivo, kar nadgradimo z delom s zbrale učiteljice matematike po vertikali, smo vedele, kaj lahko tablicami. Počasi uvedemo koordinatni sistem, ki ga predstavimo od otrok na določeni stopnji razvoja pričakujemo. s pomočjo programa Geogebra, ki je brezplačen in deluje tudi na Ko smo pregledale učne načrte in stanje na šoli, smo se tablicah. Učence navajamo, da sledijo navodilom in razlagi na opredelile še na to, kaj lahko pri matematiki ponudimo in kakšne ekranu, tako poleg digitalnih kompetenc razvijamo tudi bralno kompetence želimo, da ima učenec, ko našo šolo zapusti. pismenost, saj nam računalnik oziroma tablica pokaže in napiše, Raziskale smo programe, ki jih uporabljamo, pregledale, kaj bi kaj smo narobe naredili. V drugem vzgojno-izobraževalnem lahko začele uporabljati že prej in s katerimi programi ter obdobju slike v slikovnih programih zamenjajo matematični metodami bi lahko tudi nadaljevale. Nastala je tabela razvoja programi za geometrijo. Učenci, ki so spretnejši, narišejo v digitalnih kompetenc pri pouku matematike po vertikali na programu za Geogebro Pitagorejsko drevo (slika 2), ostali pa Osnovni šoli Draga Kobala Maribor. sliko, kjer uporabijo tako večkotnike, kote, krog in dele kroga. 3.1 Prvo vzgojno izobraževalno obdobje V prvem vzgojno-izobraževalnem obdobju, bomo zraven prostorskih predstav, ki jih razvijamo s pomočjo BEE-BOOTov (slika 1), razvijali še uporabo tablic, s pomočjo katerih bomo učence navajali na kalkulator in osnovne računske operacije. Veliko časa bomo namenili tudi medpredmetnim povezavam. V računalniški učilnici bomo s pomočjo slikarskih programov v sklopu matematike v povezavi z likovno umetnostjo ustvarjali s pomočjo likov, števil, simbolov,. . Prav tako bomo spoznali programe za urejanje besedila, kjer bomo matematiko povezali s slovenščino in se naučili pravilnih zapisov števil, datumov, denarja, ure in drugih. Pri matematiki je potrebno veliko vaje, tako smo se odločili, da bomo nekaj ur matematike porabili tudi za preverjanje in utrjevanje znanja iz osnovnih računskih operacij. Le-teh pa ne bomo utrjevali samo na papirju, ampak Slika 56: Primer Pitagorejskega drevesa Na tak način učenci spoznajo osnovno delovanje programa. bomo uporabljali IKT, s katero lahko v kratkem času delo Pri računanju utrjujejo računske operacije in spretnosti s diferenciramo in hitrost utrjevanja prilagodimo vsakemu pomočjo spletne strani Lefo lefo [5], ki omogoča, da učenci med posamezniku. Ob koncu prvega izobraževalnega obdobja bomo seboj tudi tekmujejo in si izmenjujejo dosežene rezultate. Ker 590 učenci dobijo svojo digitalno identiteto v začetku drugega vzgojno- izobraževalnega obdobja, le-to uporabljajo tudi pri pouku matematike tako, da učence navajamo na uporabo spletnih učilnic, kjer jih na začetku navajamo na gesla in jih opozarjamo na pomembnost gesla ter skrbno varovanje le-teh. Predstavimo jim, zakaj mora biti geslo zapleteno in poučimo jih, kaj se lahko zgodi, če geslo pride v napačne roke. Veliko uporabljamo spletno stran safe.si, ki na prikupen in poučen način prikazuje različne situacije, ki se lahko zgodijo [4]. V spletni učilnici dobivajo učenci kratka navodila, ki jim morajo slediti. Izdelali smo kvize in učence smo naučili oddajati naloge preko spletne učilnice. Zaenkrat je dovolj, če učenci Slika 57: Delo s preglednicami oddajo le slike, Wordove dokumente ali Excelove datoteke. Proti Ker so učenci v tretjem izobraževalnem obdobju že zelo koncu drugega izobraževalnega obdobja, jih navadimo, da pri spretni z uporabo IKT, rešujejo že zapletene primere s oddajanju nalog le- te oddajo v pdf obliki. V sredini drugega podobnostjo, kot so izračunati višino šole, višino drevesa pred izobraževalnega obdobja učence začnemo navajati tudi na delo s šolo, torej izračunati, izmeriti višino predmetov, ki so višji od tabelami. Tako spoznajo Microsoftova orodja Excel in Oblak učencev. Učenci samostojno povežejo znanje iz matematike z 365, do katerih imajo vsi učenci naše šole brezplačen dostop. realno situacijo [2]. Hitro ugotovijo, da si lahko pomagajo z Pokažemo jim tudi druga brezplačna orodja za delo s znanjem iz podobnosti. Zbrali so potrebne podatke, merili sence preglednicami, kot so OpenOffice, LibreOffice in druge. Pri predmetov, katerim so znali izmeriti višino in predmetov, matematiki jih navajamo tudi na pošiljanje spletne pošte, kar bi katerim višino so želeli izračunati. Skupaj ugotovimo, da bi lahko se naj naučili pri slovenščini v četrtem razredu, a kot velja, vaja predmete poslikali in v računalniški učilnici izračunali njihove dela mojstra. Neprestano učence opozarjamo na zapis števil, višine. Kar smo tudi naredili. Tako učencem pri matematiki v ta datumov, časa in drugih matematičnih znakov. Ker imajo vsi namen pokažemo tudi nekaj osnov fotografiranja in jih učenci naše šole od četrtega razreda naprej dostop do Oblaka 365, opozorimo na to, kaj je dobra fotografija. Naučimo se fotografijo jih navajamo tudi na delo s tem orodjem [3]. Opozorimo jih, da uporabiti kot pripomoček za izračun višine šole. Naučimo se ni Microsoft edini ponudnik takšnih orodij, da lahko izbirajo tudi prenesti fotografije iz tablice ali telefona na računalnik, kar nam druge. Učence smo opozorili, da bomo pri matematiki uporabljali omogoča, da lahko merimo razdalje na fotografiji (slika 4) in Oblak 365, ker nam je prosto dostopen in ima šola tako ugotovimo dejanske višine objektov. Seveda pa znova administratorske pravice. utrjujemo znanje iz preglednic, saj vse izračune računamo s V preglednicah učenci spoznajo različne diagrame za prikaz pomočjo računalnika. podatkov, samostojno izdelajo preiskovalno nalogo, kjer naučeno znanje tudi uporabijo na dejanskem modelu. Navajamo jih na zapis decimalnega števila in ulomka. 3.3 Tretje vzgojno-izobraževalno obdobje Učence še vedno opozarjamo na njihovo digitalno identiteto, jih navajamo na gesla in rokovanje z njimi. Vseskozi skrbimo za varnost na spletu in učence na to tudi opozarjamo [1]. V tretjem izobraževalnem obdobju učence učimo kritično oceniti najdene informacije. Znanje uporabe IKT učenci tukaj utrjujejo in poglabljajo. Tako nadaljujemo z delom in prikazi v Geogebri, kjer učenci raziskujejo različne medsebojne odnose osnovnih geometrijskih pojmov. Učence naučimo s pomočjo Slika 58: Merjenje v Wordu tehnologije izmeriti kote, označiti kote. Sami hitro ugotovijo, da Ne pozabimo pa tudi na uporabo računala. Pred leti smo lahko kote različno označimo in kako pomemben je vrstni red ugotovili, da so učenci zapuščali našo šolo in niso znali zapisa točk, ker jim enkrat prikaže izbočeni in drugič udrti kot. uporabljati računala. Zato jih skozi vsa vzgojno-izobraževalna Učence zraven uporabe IKT navajamo tudi na samostojno delo obdobja navajamo tudi na uporabo računala. V prvem in drugem in raziskovanje. Tukaj jim pokažemo tudi druga orodja za vzgojno-izobraževalnem obdobju učence s pomočjo tablic geometrijo, kot so Desmos, RiŠ, Dr. Geo in druga. navajamo na vrstni red računskih operacij. Ob koncu drugega Nadaljujemo delo s preglednicami, kjer spoznamo zraven izobraževalnega obdobja imajo učenci svoja računala in jih pri osnovnih računskih operacij in različnih zapisov števil tudi matematiki navajamo na uporabo le-teh, saj vsi dobro vemo, da formule, kot so sum, if, sumif, count, sqrt in druge (Slika 3). računala računajo pravilno le, če jim pravilno vnesemo račun. Učenci znajo računati s potencami, spoznajo različne ukaze iz statistike, kot so modus, aritmetična sredina, mediana. Nadgradimo tudi znanje risanja diagramov. 4 ZAKLJUČEK Verjamemo, da sedaj učenci našo šolo zapuščajo polni znanja tudi uporabe IKT. Pri matematiki se bomo še naprej trudili, da bomo po celi vertikali nadgrajevali znanje uporabe IKT 591 predvsem matematičnih vsebin in aplikacij. S svojim delom LITERATURA IN VIRI bomo nadaljevali. Razvijali bomo IKT veščine od prvega razreda [1] do devetega. Po posameznih triadah bomo utrjevali in Ala-Mutka K. 2011. Mapping Digital Competence: Towards a Conceptual Understanding. Expo. c/ Inca nadgrajevali znanje iz IKT, saj želimo, da bodo ob koncu šolanja Garcilaso Spain. naši učenci digitalno pismeni. Zato je pomembno, da učencem DOI=ftp://jrc.es/pub/EURdoc/JRC67075_TN.pdf predstavimo, kako pomembno je, da dobro obvladamo IKT, saj [2] Različni avtorji. 2011. Učni načrt za matematiko v osnovni nam le-ta ob pravilni uporabi veliko pripomore in olajša delo. šoli. Ministrstvo za izobraževanje, znanost in šport, Zavod Menimo, da lahko še veliko naredimo na področju uporabe IKT, RS za šolstvo. vendar le z malimi koraki nam bo uspelo. DOI=https://www.gov.si/assets/ministrstva/MIZS/Dokume nti/Osnovna-sola/Ucni-nacrti/obvezni/UN_matematika.pdf [3] Računalniški program Oblak 365, DOI= https://o365.arnes.si/ [4] Različni avtorji, Safe.si, DOI= https://safe.si/ [5] A. Divjak, Spletna stran Lefo lefo, DOI= http://sl.lefo.net/ 592 Aplikacije in metode dela za poučevanje angleškega jezika na daljavo Apps and pedagogical methods for teaching English language online Lea Opravž Ostrelič Osnovna šola XIV. divizije Senovo Trg XIV divizije 3 8281 Senovo, Slovenija leaopravz@gmail.com POVZETEK trgovine, letalstva, pri meddržavnih dogovarjanjih itn. ter omogoča najširši dostop do podatkov [1]. V članku so predstavljeni programi in aplikacije, ki jih Eden izmed pomembnejših ciljev, katerim sledimo učitelji uporabljamo pri poučevanju angleščine na daljavo na naši angleškega jezika, je, da bi naši učenci postali samostojni, osnovni šoli. V času izolacije smo uporabljali veliko različnih suvereni in učinkoviti uporabniki angleškega jezika, ki bi bili aplikacij, nato pa smo s pomočjo anket in pogovorov z učenci in sposobni samozavestno komunicirati z ostalimi govorci učitelji izbrali pet najboljših digitalnih orodij, ki so se izkazali za angleščine in bi imeli funkcionalno znanje jezika. V osnovni šoli najbolj uspešne. S tovrstnim delom nam je uspelo dvigniti razvijamo te zmožnosti učencev preko poslušanja in slušnega motivacijo učencev za učenje tujega jezika, posledično se je razumevanja, govornega sporazumevanja in govornega dvignil tudi nivo znanja angleškega jezika. sporočanja, branja in bralnega razumevanja, pisanja, pisnega KLJUČNE BESEDE sporazumevanja in pisnega sporočanja. Za vse te cilje je značilno, da so enako pomembni, da se med seboj prepletajo, so soodvisni Aplikacije, programi, IKT, angleščina, osnovna šola drug od drugega in se pogosto razvijajo integrirano. ABSTRACT Z učenjem jezika učenci ne razvijajo samo svoje znanje tujega jezika, ampak razvijajo tudi sporazumevalno kulturo in In this article are presented different computer programs and razumevanje medkulturnosti, razvijajo lastno večjezičnost in apps that we’re using for online English language teaching in our jezikovno zavest. Jezike (tuje in materin jezik) primerjajo med primary school. During the isolation, we used many different seboj in s tem razvijajo svojo zmožnost analitičnega mišljenja. apps. During and after the isolation we used surveys and Razvijajo tudi svojo sposobnost za vseživljenjsko učenje tujih interviews both with students and teachers and we selected top jezikov, kajti zmožnost za sporazumevanje zunaj okvira five digital tools that proved to be the most successful. With this materinščine je eden izmed temeljnih izobraževalnih ciljev v kind of work, we succeeded in raising the levels of motivation of osnovni šoli. our pupils for learning English language. As a result, the level of V času epidemije in pouka na daljavo smo bili vsi primorani English language knowledge, has also risen. uporabljati moderne medije oz. IKT. Če si po teoriji Edgarda Dala učenci zapomnijo 10 % tistega, kar preberejo, in 90 % KEYWORDS tistega, kar doživijo, potem lahko delo z digitalnimi mediji Applications, computer programs, ICT, English language, pomeni nov mejnik učenja s pomočjo IKT-ja [3]. S pomočjo primary school računalnika, tablice ali pametnega telefona lahko učenci obiščejo kraje, ki jih praktično sami ne bi mogli videti ali doživeti. Sam pouk v klasični ali virtualni učilnici je lahko kakovostnejši in bolj 1 UVOD učinkovit ob pametni uporabi modernih tehnologij. V Sloveniji je angleščina za večino otrok tuj jezik, s katerim se prvič srečajo že v prvem razredu osnovne šole. Nekateri otroci se z njim srečajo že v predšolskem obdobju, večina pa v prvi 2 PROGRAMI IN APLIKACIJE PRIMERNI triadi osnovne šole. Angleški jezik je pomemben, saj je globalni ZA UPORABO PRI POUKU ANGLEŠČINE jezik, ki ga uporablja več tujih kot domačih govorcev in se NA DALJAVO uporablja pri sporazumevanju na področju znanosti, tehnologije, Čeprav so bili naši učenci vajeni dela z IKT, so se vseeno pojavile težave pri učencih in pri njihovi uporabi računalnika ter novih aplikacij. Težave so bile na več nivojih: od preslabih računalnikov do časovne omejitve časa preživetega za Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed računalnikom (več šoloobveznih otrok in starši, ki delajo od for profit or commercial advantage and that copies bear this notice and the full doma), do težav zaradi aplikacij v angleškem jeziku. Z učenci citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). smo težave reševali sproti, pogosto skupaj. Na voljo sem jim bila Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia preko družabnih omrežij in preko telefona. Če se je pojavila © 2020 Copyright held by the owner/author(s). 593 težava, katero ni znala rešiti večina učencev, sem s pomočjo aplikacije Screencastify posnela posnetek z razlago celotnega postopka in ga delila z učenci. Ta metoda pomoči se je izkazala za najbolj zanesljivo. Pogosto se je zgodilo, da smo določeno zapleteno aplikacijo enostavno nehali uporabljati in jo nadomestili s podobno, manj zapleteno. Tukaj predstavljam pet aplikacij, ki so se nam zdele najbolj primerne za uporabo pri pouku angleščine na daljavo in ki so bile po anketi izvedeni med našimi učenci, njim najbolj uporabne, enostavne in zanimive. 2.1 Flipgrid Slika 2: Flipgrid (vir: Flipgrid [Slika 1] je uporabna aplikacija, s katero na zabaven https://www.mrspriestleyict.com/blog/flipgrid#/ ) način spodbujamo govorno sporočanje naših učencev. Uporabljamo jo lahko na telefonu, tablici ali računalniku, 2.2 Wakelet pomembno je le, da imamo kamero, mikrofon in zvočnik. Učitelj Naslednja aplikacija, ki krepi digitalne kompetence učencev in je pripravi učno okolje, kjer lahko učenci prispevajo svoje posnetke primerna tako za poučevanje na daljavo kot za delo v razredu, je (npr. refleksija, diskusija, evalvacija …). Orodje ima pester Wakelet [Slika 3] . Wakelet je brezplačna aplikacija za nabor funkcionalnosti in je brezplačno. Učitelj nalogo z učenci shranjevanje, organiziranje in deljenje vsebin s celega spleta. Z deli na različne načine (s QR kodo, dostop preko maila, njo lahko shranimo katero koli vsebino s spleta, naj bo to vpis uporabnikov). Učenci se prijavijo v mrežo, pogledajo najljubša pesem, članek, videoposnetek, blog, tweet ali celo učiteljev videoposnetek z navodili in na zelo enostaven način Facebook objava. Celoten proces shranjevanja in organizacije oddajo svoj prispevek v mrežo (grid) [Slika 2]. Posnetek gradiva je zelo enostaven. Uporabljali smo ga z učenci tretje pogledajo, lahko ga tudi obdelajo (si dodajo dodatke, skrijejo triade. Tudi ta aplikacija se lahko uporablja na različnih obraz, spremenijo ozadje) in ko so zadovoljni z njim, ga objavijo. napravah (tablica, računalnik pametni telefon). Lahko si tudi ogledajo posnetke svojih sošolcev, lahko jih video Pri pouku na daljavo smo Wakelet uporabljali na različne komentirajo, se odzovejo nanje z emojiji, lahko jih delijo na načine: različnih socialnih omrežjih. Posnetke v mreži vidi le tisti, ki je bil v mrežo povabljen oz. ima kodo za dostop. Po naših izkušnjah - za samostojno delo, ko so učenci pripravljali določen je bila aplikacija Flipgrid najbolj všeč učencem druge triade. Pri izdelek: npr. plakat ali predstavitev teme za govorni učencih prve triade smo z uporabo te aplikacije naložili preveč nastop. Učenci so Wakelet uporabljali predvsem v dela že tako obremenjenim staršem, tako da smo se tega poslužili začetnem delu, kjer so s pomočjo spleta iskali le enkrat in dobili le skromen odziv. Nekaj staršev nam je pisalo, informacije, povezane z dano temo. V začetni fazi so da imajo velike težave z aplikacijo prav zaradi tega, ker je v običajno svojo zbirko delili tudi z nami, svojimi angleščini. Pri učencih tretje triade ni bilo nikakršnih tehničnih učitelji, tako da smo lahko videli, kako nastaja izdelek, težav ali težav zaradi tega, ker je aplikacija v angleškem jeziku. kakšno gradivo zbirajo učenci in jih po potrebi Največja težava pri njih je bila v tem, da niso želeli, da jih gleda usmerjali in jim pomagali pri izboru pravega (in verodostojnega) gradiva. V tem delu so se učenci kdo drug. Naloge v Flipgridu so pri njih zaživele šele, ko smo veliko naučili tudi o varnosti na internetu ter o spletni jim dovolili, da naredijo posnetek, pri katerem je nujno, da etiki. govorijo, ni pa nujno, da takrat snemajo sebe. Največji uspeh je - pri skupinskem, sodelovalnem delu, kjer je skupina aplikacija Flipgrid požela pri učencih druge triade. Aplikacijo so učencev morala izdelati nek skupni izdelek oz. uspešno uporabili z manjšo pomočjo staršev, snemanje svojega predstavitev, ampak dela niso smeli opraviti skupaj video odgovora in komentarjev so vzeli zelo resno in se nanj tudi zaradi prepovedi druženja. To je bil učencem najljubši dobro pripravili. Ugotovili smo, da lahko to aplikacijo v drugi del dela s to aplikacijo, kajti ugotovili so, kako hitro triadi tudi uspešno uporabimo za ustno ocenjevanje znanja. lahko zberejo gradivo, če pri tem sodelujejo in se Kot učiteljici mi je bilo zelo všeč, ker sem lahko vsakemu dopolnjujejo. Všeč jim je bilo tudi, ker je Wakelet posameznemu učencu preko aplikacije podala povratno nadomestil več orodij in aplikacij, ki so jih morali uporabljati včasih, da so opravili enako delo. informacijo o njegovem posnetku. - za navodila učitelja ali pri predstavitvi določene teme. Sama sem uporabila to aplikacijo, kadar sem učencem predstavila novo orodje. Svoja navodila sem pripravila z aplikacijo Wakelet, v katero sem poleg samih navodil vključila tudi slikovno in video gradivo o tem orodju, ki sem ga našla na spletu. Pogosto sem Wakelet uporabila kot uvodno motivacijo v novo temo. Tako sem učencem predstavila temo, npr. nutrition (prehrana) [Slika 4] in preko Wakelet- a sem jim predstavila prehransko piramido, animiran filmček iz You Tuba o zdravi prehrani, za konec sem jim dodala Slika 1: Flipgrid logo (vir: še povezavo do spletne strani z vprašalnikom, ki so ga https://blog.flipgrid.com/news/2017/6/13/10ways ) 594 rešili o svoji prehrani in ki nam je potem služil kot izkazalo za zelo primerno pri učencih prve triade, ki še iztočnica za nadaljnjo obravnavo snovi. niso pretirano dobri bralci. Veliko staršev mi je bilo zelo hvaležnih, kajti na ta način sem jaz otrokom razložila, kaj morajo narediti, na kaj morajo biti pozorni in kako naj rešijo katero nalogo in jih na ta način razbremenila. - prikaz zapletenih postopkov uporabe novih aplikacij ali kakšnega drugega postopka kot npr: kako oddati Slika 3: Wakelet logo (vir: nalogo v googlovi učilnici, ali: kako posneti posnetek http://www.kathleenamorris.com/2018/08/27/wakelet/) v aplikaciji Flipgrid. Čeprav sta si obe aplikaciji zelo podobni in sta zelo enostavni Vidim, da je ta aplikacija naredila dober vtis, kajti kar nekaj za uporabo, je med njima še vedno nekaj razlik. Tu bom zapisala učencev mi je po zaključenem delu pouka na daljavo povedalo, le nekaj razlik, ki so mene prepričale v pogostejšo uporabo kako pogosto jo uporabljajo tudi pri stvareh, ki niso povezane s aplikacije Loom: šolo, kot na primer seznam filmov, ki si jih morajo ogledati, - Dolžina videoposnetkov: Screencastify dovoli seznam dobrih računalniških iger, ki jih morajo odigrati, zbiranje brezplačno snemanje le 5 minutne videoposnetke (v informacij o nadaljevanju šolanja v srednji šoli itd. Všeč jim je, času korone so ta čas sprostili na neomejeno dolge ker imajo s to aplikacijo vse željene informacije na enem mestu. videoposnetke), aplikacija Loom ima omejitev 25 Najbolj jim je všeč, ker s to aplikacijo na stotine internetnih minut, kar je več kot dovolj za uporabo poučevanja na povezav spremeniš v eno samo. daljavo v osnovni šoli. - Shranjevanje videoposnetkov: Screencastify shranjuje posnetke na Google drive in posledica tega je, da se količina brezplačnega prostora na google računu zelo hitro napolni, Loom pa shranjuje posnetke na svojo spletno stran in učitelj deli z učenci povezavo na njihovo stran, če seveda ne objavi svojega posnetka na You Tubu. - Posnetek spletne kamere računalnika lahko pri Screencastify le premikamo po zaslonu, pri aplikaciji Loom ga lahko spreminjamo med samim snemanjem. Lahko ga povečamo na celoten zaslon, poljubno pomanjšamo ali celo odstranimo, odvisno kaj v Slika 4: Wakelet zbirke (osebni arhiv) določenem trenutku potrebujemo. - Boljša zaščita objavljenih posnetkov. Pri obeh 2.3 Screencastify in Loom aplikacijah deliš posnetek preko povezave, ampak Obe aplikaciji sta si zelo podobni in sta bili v času dela na daljavo aplikacija Loom omogoči, da ta posnetek še dodatno za nas nepogrešljivi. Uporabljali smo ju za snemanje zaslona, zaščitimo z geslom. zraven pa lahko snemata tudi zvok in video preko spletne - Komentiranje posnetkov in štetje ogledov. Če kamere. Res je, da smo navodila in razlage pogosto podajali videoposnetka, narejenega s Screencastify, ne objaviš učencem v tekstovni obliki, pogosto pa smo se vsi znašli v na You Tubu, ga gledalci ne morejo komentirati in/ali situaciji, kjer smo učencem morali enostavno stvari razložiti se na njega odzvati z emoji. Pri posnetkih aplikacije verbalno, ob beli tabli in z vso mimiko telesa, ki jo uporabljamo Loom lahko posnetke komentiramo in se nanje pri pouku. odzivamo z emojiji. Screencastify in Loom [Slika 5] sta brezplačni aplikaciji, pri - Če želite uporabljati napredne funkcije obeh aplikacij katerih se mora učitelj registrirati, učenec pa le klikne na in snemati neomejeno število posnetkov, je potrebno povezavo in že uživa v učiteljevem posnetku. Obe aplikaciji za Screencastify plačati 29 $ na leto, pri aplikaciji zajemata zaslon, istočasno snemata video, uporabnik pa po želji Loom je profesionalna verzija doživljenjsko vklopi tudi snemanje samega sebe. Pri svojih urah sem ga brezplačna za učitelje in študente. pogosto uporabljala na tri načine: - Moramo omeniti še eno razliko med tema dvema - razlaga nove snovi. Po anketi, ki sem jo izvedla med aplikacijama, ki je bolj v prid aplikaciji Screencastify. svojimi učenci po končanem poučevanju na daljavo, je Uporaba oz. snemanje posnetkov s Screencastify lahko bilo veliko učencem zelo všeč, ko sem poslala razlago poteka tudi v primeru, ko smo brez internetne snovi v obliki videa in kot zapis v wordovem povezave. Za snemanje z aplikacijo Loom pa vedno dokumentu. Moramo vedeti, da so naši učenci različni potrebujemo internetno povezavo. učni tipi, tako da enim bolj odgovarja poslušanje, drugim pa branje nove učne snovi. - podajanje navodil za delo. Pogosto se je zgodilo, da je bilo enostavno preveč navodil, da bi jih zapisala, zato sem se pogosto odločila in navodila posnela. To se je 595 odgovarjajo na dana vprašanja, rešujejo naloge kjer morajo dopolniti povedi ter naloge iskanja parov, ki je tudi zelo primerna pri poučevanju tujega jezika. Učencem zanimiva aktivnost je tudi opazovanje in učenje z gledanjem 3D predmetov. Učenci se lahko z učiteljem preko te aplikacije odpravijo na virtualni izlet v skoraj 100 različnih krajev po svetu, kjer si ogledajo njihove zgodovinske, kulturne in turistične znamenitosti. Ko učitelj pripravi učno uro, ima dve možnosti, kako jo deli z učenci: - ob pritisku na gumb LIVE deli uro v živo s svojimi Slika 5: Logotipa aplikacij Screencastify in Loom (vir: učenci in lahko v realnem času spremlja delo in https://www.saashub.com/compare-screencastify-vs-loom-for- napredek vsakega učenca posebej. Tak način smo desktop večkrat uporabili pri delu z Nearpod-om v razredu. - ob pritisku na gumb STUDENT PACED LESSON vsak učenec predela pripravljeno učno uro, ko si sam to želi oz. ko ima čas in s svojim tempom. Tudi pri tem 2.4 Nearpod načinu učitelj dobi v realnem času povratne Nearpod [Slika 6] je aplikacija oz. spletna platforma, ki zaradi informacije o delu vsakega učenca posebej. Ob poteku svojih mnogih možnosti uporabe spominja na neke vrste časovnega okvirja, namenjenega določeni učni uri, dobi učitelj poročilo o napredku in dosežkih celega enostavno spletno učilnico. Tudi ta aplikacija je za učitelja in razreda in vsakega individualnega učenca. Ta način učence brezplačna, potrebna je le registracija. Uporablja se lahko smo najpogosteje uporabljali v času učenja na daljavo. na različnih napravah in je primerna za okolje Windows, Ios in Android. Aplikacija Nearpod je bila najbolj zanimiva mojim učencem druge triade. Aplikacijo so poznali že iz časa pred poukom na daljavo, tako da nam ni bilo potrebno vložiti veliko časa in truda v to, da bi učence naučili uporabo novega orodja. Učenci so na zelo zabaven način spoznavali novo snov in utrjevali besedišče, mi učitelji pa smo v vsakem trenutku natančno vedeli kakšno je znanje naših učencev, s katero snovjo imajo še težave in kaj bo potrebno še utrditi. Z aplikacijo Nearpod je bilo tudi enostavno diferencirati ure in dodati še nekaj dodatnih, bolj zahtevnih nalog za tiste učence, ki zmorejo več. Nearpod je bila ena izmed najbolj uporabnih aplikacij pri našem delu na daljavo, saj smo z njo z lahkoto sestavili celo Slika 6: Nearpod logo (vir: https://nearpod.com/) šolsko uro z različnimi dejavnostmi in aktivnostmi. Zaradi Aplikacija je namenjena predstavitvi nove snovi ter prav tako omogočenega snemanja avdio posnetkov sem na ta način lahko spremljanju in preverjanju znanja učencev. Učitelj lahko pri na začetku ure učence pozdravila in jim dala krajša navodila o pripravi svoje ure uporabi že ustvarjene učne ure, ki jih vidi v uri, ki smo jo izvedli ta dan, nato pa so s svojim tempom predelali knjižnici, le te lahko predela in spremeni, tako da ustrezajo njemu učno snov in preverili svoje znanje. Na koncu so tako učenci kot in njegovim učencem, lahko pa seveda sestavi tudi svoje lastne jaz dobili povratno informacijo o pravkar izvedenem delu. učne ure. Že sestavljene ure so kvalitetne in razdeljene po predmetih, edina težava je lahko le to, da so vse v angleškem jeziku. Za nas, angliste, to seveda ni težava. Učitelj lahko sestavi učno uro v aplikaciji Nearpod, če pa ima že sestavljeno predstavitev v Powerpointu, PDF-ju, Google slides ali Sway-u, jo lahko naloži v Nearpod in jo spremeni v interaktivno Nearpod učno uro[Slika 7] . Sama izdelava učne ure v Nearpodu je enostavna. Podobno je delu v Power Pointu, le da lahko tu razen gradiva, ki ga predstavljamo učencem (besedilo, fotografije, avdio in videoposnetki ter povezave do gradiva na spletu) dodajamo tudi različne aktivnosti, v katerih Slika 7: Ustvarjanje predstavitve (vir: bodo sodelovali naši učenci. V svojo predstavitev lahko https://mrspearsall.com/category/ed-tech/nearpod/) vključimo tudi različne kvize, ankete, aktivnosti, kjer lahko učenci odgovorijo z risanjem (odlična aktivnost za preverjanje 2.5 EdPuzzle besedišča), lahko naložimo delovni list, ki ga že imamo Aplikacija EdPuzzle [Slika 8] služi kot orodje, s katerim lahko sestavljenega in učenci preko Nearpoda pišejo nanj in ga rešijo, video posnetek iz You Tuba ali podobnih spletnih strani kakor bi v živo reševali delovni list v šoli. Lahko tudi opremimo s komentarji in vprašanji, na katere učenci 596 odgovarjajo, in tako pripravimo interaktivni video. Odgovori reševanje. Prednost te aplikacije je tudi povratna informacija učencev se zabeležijo in so lahko učitelju v pomoč pri učitelju o uspešnosti učencev pri reševanju naloge. Učitelj ima spremljanju napredka in razumevanja. Okolje je primerno za možnost pogledati posamezen posnetek, kako uspešno ga je rešil preverjanje razumevanja snovi ali za podajanje teoretičnih celoten razred, ima pa tudi možnost povratne informacije o vsebin. posameznem učencu (ali je v celoti pogledal videoposnetek, katere naloge je rešil in kako uspešno). Pri brezplačni verziji aplikacije je posameznemu učitelju na voljo 30 videoposnetkov. Če nam to ni dovolj, je na voljo plačljiva verzija, kjer je število posnetkov neomejeno. Slika 8: EdPuzzle logo (vir: 3 ZAKLJUČEK https://edtechawesomeness.com/2017/08/15/cool-tools- Čas poučevanja na daljavo zaradi korona virusa pa nas je vse edpuzzle/ prisilil, da smo v zelo kratkem času usvojili nove metode poučevanja, komuniciranja z učenci ter preverjanja znanja. Sama Običajno smo ga uporabljali tako, da smo pred gledanjem sem se naučila uporabljati vsa tista orodja za katera sem vedela, videoposnetka za učence posneli kratka avdio navodila, v katerih da obstajajo, a so se mi zdela prezahtevna za uporabo. Seveda ni smo jim razložili, kakšen je cilj gledanja tega posnetka ter jim bilo vse enostavno in zabavno. V poučevanje na daljavo je moral dali pomembnejša navodila za delo. Med samim gledanjem smo vsak učitelj vložiti ogromno svojega časa in vsakodnevno iskati jim dodali odseke, ko se je posnetek ustavil (po kakšnem nove možnosti podajanja snovi, preverjanja znanja in še posebej pomembnejšem odseku posnetka) in je sledilo nekaj vprašanj v motiviranja učencev, ki si pogosto gledali na čas pouka na povezavi s pogledano vsebino oz. preverjanje razumevanja. daljavo kot na čas počitnic. Vprašanja so lahko izbirnega ali odprtega tipa. Dokler učenec ne Tudi učencem ni bilo enostavno, kajti nekateri v treh mesecih odgovori na vsa vprašanja, ne more nadaljevati z ogledom pouka na daljavo nikakor niso uspeli preklopiti na tovrsten način posnetka. Vedno so dobili tudi nekaj vprašanj odprtega tipa ob dela. Vendar iz svojih izkušenj lahko trdim, da je tudi učencem koncu gledanja posnetka. Takoj ko učenec konča z nalogo, dobi tak način dela prinesel neko dodano vrednost. Vsakodnevno sem delno povratno informacijo, končno informacijo pa dobi, ko bila v stiku z večino svojih učencev in pri učencih višjih razredov učitelj preveri vse učenčeve odgovore [Slika 9]. Učitelj ima pri sem opazila, da so postali bolj samostojni, bolj organizirani in urejanju videoposnetka možnost rezanja, tako da lahko dele, ki bolj samozavestni, saj so ugotovili, da z »majhno« pomočjo nas za učence niso pomembni, enostavno izreže iz videoposnetka. učiteljev zmorejo premikati tudi ogromne skale. Pa zaključimo z izjavo Alberta Einsteina: »Edini vir znanja so izkušnje« [2]. Sedaj smo vsi bogatejši za izkušnjo z pouka na daljavo. Videli smo, kaj zmoremo in česa smo sposobni s pomočjo modernih medijev. Moderni mediji, tehnologije in izobraževalne aplikacije imajo to moč, da skozi zanimive vsebine pri učencih (ob pravilni uporabi) povečajo motiviranost, raven sodelovanja pri pouku, spodbujajo njihovo predstavo in razvijajo kreativnost. Ker je pri uporabi take tehnologije vključenih več čutil, je tudi raven pomnjenja učne snovi veliko večja kot pri klasičnemu pouku. LITERATURA [1] Andrin, A., Eržen, V., Kogoj, B., Lesničar, B. 2016. Učni načrt za angleščino. Zavod Republike Slovenije za šolstvo, Slika 9: Poročilo za učitelja o tem, kako uspešni so bili učenci Pridobljeno s: pri določeni nalogi (vir: https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/Os https://www.researchgate.net/figure/Sample-image- novna-sola/Ucni-nacrti/obvezni/UN_anglescina.pdf showing-the-reports-page-generated-by-Edpuzzle-for- [2] Class VR. 2017. White paper: A Guide To AR & VR In answers-given-to_fig4_324562565 Education. Pridobljeno s: http://www.classvr.com/virtual- reality-downloads/. Učitelj lahko aplikacijo EdPuzzle integrira v svojo Google učilnico, lahko pa le objavi povezavo do te aktivnosti. Določimo [3] Dale, E. 1969. Audiovisual methods in teaching. (str. 37 – lahko tudi, od kdaj do kdaj je naloga na voljo učencem za 38). New York. Dryden Press. 597 Razvijanje veščin 21. stoletja pri medpredmetni povezavi fizike z matematiko, informatiko in športno vzgojo Developing 21st century skil s in the cross-curricular connection of physics with mathematics, informatics and physical education Silvestar Ovčar I. gimnazija v Celju Kajuhova ulica 2 3000 Celje, Slovenija silvestar.ovcar@guest.arnes.si POVZETEK they are the basis for a successful career path of future generations. New knowledge and technological development Vsak napredek skozi zgodovino je povezan s pridobivanjem also create new professions or jobs. This means that we have to novih znanj, ki pa s časom naraščajo. Posledično za uspeh educate students so they can pursue professions that for now do posameznika in družbe več ni dovolj samo to, da nekdo pozna not even exist. As a result, good knowledge of a particular veliko vsebin na določenem strokovnem področju, ampak hkrati content will not be enough for their successful career, as postaja vse pomembnejše tudi razvijanje t. i. veščin 21. stoletja. mastering the previously mentioned skills is becoming just as To so: kritično mišljenje, ustvarjalnost, komunikacija, important as the knowledge of the content. The latter will enable sodelovanje, opazovanje itn. V članku na primeru medpredmetne that they will be flexible enough and that they will effectively be povezave ponazarjam, kako lahko v šoli zgoraj omenjene veščine able to adapt new demands in the society and the economy. The medpredmetno razvijamo, saj so te osnova za uspešno karierno basic purpose of this cross-curricular link is to develop 21st pot prihajajočih generacij. Nova znanja in tehnološki razvoj century skills for better learning and future career success of ustvarjajo tudi nove poklice. Dijake moramo torej izobraziti, da young people. bodo lahko opravljali poklice, ki jih še sploh ni. Za njihovo uspešno kariero zato ne bo dovolj zgolj dobro poznavanje vsebin, KEYWORDS saj postaja enako pomembno kot vsebinsko znanje še obvladovanje prej omenjenih veščin. Slednje jim bodo 21st century skills, cross-curricular connections, ICT omogočile, da bodo dovolj fleksibilni in se bodo zmogli učinkovito prilagoditi novim zahtevam v družbi in gospodarstvu. 1 UVOD Osnovni namen te medpredmetne povezave je razvijanje veščin 21. stoletja za boljšo učno in prihodnjo karierno mladih. Različne ravni tehnološkega razvoja zahtevajo različno usposobljeno osebje s širokim spektrom veščin. Iz dneva v dan KLJUČNE BESEDE naprednejša in visoko razvita tehnologija bo v bližnji prehodnosti Veščine 21. stoletja, medpredmetne povezave, IKT zahtevala veliko višji delež kadra s t. i. veščinami 21. stoletja oz. prečnimi veščinami [1]. Z optimizacijo, avtomatizacijo in ABSTRACT robotiko bo nadomeščenih veliko poklicev. Človek bo potreben Any progress through history is associated with the acquisition večinoma tam, kjer bo boljši od robotov. To bo na področjih, kjer of new knowledge that increases with time. Consequently, for the bodo potrebne kompetence 21. stoletja, kot so: reševanje success of not only the individual, but the society as well, it is kompleksnih problemov, čustvena inteligenca, sodelovanje, not enough for someone to know a lot of content in a certain komunikacija, ustvarjalnost, kritično razmišljanje, podjetnost in professional field. The development of the so-called 21st century domišljija [1]. V podporo razvijanju omenjenih veščin sem skills is becoming increasingly important at the same time. izvedel laboratorijsko vajo merjenja moči pri hoji/teku po Critical thinking, creativity, communication, collaboration, stopnicah, ki bo dijakom pomagala pri lažjem spoprijemanju z observation and similar skills fall into this category. In this article, novodobnimi izzivi. I will use the example of interdisciplinary connection to illustrate how we can develop the above-mentioned skills in school, as 2 INTEGRACIJA POUKA FIZIKE V DRUGE UČNE PREDMETE Šolski sistem ima šibko točko, saj s svojim vzgojno- Permission to make digital or hard copies of part or all of this work for personal or izobraževalnim procesom ne zmore slediti zahtevam sodobnega classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full česa, kjer se vedno znova srečujemo z novimi tehnološkimi citation on the first page. Copyrights for third-party components of this work must znanji in dognanji. Slednja zahtevajo sprotne prilagoditve in be honored. For all other uses, contact the owner/author(s). vedno nove veščine. Razvijanje veščin 21. stoletja zahteva Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). sistematičen pristop in veliko časa. Pri pouku fizike lahko po eni 598 strani na veliko načinov razvijamo takšne veščine, toda po drugi Teoretično znanje, ki smo ga ponovili in utrdili, je zajemalo strani smo zelo omejeni s časom, saj je snovi veliko, hkrati pa naslednje vsebine: prosti pad, delo, energije, izreki o energijah in imamo na voljo v gimnaziji samo dve učni uri fizike tedensko. moč. To je premalo, da bi lahko dijake ustrezno pripravili na njihove V sklopu učne ure smo z dijaki vnaprej načrtovali tudi: prihodnje izzive. Dijakov ne moremo izobraziti za nove poklice, • da bodo hodili in tekli po stopnicah pri ker jih še ne poznamo. Zelo učinkovito pa jim lahko pomagamo medpredmetni povezavi s športno vzgojo; pri razvoju veščin, ki bodo pri novih poklicih v prihodnosti • da bodo za dosego cilja potrebovali dodatno nepogrešljive, saj lahko te relativno dobro predvidimo. matematično znanje kotnih funkcij, ki ga bodo S svojimi dijaki sem izvedel laboratorijsko vajo merjenja osvojili v sklopu medpredmetne povezave z moči tako, da smo porabili samo eno učno uro fizike. Za uspešno matematiko; izvedbo laboratorijske vaje in hkratno razvijanje veščin smo • da bo pri delu vsak uporabljal svoj mobilni telefon, potrebovali še dodatnih pet šolskih ur. Teh nismo porabili pri ki mu bo služil kot štoparica, merilec naklona in pouku fizike, saj bi nam s tem zmanjkalo časa za obravnavo orodje za vnašanje meritev; preostale snovi. Rešitev sem videl v vzpostavitvi več • medpredmetnih povezav. Vajo smo tako izvedli pri eni učni uri da bodo meritve vnašali s pomočjo mobilnega telefona v svojo osebno Excelovo preglednico; fizike, eni učni uri matematike, dveh učnih urah informatike in dveh učnih urah športne vzgoje. Na ta način sem pridobil 5 učnih • da bodo za dosego ciljev potrebovali osnovna ur za razvijanje veščin 21. stoletja pri dijakih in obravnavo znanja iz Excela; fizikalnih vsebin. • da se bodo morali vpisati v Microsoftov račun Fizika je temeljna naravoslovna znanost, ki posega na več Office 365, kjer bo vsak našel svojo povezavo do znanstvenih področij. Pri informatiki se ukvarjajo s sodobno Excelove datoteke z vsemi tabelami za vnos tehnologijo, ki se uporablja tudi pri fiziki. Zakaj potem ne bi vsaj meritev in da enega dela fizike obravnavali pri informatiki? Prav tako fizika • se bodo v Office 365 vpisali pri pouku informatike, obravnava kinematiko in dinamiko, zakaj potemtakem ne bi vsaj kjer bodo osvojili tudi potrebna znanja iz Excela in del pouka fizike obravnavali pri pouku športne vzgoje? In ni ure • da si morajo na pametni telefon naložiti aplikacijo fizike, ko se ne bi ukvarjali tudi z matematiko, ki je osnovno za merjenje naklona (Bubble level Galaxy) [2]. orodje za opis naravnih pojavov. Zakaj potem ne bi kakšne ure fizike izvedli pri matematiki? Pogovoril sem se z nosilci omenjenih učnih predmetov, ki so moje argumente in predloge z veseljem sprejeli. Dodaten izziv pri izvedbi tako zastavljenega učnega procesa je fiksen urnik dijakov. To je pomenilo, da mi ne bo treba biti prisoten pri vseh teh urah, temveč sta na urah bila prisotna profesor predmeta in laborantka za fiziko. Z laborantko sva pred začetkom pouka natančno šla skozi vsa navodila in potek laboratorijske vaje. Podobno strokovno srečanje sem opravil še s profesoricami za matematiko, športno vzgojo in informatiko. 2.1 Določanje ciljev in potrebnih znanj za doseg ciljev pri učni uri fizike Pri učni uri fizike smo z dijaki zastavili cilje, ki jih želimo doseči na naslednjih učnih urah. Prav tako smo preverili in utrdili vso potrebno teoretično znanje, ki ga bodo dijaki za dosego ciljev potrebovali. Temeljni cilj, ki smo si ga zastavili, sta bila določiti moč pri hoji po stopnicah in izračunati količino čokolade, ki bi nadomestila energijske izgube. Za njun doseg smo s pomočjo slike 1 in vizualizacije problema načrtovali tri možne poti doseganja krovnih ciljev in oblikovali več podciljev. To so bili: • izmeriti čase vzponov do vrha stopnic; • izračunati višino stopnišča s pomočjo višine ene Slika 1: Določanje višine stopnišča s pomočjo viziranja in stopnice in števila vseh stopnic; kotnih funkcij. • izračunati višino stopnišča z uporabo znanja prostega pada; 2.2 Preverjanje in utrjevanje kotnih funkcij v • izračunati višino stopnišča z uporabo znanja kotnih skupinskem delu pri pouku matematike funkcij; Profesorica matematike je v prvi polovici učne ure razložila snov • določiti kot α (slika 1) s pomočjo viziranja in iz vsebin kotnih funkcij (definicije, uporaba in računanje s • izračunati porabljeno energijo za vzpon do vrha stopnišča. kotnimi funkcijami), v drugi polovici učne ure pa so dijaki delali 599 v skupinah pod vodstvom laborantke za fiziko in profesorice • izmeriti čas prostega padanja kamenčka od vrha matematike. stopnišča do tal za poznejši izračun višine Vsaka skupina dijakov je dobila metrsko desko, ki so jo stopnišča. morali prisloniti na zid pod poljubnim kotom. S pomočjo telefonov so izmerili kot α med desko in vodoravnico, nato pa Vnaprej so bili opomnjeni, da naj meritve izvajajo na tak vodoravno k2 in navpično k1 razdaljo deske (slika 2). način, da bodo čas čim bolj optimalno izkoristili. Vse meritve so v ustrezno tabelo na svojih telefonih morali vnašati sproti (slika 3). Po vseh opravljenih meritvah so dijaki zamenjali vloge in naredili še preostale meritve. Pri teh dveh urah so dijaki razvijali veščine opazovanja, sodelovanja, komunikacije, ustvarjalnosti in kritičnega razmišljanja. Slika 2: Merjenje naklona deske, navpične in vodoravne komponente. V drugem delu skupinskega dela so dijaki ti dve razdalji izračunali še s pomočjo kota in dolžine deske, ter ju primerjali z izmerjenima. Ko so vsi dobili približno enake vrednosti, smo lahko trdili, da smo eksperimentalno preverili veljavnost in uporabnost kotnih funkcij. Na ta način so dijaki pridobili potrebna znanja iz vsebin kotnih funkcij. Pri tej učni uri so dijaki preverjali kotne funkcije z namenom spodbujanja sodelovalnega timskega dela, kritičnega mišljenja, načrtovanja in razvijanja komunikacije. Slika 3: Excelova datoteka z navodili in vnesenimi 2.3 Izvajanje meritev za določanje moči pri uri meritvami oz. izračuni. športne vzgoje Pri tej učni uri sta sodelovali laborantka za fiziko in profesorica 2.4 Izpolnjevanje Excelove datoteke pri pouku športne vzgoje. Glavni cilj je bil, da dijaki izvedejo vse potrebne informatike eksperimentalne meritve in jih vnesejo s pomočjo uporabe Zaključne aktivnosti so dijaki izvajali pri dveh urah informatike, pametnega telefona v osebno Excelovo datoteko (slika 3). Morali kjer smo bili navzoči profesor fizike, profesorica informatike in so se povezati v Eduroam omrežje in dostopati do Excelove laborantka za fiziko. Dijaki so delali samostojno vsak s svojim datoteke, ki je bila shranjena v oblaku OneDrive. Vsak je imel računalnikom v učilnici za informatiko, saj so imeli vsa navodila dodeljeno pravico, da lahko ureja in vstavlja meritve v svojo že v svojih tabelah v obliki pripomb (slika 3 in 4). V celicah niso lastno datoteko. bila samo navodila, ampak tudi namigi, kako se kakšnega Dijaki so bili pri delu razdeljeni v skupine, pri čemer so se problema lotiti (slika 4). Preden so delo začeli, so morali urili v veščinah sodelovalnega timskega dela. Prva skupina štirih odgovoriti na motivacijsko vprašanje; koliko čokolade bi lahko dijakov je morala s pomočjo viziranja določiti višino zunanjih zaužili, da bi nadomestili energijske izgube, potem ko so se požarnih šolskih stopnic. To so naredili tako, da so na voziček štirikrat povzpeli do vrha požarnega stopnišča. dali ravno metrsko palico in jo nagnili pod takšnim kotom, da so videli vrh stopnišča, v skladu s sliko 1. Sledila je meritev naklona palice s pomočjo telefona in nato še meritev vodoravne razdalje do stopnišča in višine vozička. S pomočjo teh podatkov so lahko z uporabo kotnih funkcij določili višino stopnišča (slika 1). Druga skupina dijakov je med vzpenjanjem po stopnicah imela naslednje naloge: • s pametnih telefonom izmeriti čas hoje (hitre hoje Slika 4: Opomba in napotek pretvorbe iz Wattov v konjsko in teka) do vrha stopnišča; moč. • prešteti število stopnic do vrha; • izmeriti višino ene stopnice na več mestih z namenom kasnejšega izračuna višine stopnišča; Vse zahtevano je vsem dijakom, v dveh urah informatike in s pomočjo profesorjev in laborantke, uspelo narediti. Z dijaki smo 600 po opravljanih aktivnostih opravili tudi evalvacijo dejavnosti, v sklopu šestih učnih ur, od katerih sem pet učnih ur izvedel v sklopu katere smo poiskali težave in napake pri delu, na nerešene medpredmetnih povezavah z matematiko, informatiko in športno probleme poiskali rešitve in določili domače delo. Za domačo vzgojo. Prednost tako izvedenega dela je v krepitvi nalogo so morali izračunati, kolikšna bi bila približno absolutna sodelovalnega timskega dela, prestavitev pouka iz učilnic, napaka zaužite čokolade zaradi napak pri računanju višine urjenja dijakov v sodelovalnem timskem delu in uporabi stopnišča. sodobnih digitalnih orodij za učne namene. Dodatno Pri teh dveh učnih urah so dijaki razvijali kritično mišljenje, obremenitev tako izvedenega pouka predstavlja veliko reševanje problemsko zastavljenih nalog in računalniško usklajevanja z nosilci drugih predmetov in neprilagodljivost pismenost. urnika. Ne glede na manjše ovire, ki so del spremenjenega načina dela, menim, da so dijaki v tako organiziranem pouku veliko bolj 3 ZAKLJUČEK proaktivni, samoiniciativni, kritično misleči in tudi sooblikovalci Na hitro spreminjajočem se trgu dela težko predvidimo vse učnega procesa, kot so to lahko pri klasičnem frontalnem poklice prihodnosti. Ne glede na to pa lahko že v današnjem času, poučevanju. ko so vse informacije hitro dostopne, ocenimo, da v poklicih prihodnosti ne bo več ključno dobro pomnjenje velikega števila podatkov. Na prihodnjem trgu dela pričakujemo, da bodo VIRI uspešnejši kadri tisti, ki se bodo hitro prilagajali novim razmeram [1] Transversal Skills Framework. ATS2020. (2020). dela in bo podkrepljen s t.i. veščinami 21. stoletja oz. prečnimi Dostopno na: http://ats2020.eu/transversal-skills- veščinami. Te veščine so prilagodljivost, iznajdljivost, zmožnost framework. delovanja v spremenjenih razmerah, prevzemanje odgovornosti [2] Mobilna aplikacija za merjenje naklona. Bubble level in pobude, sodelovalno timsko delo, komunikacijske sposobnosti Galaxy. Dostopno na: in uporaba digitalnih orodij [1]. Z namenom načrtnega razvijanja https://play.google.com/store/apps/details?id=pl.nenter.app in krepitve opisanih veščin sem fizikalno učno snov predelal v .bubblelevel&hl=en_US 601 Učenje na daljavo v Arnesovih spletnih učilnicah Distance learning in Arnes online classrooms Tina Pajnik Sonja Strgar OŠ Vide Pregarc OŠ Antona Martina Slomška Vrhnika Bazoviška ulica 1 Pod Hruševco 33 1000 Ljubljana, Slovenija 1360 Ljubljana, Slovenija tpajnik@gmail.com sonja.strgar@guest.arnes.si POVZETEK komunikacije, procesa učenja in poučevanja v spletno okolje oz. v okolje, kjer sta učitelj in učenec fizično ločena, je odprl številna V prispevku je predstavljeno delo na daljavo v času epidemije vprašanja in ponudil možnosti za izboljšanje vzgojno- SARS-CoV-2, ki je potekalo preko Arnesovih spletnih učilnic. izobraževalnega procesa. Na dveh osnovnih šolah se je izvajalo učenje na daljavo z Učenje na daljavo ima svoje začetke v angleško govorečih uporabo Arnesovih spletnih učilnic za učence od 1. do 9. razreda državah. Konec 19. stoletja se je zaradi geografske izolacije pri predmetih tuji jezik v prvem vzgojno-izobraževalnem nekaterih območij in velikih razdalj v Združenih državah obdobju, knjižnično-informacijska znanja in matematika od 6. do Amerike, Kanade in Avstralije razvilo učenje na daljavo [1]. 9. razreda. V času dela na daljavo so uporabniki podrobneje Encyclopedia Britannica distance learning ali učenje na daljavo spoznavali Arnesovo spletno učno okolje in raziskali prednosti razlaga kot obliko izobraževanja, v kateri sta učitelj in učenec in slabosti uporabe spletnih učilnic. prostorsko ločena, komunikacijo med njima pa omogoča različna KLJUČNE BESEDE tehnologija [1]. Skozi zgodovino so se modeli učenja na daljavo izpopolnjevali, spreminjali glede na ciljno učečo skupino in se Učenje na daljavo, Arnesove spletne učilnice, spletno učenje, posodabljali v skladu s tehnološkim napredkom. osnovna šola 12. marca 2020 je bila v Republiki Sloveniji razglašena ABSTRACT epidemija, virus SARS-CoV-2 je povzročil zaprtje vzgojno- izobraževalnih zavodov ter drugih ustanov. Učenje in The paper presents distance learning during the SARS-CoV-2 poučevanje sta se preselila v domače okolje, učitelj in učenec sta epidemic, which took place in Arnes' online classrooms. At two postala fizično ločena, šole so na podlagi navodil in priporočil primary schools, distance learning was carried out using Arnes oblikovale skupne načine komunikacije, spletne učilnice in online classrooms for students from 1st to 9th grade in foreign protokole pri delu na daljavo. language in the first educational period, library and information Zavod Republike Slovenije za šolstvo je izdal strokovna skills and mathematics from 6th to 9th grade. During the distance navodila za ravnateljice in ravnatelje osnovnih šol za izvajanje learning, users got to know Arnes' online learning environment izobraževanja na daljavo v izrednih razmerah, v katerem avtorji in more detail and explored the advantages and disadvantages of priporočajo, da v času izobraževanja na daljavo [2]: using online classrooms. - šola vzpostavi komunikacijo s starši oz. učenci po različnih kanalih. KEYWORDS - se pri izbiri komunikacije šola, aktiv, oddelčni učiteljski Distance learning, Arnes online classrooms, online learning, zbor poenotijo in naj pri izbiri načina komunikacije primary school upoštevajo možnosti in zmožnosti staršev in otrok. - je pomembna tako povratna informacija učitelju o 1 UČENJE NA DALJAVO zadovoljstvu učencev in staršev s strani učencev in staršev kot tudi povratna informacija učencu na njegovo delo in V šolskem letu 2019/20 so se slovenske osnovne šole v drugi napredovanje. polovici šolskega leta zaprle in svoje vzgojno-izobraževalne dejavnosti izvajale na daljavo. Marca 2020 so se šolski strokovni - naj učitelji upoštevajo, da vsak učenec nima dostopa do svoje naprave oz. da nimajo vsi tiskalnikov. delavci soočali z novo realnostjo, z učenjem na daljavo, z učenjem v spletnem okolju, kjer sta didaktika in metodika dela Sodobni učitelj se je tako znašel pred popolnoma novim popolnoma drugačni v primerjavi s klasični poukom. Prenos izzivom. Učenje na daljavo je zahtevno in od učitelja zahteva, ne samo obvladovanje pedagoškega dela, ampak tudi poznavanje IKT opreme, ustrezno stopnjo računalniške pismenosti, prilagajanje novim razmeram ter hitro odzivnost v spletnem Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed okolju. for profit or commercial advantage and that copies bear this notice and the full Da bi izvedli učenje na daljavo, prenesli dejavnosti v spletno citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). okolje, uskladili učni proces in zmožnosti učencev, sva se Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia učiteljici na Osnovni šoli Vide Pregarc v Ljubljani in Osnovni © 2020 Copyright held by the owner/author(s). 602 šoli Antona Martina Slomška na Vrhniki odločili za uporabo Po opravljenih nalogah so učenci glede na vrsto naloge oddali Arnesovih spletnih učilnic. svoj izdelek, zapis, ilustracijo ali posnetek na način, ki je bil opredeljen v navodilih. Večina je svoje izdelke pošiljala na elektronski naslov učitelja, nekatere naloge ali rezultati pa so se 2 ARNESOVE SPLETNE UČILNICE beležili z reševanjem interaktivnih učnih listov. Arnes ponuja storitev, ki temelji na spletnem sistemu Moodle – Spletna učilnica se je posodabljala dvakrat tedensko, včasih Arnes Učilnice. Ker na Arnesu skrbijo za tehnično vzdrževanje tudi vsak dan, odvisno od načina dela. Zaradi preglednosti so se spletnih učilnic, so Arnesove Učilnice zagotovo najboljša izbira označevali tedni učenja na daljavo. Sčasoma je besedila bilo vse za spletno okolje, v katerem se izvaja učenje na daljavo. več, zato so se objavile samo tekoče vsebine (za obdobje dveh Nekatere šole so se odločile za uporabo Arnesovih spletnih tednov), ostalo pa se je pripelo v Wordov dokument Arhiv. S učilnic. Obveščanje staršev in učencev je praviloma potekalo klikom na priponko so imeli uporabniki pregled nad celotnim preko šolskih spletnih strani, na kateri so šole objavljale tudi delom. dostop do spletnih učilnic. S klikom na povezavo so učenci ali Za mlajše učence se je izkazalo, da je delo v spletni učilnici starši vstopili v Arnesove spletne učilnice, ki so bile urejene po lažje, če so navodila kratka in ne zahtevajo veliko klikanja do razredih ali predmetih. S klikom na določeno Arnes spletno cilja oziroma, če je poleg povezave slikovno gradivo ali če učilnico so se odprli predmeti oz. področja, pod katerimi so povezava sama ponuja video posnetek (slika 1), ne da bi učitelji objavljali navodila, povezave, slikovno gradivo, video uporabniki posebej odpirali strani ali lepili povezave. posnetke, fotografije, odpirali razprave v obliki forumov, pripravili prostor za oddajanje nalog učencev, izdelali kvize, pripravili interaktivne vsebine (H5P), izvedli videokonference Jitsi. Arnesove spletne učilnice so enostavne za uporabo, zato so na OŠ Vide Pregarc zajeli kar celotno vertikalo, to je učence od prvega do devetega razreda. V nižjih razredih, kjer učenci še ne berejo samostojno, so pri uporabi spletnih učilnic pomagali starši. Za prijavo v Arnes Učilnice so učenci potrebovali AAI račun, ki ga je naredil računalnikar na šoli. Šola je izdelala kratka navodila za prijavo v Arnes Učilnice. Večjih težav s prijavami ni bilo. 2.1 Tuji jezik v prvem vzgojno-izobraževalnem obdobju Slika 1. Primer video povezave s slikovno oporo. Za učence prvih treh razredov so bile oblikovane tri spletne učilnice. Glede na razred je učiteljica objavljala navodila za delo 2.2 Knjižnično-informacijska znanja na daljavo. V prvem razredu so navodila prebrali starši, v drugem Učenci so v času učenja na daljavo imeli možnost opravljati in tretjem razredu pa učenci sami. Navodila so bila objavljena bralno značko in eko bralno značko. V veliko pomoč jim je bila enkrat tedensko, saj ima predmet angleščina na razredni stopnji spletna učilnica Knjižnica, v kateri je bila objavljena povezava dve uri na teden. Arnesove Učilnice so omogočile, da je do spletne knjižice Koronavirus, pod njo pa navodila za uporabnik prebral navodila in opravil določeno dejavnost, pri opravljanje bralnih dejavnosti (slika 2). Ker so bile knjižnice tem je lahko: zaprte, učenci niso imeli dostopa do besedil, zato so se v spletnih - s klikom na povezavo na YouTube ponovil angleško knjižnicah objavljala besedila, ki so prosto dostopna na spletu. pesem, Povezave do ljudskih in avtorskih pravljic so učencem pomagale, - s klikom na priponko odprl slikovno gradivo in na podlagi da so opravljali bralno značko. Od vseh ponujenih besedil so le-tega pripravil govorni nastop po vzorcu, učenci največkrat izbrali slovensko leposlovje na Wikiviru, ki so - s pregledom pripetega slikovnega gradiva po navodilih v spletni učilnici bili objavljeni v obliki povezav, te so bile izdelal pravljični zemljevid, urejene po priimkih avtorjev za lažjo orientacijo. Učenci so nato glede na svoje zmožnosti in starostno stopnjo odgovorili na - ob ogledu naloženega videoposnetka ponovil ritmično vprašanja in jih objavili v zbirniku v Padletu ali pa so zapiske izreko, s katero je ponovil dneve v tednu, poslali učitelju na e-mail in jih je nato učitelj objavil v Padlet - s klikom na povezavo na spletno stran poslušal zvočno zbirniku. Če pa so bralci skupinsko prebrali besedilo, se je odprl pravljico v angleščini in nato poročal s sliko ali besedo o klepet, kjer so udeleženci delili svoje bralne vtise. sestavinah pravljične jedi, Poleg klasične bralne značke se je na podoben način izvajala - s klikom na povezavo na interaktivni učni list, ki je sam tudi eko bralna značka. Učencem je spletna učilnica nudila sešteval točke in dajal številčno povratno informacijo, povezave na članke z ekološko vsebino, povezave do besedil v angleškem in nemškem jeziku, do slovarjev, zvočnih knjig, - s klikom na priponko v PowerPoint formatu opravil strokovnih revij, gledaliških in lutkovnih predstav pa tudi preverjanje znanja, priročnikov za ustvarjanje. - s klikom na povezavo rešil kviz in preveril svoje znanje besedišča iz različnih sklopov. 603 Slika 2. Navodila za opravljanje bralne značke. Spletna učilnica se je posodabljala vsak dan. Učenci so tako sproti dobili povratno informacijo o svojem delu, preverili so lahko komentarje v zbirniku, z rdečo barvo so bile označene Slika 4. Zadnje obvestilo v spletni učilnici. novosti. Knjižničar je moral enkrat tedensko preverjati povezave, Sledili so posamezni razredi, znotraj razredov pa je bila saj se je dogajalo, da nekatere povezave niso bile ves čas delitev narejena po tednih (slika 5). Ker je sčasoma spletna dostopne. učilnica postala nepregledna zaradi prevelikega števila objav, Rezultat opravljenih bralnih značk je bil kljub učenju na smo neaktualne tedne skrili za udeležence. daljavo visok. Veliko število bralcev je šolskemu knjižničarju sporočalo, da imajo čas in dostop do besedil in da bodo verjetno tudi med počitnicami brali besedila, ki so na voljo v spletnih učilnicah. 2.3 Matematika Učenci so se matematiko učili v spletni učilnici Matematika, ki je bila razdeljena po razredih (slika 3). Slika 5. Razdelitev poglavja 6. c. Vsako poglavje je imelo tudi forum, kjer so učenci postavljali vprašanja (slika 6). Odgovarjali pa so tako sošolci kot učiteljica. Forum je služil kot pomoč pri težavah, na katere so naleteli učenci, lahko pa tudi zgolj za debato med njimi. V spletni učilnici smo objavljali vsak dan sproti, za vsako uro na urniku posebej. Vedno smo najprej pričeli z nagovorom učencem, nato smo dodali navodila za delo za učno uro, sledila so dodatna navodila (priprava na tekmovanja, reševanje NPZ-jev, Slika 3. Razdelitev spletne učilnice za matematiko. izdelava plakata Matematika v vsakdanjem življenju … ). Navodila so bila sestavljena iz besedila, povezav do uporabnih Na vrhu spletne učilnice so bila Obvestila (slika 4), ki so spletnih strani, povezav do videokonferenc, povezav do anket, zajela redno obveščanje o novicah, ki se tičejo vseh učencev in povezav do preverjanja znanja in rešitev le-teh, motivacijskih navodila (npr. kako najhitreje dostopam do spletne učilnice). slik, napotitve za premagovanje ovir, povezav do videoposnetkov. Učence smo tudi sproti opozorili, v kolikor kdo naloge ni pravočasno oddal, naj to uredi. 604 Slika 8. Spremljanje zadnjega dostopa do predmeta. 3 DISKUSIJA 31. maja 2020 se je učenje na daljavo uradno zaključilo. Vsi osnovnošolci so se s 1. junijem 2020 lahko vrnili v šolske klopi. Za učence osnovnih šol je učenje na daljavo potekalo več kot dva meseca. V času učenja na daljavo s(m)o učitelji v spletnih učilnicah ves čas skrbeli za povratne informacije na različnih ravneh: kakšno je počutje učencev, kako doživljajo učenje na daljavo, kako se spopadajo s spletnim učnim okoljem, ali imajo tehnično podporo, kako se znajdejo pri uporabi spletnih učilnic, Slika 6. Primer foruma razreda. ali lahko sledijo navodilom. Starši in učenci so sporočali, da so Arnesove Učilnice Arnes Učilnica znotraj storitve nudi Videokonferenco Jitsi, na preproste za uporabo, da se znajo orientirati v spletnih učilnicah, željo učencev pa smo uporabili Zoom (slika 7). da so povezave vidne in razumljive, da so jim navodila za uporabo v pomoč. Poudarili so, da je spletna učilnica odlično izhodišče za uporabo dodatnih aplikacij kot so Zoom, Kahoot in Padlet. Z vsakodnevno komunikacijo spletna učilnica deluje živo, saj se kar naprej posodablja in spreminja. Za učitelje je vsekakor prednost, da z uporabo Arnesovih Učilnic lahko s prilagoditvami vnašajo v učenje na daljavo elemente formativnega spremljanja, ki poudarja aktivnost učenca in trajnejše znanje. Če pod elemente formativnega spremljanja štejemo [3]: namene učenja in kriterije uspešnosti, dokaze, povratno informacijo, vprašanja v podporo učenju in samovrednotenje/vrstniško vrednotenje; potem z Arnesovimi Učilnicami lahko zajamemo vse. V spletnih učilnicah lahko predstavimo namene učenja, kriterije uspešnosti, izdelke v Slika 7. Povabilo na videosrečanje Zoom. spletnih učilnicah lahko uporabimo kot dokaze, lahko omogočimo komunikacijo, ki omogoča vrednotenje. Vse našteto Učenci so povratne informacije za delo dobili: je pomembno tudi za učitelja, saj tako lahko tudi preverja in - svoje izdelke so poslali na učiteljičin mail in ta jim ocenjuje ter v spletnem okolju vzpostavlja podobne učne je odgovorila. strukture kot v razredu. - učenci so rešiti ankete narejene v Google Docs in Arnesove Učilnice so se izkazale za zelo učinkovito spletno so takoj dobili povratno informacijo. okolje v času dela na daljavo. Razen nekaj začetnih težav z - učenci so izdelali kolaž slik svojega dela in slike dostopanjem do strežnikov, kar so na Arnesu hitro uredili, težav prilepili v Padlet, kjer so sošolci in učiteljica z dostopanjem do spletnih učilnic ni bilo. Delo znotraj učilnic je komentirali delo posameznika. bilo enostavno, ne učitelji ne učenci niso imeli večjih težav. Komunikacija je bila dvostranska in učinkovita, povratna - učenci so rešiti spletni kviz Kahoot in so takoj informacija pa takojšnja. dobili povratno informacijo. Omejitve in priporočila so postale del vsakdanjega življenja. - učenci so zahtevano nalogo oddali v spletni učilnici Učenje na daljavo ni več samo pojem, ki se izvaja nekje daleč na in učiteljica je podala povratno informacijo. drugi celini, ampak je postalo del slovenskega šolskega sistema, - učenci so sodelovali v videokonferenci. zato je potrebno pripraviti bodoče učitelje na delo na daljavo, vpeljati v študijske programe tudi sistematično razvijanje Zelo uporabno za učiteljico matematike je bilo tudi poglavje računalniške pismenosti, strokovno izpopolniti učitelje, ki niso Sodelujoči (slika 8), saj je učiteljica redno spremljala, kdaj je bil vešči dela z IKT, ter podpreti učitelje, da raziskujejo nova spletna posamezni učenec nazadnje aktiven v učilnici ter tako sproti orodja. opozarjala učence na morebiten prevelik primanjkljaj v sprotnem delu. 4 ZAKLJUČEK V času učenja na daljavo smo na dveh osnovnih šolah uporabljali Arnesove Učilnice, ki so omogočale delo na daljavo pri različnih 605 predmetih od 1. do 9. razreda. Ugotovili smo, da z uporabo LITERATURA Arnesovih učilnic lahko izvajamo učenje na daljavo v skladu s [1] priporočili Zavoda Republike Slovenije za šolstvo, saj je Encyclopedia Britannica. DOI= https://www.britannica.com/ Arnesovo spletno okolje preprosto za uporabo s strani uporabnikov, na drugi strani pa omogoča zbiranje dokazov in [2] Izvajanje izobraževanja na daljavo v izrednih razmerah. povratnih informacij ter omogoča vnos elementov formativnega Strokovna navodila za ravnateljice in ravnatelje osnovnih šol. 2020. Ljubljana: Zavod Republike Slovenije za spremljanja v digitalno okolje. šolstvo. DOI= https://sio.si/wp- V primeru, da se bo učenje na daljavo ponovilo v novem content/uploads/2020/03/Strokovne-usmeritve-Navodila- šolskem letu, pa velja razmisliti o dostopu v spletne učilnice z ZRS%C5%A0.pdf gesli, saj se z objavami učnih gradiv, ki jih izdelujejo učitelji, [3] Formativno spremljanje v podporo učenju: priročnik za odpirajo tudi vprašanja o avtorskih pravicah, navajanju virov in učitelje in strokovne delavce. 2019. Ljubljana: Zavod za intelektualni lastnini strokovnih delavcev. Kot primer dobre šolstvo Republike Slovenije. prakse velja izpostaviti spletno učilnico Matematika, kamor so učenci dostopali z AAI prijavo, s čimer smo poskrbeli tudi za njihovo spletno varnost. 606 Poučevanje tujega jezika na daljavo in nova normalnost New normal: foreign language and distance teaching Alan Paradiž Srednja vzgojiteljska šola, gimnazija in umetniška gimnazija Ljubljana Kardeljeva ploščad 28a 1000 Ljubljana, Slovenija alan.paradiz@svsgugl.si POVZETEK Digitalizacija učenja ponuja mnogotero možnosti za usvajanje 1 UVOD tujega jezika, hkrati pa pomeni, da učitelj v novem okolju Generaciji t. i. screenagerjev, rojenim v svet digitalnega za prevzema vloge, ki do pojava digitalizacije niso obstajale. Nova učenje več ne zadostuje le beseda, ampak za učenje potrebujejo »normalnost« nas je čez noč prisilila, da smo klasično digitalne podpore. Usvajanje znanja je z digitalizacijo postalo poučevanje zamenjali samo s poučevanjem na daljavo. Zaprt časovno ter prostorsko odprto. Z digitalizacijo učenja je le-to prostor učilnice je zamenjal neskončni prostor digitalnega sveta. preseglo ozko definicijo pomnjenja in zdaj vključuje Brez fizične prisotnosti je učitelj čez noč moral osvežiti ali raziskovalno, sodelovalno delo, pomeni tudi iskanj preverjenih nagraditvi svoje IKT spretnosti in jih uporabiti za optimalno in merodajnih informacij na medmrežju, pri čemer je učeči se učenje na daljavo. Moral je tudi upoštevati številne zunanje subjekt avtonomen uporabnik, aktiven v učnem procesu. Nova faktorje, ki bi lahko vplivali na uspešnost učenja dijakov, a hkrati »normalnost« je kljub izzivom ter preprekam in dilemam o imel edinstveno možnost, da upošteva načelo avtonomnosti pri nenadomestljivosti klasičnega pouka v šoli, pomenila priložnost, učenju, ki dela učno izkušnjo najbolj optimalno. da učitelj, kot usmerjevalec učnega procesa dijaku omogoči, da je pri usvajanju jezika samostojen, avtonomen ter časovno KLJUČNE BESEDE neobremenjen, tj. da se uči (oz. pri tujem jeziku potaplja v Avtonomnost, tuji jezik, digitalizacija, vloga učitelja, poučevanje jezikovno kopel), ko to tudi sam želi. na daljavo, učenje na daljavo V pričujočem prispevku se osredotočam na izkušnje poučevanju angleščine kot prvega tujega jezika na daljavo v ABSTRACT srednji šoli in gimnaziji. Spoznanja, ki ji navajam, so moje lastne Digitalisation of teaching offers an abundance of opportunities to ali pa so to povratne informacije dijakov, hkrati pa ugotavljam, foster language acquisition, thus giving a teacher a set of new kje so še možnosti za izboljšavo učenja na daljavo. roles that did not exist prior to the emergence of digitalisation. The new »normal« urged us to become more involved in distance teaching than ever before. Learning in an enclosed classroom has 2 VLOGA UČITELJA PRI POUČEVANJU become substituted with the infinite learning space of the digital NA DALJAVO world. With no face to face communication, a teacher has Preteklo šolsko leto je bilo v luči nove »normalnosti« na overnight become someone who has to employ the advantages of področju izobraževanja unikum, poln izzivov, novih (spo)znanj »the digital« classroom in order to teach their students effectively, ter lekcij za prihodnost. Nova »normalnost« je od učitelja thus obtaining new skills in IKT technology that pertains to zahtevala, da se je IKT opismenil. Funkcija učitelja pri distance teaching, but also considering outside factors that might poučevanju na daljavo pa se ni zmanjšala, ampak le influence their or their students' learning process. The distance dinamizirana. Le-ta v informacijski dobi ni le prenos znanja, learning has also given teachers the opportunity to consider the ampak tudi poznavanje specifik ciljne publike, saj poučuje factor of autonomy in each and every student’s style of learning, populacijo, ki ima, [4] (a) visoko razvite spretnosti pri uporabi thus making their learning experience optimal. modernih tehnologij, ki pa jih je, kot njihovo močno področje, potrebno naprej dodatno razvijati. Prav tako (b) delo v KEYWORDS digitalnem okolju [dijake] dodatno motivira, (c) uporaba spleta Autonomy, foreign language, digitalisation, distance learning, pa neodtujljiv medij pri poučevanju, saj poglablja in razširja distance teaching, teacher’s role znanja, ki jih [dijak] nezavedno ponotranji med tem ko se uči v svetu, ki mu je blizu. Nova »normalnost« je čez noč povzročila situacijo, ko več ni šlo za kombinacijo klasičnega poučevanja in poučevanja v Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed digitalnem okolju, katerega se večina učiteljev poslužuje, ampak for profit or commercial advantage and that copies bear this notice and the full dokončen (in vsaj začasen) premik k slednjemu. Odsotnost citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). dijakov izza štirih sten učilnic in matičnih šol in manko Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia neposrednega stika s profesorji je pomenil, da smo se morali vsi, © 2020 Copyright held by the owner/author(s). 607 tako dijaki kot učitelji (pa tudi starši), čez noč privaditi na novo Učitelj kot »animator« pri poučevanju na daljavo naredi razmere – situacijo poučevanja in učenja na daljavo, kjer se je, učenje tujega jezika karseda raznoliko, odprto in dinamično in tako na eni kot drugi strani, izkazala za nemoten potek le-to izhaja iz raznolikega (a ne prevelikega) števila virov in izobraževalnega procesa nujnost poznavanja IKT tehnologije. pristopov. Na ta način učenec najde vir ali pristop, ki mu najbolj Da pa bi ohranili pouk kvaliteten, je bilo tudi ključno, da se odgovarja in med vsemi možnostmi tudi izbira in si učenje kroji učitelji zavedamo, kdo je naša ciljna publika. Kvaliteten pouk bo po lastni meri, je avtonomen , učenje pa si personalizira – na ta tisti, [1] ki » nas aktivno vključuje in povezuje z drugimi način pa bo tudi bolj motiviran in uspešen, pri tem pa ne čuti sodelujočimi, [pri čemer pride] do izmenjave izkušenj in časovnih pritiskov klasične šolske ure. Ti aspekti in dejstva zanimivih idej«. V tem času je [2] pomemben učiteljev optimalnejšega učenja so mi pri načrtovanja dela na daljavo »prilagojen pedagoški stil« oz »posluh« kot tehnologija sama. pomagali, da sem oblikoval pouk »po meri dijaka«. Učitelj je [2] »animator kolektivne inteligence« učečih se subjektov, hkrati pa je opazovalec in vodja ter podpornik individualnega učnega procesa, ki ga omogoča splet. Vloga 4 PRIMERI DOBRIH PRAKS POUČEVANJA učitelja pri učenju na daljavo se torej le redefinira. NA DALJAVO PRI TUJEM JEZIKU Pri poučevanju na daljavo sem naletel na veliko izzivov, 3 PARADIGMA UČENJA NA DALJAVO – vprašanj, našel pa tudi veliko rešitev in dobrih praks, podlaga TEORIJA katerih je poznavanje IKT tehnologije, a morda pomembneje, posluh do dijakov oz. razumevanje, kdo so in kako se učijo. V Iz paradigme učenja na daljavo [3] je viden premik v odnosih tem poglavju navajam in osvetlim pomembnejša spoznanja v med deležniki v virtualnem okolju. Vloga učitelja in učenca je času poučevanja na daljavo. dinamizirana. Učitelj, ki fizično ni prisoten v prostoru, vodi, organizira in usmerja proces učenje, nudi pomoč in daje povratne 4.1 Komunikacija informacije v zvezi s predmetnim področjem, samostojno pa delo Z dijaki smo komunicirali preko enega skupnega okna opravi dijak sam. Gre za poseben odnos interakcije, ki mogoča »komunikacija« (na portalu e-asistent), kjer so tedensko izkušenjsko učenje v dijaku domačem okolju, učne vsebine pa so prejemali navodila za delo. Ob pričetku dela na daljavo, sem prek moderne tehnologije in spletnih platform bolj privlačne in dijake vseh oddelkov obvestil, kako sem zastavil delo in na tako dijaka notranje motivirajo ter stimulirajo (nezavedno) kakšen način bo potekalo naše sodelovanje. Vseskozi je bilo učenje. Vloga učitelja je vloga organizatorja in usmerjevalca, moje in njihovo delo tudi evalvirano. pomočnika in vira povratne informacije (ali dodatne razlage), dijak pa se uči samostojno. Njegova vloga se spreminja, saj 4.2 Načrtovanje in izvedba (primer tedenskega postaja samostojni uporabnik in ne le učenec. sveta okrog sebe. sklopa) Tabela 1: Paradigma učenja na daljavo – vloge učitelja, učenca Načrtovanje pedagoškega procesa se je izkazalo za ključno tudi in tehnologije pri delu na daljavo. Pri planu dela za posamezni teden sem upošteval najprej količino dela in zadolžitev, ki jih dijaki Kako mora biti v virtualnem okolju opravijo samostojno glede zahtevnost učne snovi in dejstvo, da Kdo,kaj delajo skoraj samostojno in na daljavo, predvidel pa sem tudi, kako si je delo možno razdeliti na manjše zaključene celote, saj Učitelj Vodi učenca kot organizator pouka, je e- upoštevam dejstvo, da se vsi enako hitro ne učijo. kompetenten Dijaki so bili v skupnem oknu »komunikacije« na portalu e- asistent v ponedeljek zjutraj (plan dela, gradiva, posnetki, Učenec Je v interakciji z vsebinami in drugimi povezave itd. so bili pripravljeni teden prej) obveščeni o snovi, sodelujočimi, postaja avtonomen, notranje ki jo bo potrebno (ob različnih podporah) predelati. Pravočasna motiviran in kritičen uporabnik, ki si tudi obveščenost dijakov, se mi je zdela ključna, saj le-ta omogoča, sam določa kdaj in koliko dela da dijaki že v začetku tedna vidijo, koliko zadolžitev jih čaka in Prostor Digitalni prostor za usvajanje znanj, lahko tudi sami načrtujejo ter organizirajo delo v novem tednu. izmenjavo idej in informacij Obvestilo o zadolžitvah je bilo z alinejami razdeljeno na manjše Izkušnje Proces izmenjave izkušenj med člani enote. Namen takega obvestila je bil dvojen. Dijaki, ki so učno skupine, ki ga v učni proces vključuje uspešnejši, so lahko snov celotnega tedna predelali v enem učitelj zamahu, tisti pa, ki potrebujejo več časa, so lahko delo opravili v Učenje Prijetna izkušnja (osebna, intelektualna skladu s časovnico dela na urniku (tj. v treh manjših sklopih, v rast), nezavedno ponotranjenje podatkov obsegu treh šolskih ur) do konca tedna. Ta oblika dela spodbuja Učne vsebine Fleksibilne, večplastne, življenjske in pri dijakih avtonomnost dela (dijak si sam določa, kdaj bo opravil odprte glede na potrebe in želje učencev zadolžitve), in dijaku daje večjo fleksibilnost pri učenju (zaradi Moderna Virtualno okolje, splet, e-učilnice, ZOOM, manjšega števila ZOOM video konferenc, ki so jih zamenjale tehnologija, učna aplikacije, e-komunikacija (portal e- vnaprej posnete zvočne ali video razlage zahtevnejše snovi), da okolja asistent), google docs si sam časovno razporeja delo. Raba novih Učitelj in učenec se poslužujeta IKT, kar komunikacijskih omogoča izmenjavo znanj in izkušenj. 4.3 Povratna informacija tehnologij Potreben je skupni nivo e-kompetenc. Povratna informacija je ključnega pomena. 608 Najprej to velja, ko gre za ugotavljanje in evalvacijo ali dijaki pismo za maturo), sem vnaprej posnel zvočne učne ure, s razumejo snov. Nabor dijakov iz vsakega razreda (tedensko pomočjo katerih sem dijake skozi že znane vire (učbenik in preverjanje nalog več kot 200 dijakov, od tega 60 maturantov, je delovnik zvezek) ter gradiva iz že znane e-učilnice vodil in nemogoče) je moral do konca tedna oddati naloge iztekajočega usmerjal pri usvajanju nove snovi. Za ta pristop sem se odločil iz tedna (ali preteklih tednov). Pri tem upoštevam možnost več razlogov. Glavni sta časovna fleksibilnost in upoštevanje izbirnosti. Dijaki so bili obveščeni, katere naloge morajo nujno notranje diferenciacije. Za razlago eseja, na primer, bi v razredu oddati (npr. poprava testa) in katere lahko oddajo izbirno pri klasičnem pouku porabil 3 šolske ure, saj v heterogeni skupini (povzetek vsebine videa, interpretacija znanega citat, članek, ni mogoče prehitevati snovjo. Te tri ure bi v primeru izbora povezan z obravnavano temo, po lastni izbiri itd.), istočasno pa ZOOM video konference (in klasičnega poteka razlage) potekale imajo možnost, da svoje odgovore preverijo v sporočilu z ob točno določenih terminih po urniku in časovno nikakor niso rešitvami. Izbor nalog, ki so jih oddali, so fotografirali in optimalne. Učno uspešnejši dijaki, bi ob slednjem za istovetnost, da gre za njihovo delo, podprli z dijaško izkaznico napredovanje skozi snov porabili več časa. Snov bi bila slišana ter gradivo poslali po elektronski pošti. le enkrat, kar pa bi za učno šibkejše lahko bilo problematično. V Drug primer izbirnosti in samostojnega odločanja v kontekstu primeru pa, da so zvočne (ali video) ure posnete vnaprej, pa povratne informacije je bila video konferenca ob petkih. Vsak dosežem ciljno publiko v celoti. Kako? Dijaki, ki za učenje ne petek (oz. zadnjo uro po urniku v tekočem tednu) so dijaki lahko potrebujejo veliko podpore, se bodo zaradi možnosti odprtega prišli na skupno ZOOM video srečanje (povezava je bila učenja ob poslušanju zvočne podlage ter nabora nalog hitro tedensko v oknu »komunikacija«), kjer so za snov iztekajočega seznanili z zakonitostmi pisanja eseja in bodo ob samostojni tedna lahko prosili za pojasnila, dodatno razlago ali le preverbo, analizi že napisanih esejev hitro prišli do sinteze – samostojne da je snov razumejo. Načelo izbirnosti daje dijakom možnost, da tvorbe te literarne vrste. Učno šibkejši dijaki pa lahko med samo si sami, avtonomno, določajo, kako bodo preverili svoje znanje, razlago posnetek ustavijo, oz. posamezne dele ali celoten nanj pa nalaga tudi odgovornost za lastno učenje. posnetek poslušajo večkrat. Povratna informacija je lahko tudi podatek o tem, ali je način posredovanja snovi, tj. ali so metode in pristopi k poučevanju 4.5 Ocenjevanje znanja ustrezni (le-ta je seveda neodutljivo povezana z zgornjo).V Poseben izziv je predstavljajo ustno in pisno ocenjevanje znanja začetku obdobja nove »normalnosti«, je med učitelji potekala na daljavo. Optimalno rešitev, ki bi nadomestila (objektivno) živahna virtualna diskusija o načinih podajanja snovi na daljavo, ocenjevanje v razredu je bilo skoraj nemogoče najti, hkrati pa je izmenjava informacij o primernih metodah poučevanja in bilo potrebno najti možnost, ki bi zagotovila objektivnost platformah, ki so hkrati tudi učinkovite (in ne nazadnje varne) za ocenjevanja in merodajnost rezultatov. delo z dijaki na daljavo. Zagotovo ima vsak predmet svoje Za pisno ocenjevanje na daljavo sem uporabil švedsko specifike, ki zahtevajo svojevrsten način dela. Do ugotovitev, kaj platformo exam.net, ki že v brezplačni različici ponuja dovolj je optimum pri poučevanju tujega jezika, pa pridem lahko že s funkcij za pisanje testa, za upravljanje le-tega pa niso potrebna preprosto (anonimno) anketo. Dijaki so v oknu »komunikacija« poglobljena IKT znanja (npr. test v pdf obliki se enostavno naloži odgovorili na nekaj vprašanj, ki so me vodile do izboljšav. v sistem, dijaki ga odprejo, in v prazno word datoteko vpisujejo Nekateri so tudi podali svoje predloge preko neposrednih odgovore). Za razliko od drugih platform exam.net omogoča sporočil ali video konference. odprtje celozaslonskega načina, kar prepreči možnost odpiranja 4.4 Izbor spletnih platform in metod dela pri drugih spletni strani, datotek itd., saj se v tem primeru izpit zapre in ga mora učitelj vnovič odpreti. Hkrati je možno platformo poučevanju tujega jezika na daljavo kombinirati s videokonferenco ZOOM (, ki je bila sicer osnova Znano je, da se ljudje najbolj optimalno učimo, ko smo sproščeni, tudi ustnega ocenjevanja), kar učitelju daje možnost dodatnega ko delovno okolje ni stresno in smo notranje motivirani. Ena nadzora nad dijakom, ki pa so tudi zaradi časovnih omejitev bili izmed nalog učitelja pri učenju na daljavi je bila, da vsaj do neke primorani biti na pisanje fokusirani in niso imeli (veliko) mere zadostimo tem faktorjem, saj je v novi situaciji umanjkala možnosti uporabe nedovoljenih pripomočkov. fizična bližina in nadzor profesorja. Ena izmed ugotovitev povratnih informacij dijakov je bila, da 4.6 Delo z maturanti je prevelika raznolikost virov, povezav, novih platform, aplikacij Brez dvoma nam je bila pri poučevanju na daljavo prioriteta delo in načinov dela, lahko tudi kontraproduktivna (vsi dijaki prav z dijaki zaključnih letnikov in maturanti. tako niso enako spretni z moderno tehnologijo oz. se v množici V tem času sem s pomočjo že zgoraj opisanimi primeri podatkov in tudi načinov, kako do teh podatkov izgubljajo). načrtovanja tedenskega obsega dela, zvočnimi posnetki razlag Odločil sem se, da za video konference uporabljam enako kompleksnejših vsebin (stalna sporočanjska oblika časopisnega platformo kot večina ostalih profesorjev, da izkoristimo že znane članka), domačih nalog pisanja (preko google docs platforme so vire informacij in gradiv (e-učilnice, učbenik in delovni zvezek), dijaki pošiljali svoje seje, pisma, reportaže itd., kjer so preko iste ter komuniciram z dijaki preko portala e-asistent (okno platforme dobili individualno povratno informacijo), »komunikacija«). internetnimi povezavami do maturitetnih nalog vseh vrst iz Vnaprej posnete video in zvočne ure so se izkazale za dober preteklih let ter z video konferencami (utrjevanje knjižnih način razlage snovi. Ker so si dijaki istega razreda pri tujem predlog za maturo, urjenjenje govornih spretnosti za ustni del jeziku v svojem znanju zelo različni, je bilo moje osnovno vodilo mature, povratna informacija o svojem pisnem izdelku) dosegel upoštevanje le-ga. Pr snovi, ki zaradi kompleksnosti zahteva veliko večino dijakov, ki so, morda tudi zavedajoč se, da je dodatno razlago (npr. pogojniki, razpravljalni esej ali uradno matura pred vrati, opravili večino zadolžitev. 609 5 ZAKLJUČEK LITERATURA Nova »normalnost« preteklega šolskega leta je pomenila [1] Johnson, M. New Roles for Educators. Fev. sunkovit preobrat tudi na področju poučevanja, ki je (vsaj 2000. Dostopno 25. 6. 2018 na začasno) temeljil samo na digitalnih podlagah. Učinkovitost http://mff.org/edtech/article.taf?_function=detail pouka (tujega jezika) na daljavo je zahtevala tudi dodaten posluh &Content_uid1=290 do učečega se subjekta, ne le strokovno znanje učitelja na svojem predmetnem področju. Uporaba različnih pristopov (avdio [2] Levy, P. Cyberculture. (2000), Minnesotta, posnetki, videi, video konference, ankete, kvizi), ažurnost University of Minnesota press. povratnih informacij učitelja ter raznolikost virov za utrjevanje [3] Paradiž, A. (2012) Vloga učitelja v digitalni dobi. (347-353) in usvajanje snovi je učenca notranje motivirala in istočasno Dostopno 5. 9. 2020 na postavila v fokus učnega procesa. Dijaki so pri avtonomnem in https://vivid.fov.um.si/zbornik/arhiv-zbornikov/ pri (časovno) bolj fleksibilnem učenju bili notranje motivirani za [4] Šink, J. Prihodnost učitelja in šole. Dostopno delo. Ker pa velja, da učenje recipročen proces, kjer sodelujeta učitelj in dijak, je bila povratna informacija in evalvacija tudi pri 21. 7. 2017 tej obliki dela ključna, saj je omogočila optimizacijo učnega http://www.frodx.com/2012/04/30/prihodnost- procesa na daljavo. ucitelja-in-sole/ 610 Učenje besedišča z aplikacijo Quizlet Vocabulary learning with Quizlet Andreja Peruš Osnovna šola Ribnica na Pohorju Ribnica na Pohorju 29 2364 Ribnica na Pohorju, Slovenija andreja.perus@osribnicanapohorju.si POVZETEK učnega procesa, kot pri obliki učnih gradiv, ki se uporabljajo pri tujem jeziku [2]. Za pouk tujega jezika ima učitelj na voljo veliko Učenje besedišča pri tujem jeziku je izredno pomembno, saj je pripravljenih elektronskih in interaktivnih gradiv ter spletnih za sporazumevanje potreben bogat besedni zaklad. Ker pa lahko aplikacij, s katerimi lahko izdela tudi lastna učna e-gradiva [1]. učenje besedišča postane kar hitro dolgočasno, v pouk pogosto Pri uvajanju digitalnih orodij v pouk pa je pomembno, da učitelj integriram IKT, ki popestri sam pouk in učence motivira za delo. izbere oblike dela, ki se osredotočajo na učenca, ter da z V prispevku je predstavljena aplikacija Quizlet, ki jo pri vsebinami in ustreznimi aplikacijami omogoča učencem aktivno poučevanju tujega jezika pogosto uporabljam za samostojno in in učinkovito delovanje v digitalnih okoljih. sodelovalno učenje besedišča. Aplikacija združuje besedišče, razlago oziroma sliko, izgovorjavo in črkovanje ter omogoča zabavno in na učenca osredinjeno učenje. Učenci z aplikacijo 2 UČENJE BESEDIŠČA PRI TUJEM JEZIKU Quizlet ciljno besedišče hitro usvojijo, saj jih elektronske učne kartice, raznolike vaje in igre motivirajo za delo in učenje. Besedišče kot osnovno komunikacijsko sredstvo za sporazumevanje je pomembno za razvoj sporazumevalne KLJUČNE BESEDE oziroma leksikalne zmožnosti, tako v maternem kot v tujem jeziku. Bogat besedni zaklad je namreč nujno potreben za Učenje besedišča, tuji jezik, Quizlet uspešno obvladovanje različnih jezikovnih situacij. Učenje ABSTRACT besedišča pri tujem jeziku pa lahko kar hitro postane monotono, saj je za usvojitev le-tega potrebno veliko ponavljanja in Learning vocabulary in a foreign language is extremely raznolikih predstavitev posameznih besed. Za učinkovito učenje important, as communication requires a rich vocabulary. in usvajanje besedišča pri poučevanju nemščine v pouk However, because learning vocabulary can quickly become integriram tudi IKT, saj le-ta popestri sam pouk in učence boring, I often integrate ICT into the lessons, which enriches the motivira za delo. lessons themselves and motivates students to work. The paper Uporaba IKT lahko pomaga učencem pri razvijanju bralnih in presents the Quizlet application, which I often use when teaching slušnih zmožnosti ter pisnega izražanja, bogatenju besedišča in a foreign language for independent and collaborative vocabulary slovničnega znanja. learning. The application combines vocabulary, explanation or Kot ugotavlja Retelj, morajo e-učna gradiva in programska image, pronunciation and spelling, and enables fun and student- oprema za učenje besedišča omogočati, da učenci hitro opazijo centered learning. With the Quizlet app, students quickly learn ciljno besedišče, nuditi morajo razlago ciljnega besedišča ter the target vocabulary, as electronic learning cards, various vsebovati raznolike vaje in naloge, preko katerih učenci exercises and games motivate them to work and learn. spoznavajo razne vidike poznavanja besed. Učenci morajo preko nalog spoznavati svoje napake pri rabi besedišča in imeti KEYWORDS možnost, da jih popravljajo [2]. Aplikacija, ki sledi tem načelom Vocabulary learning, foreign language, Quizlet za učinkovito učenje besedišča in jo pogosto uporabljam pri pouku nemščine kot tujega jezika je Quizlet. Aplikacijo uporabljam predvsem za učenje in utrjevanje besedišča in 1 UVOD slovničnih struktur in sicer kot uvodno motivacijo, ob koncu Poučevanje in učenje s pomočjo informacijsko-komunikacijske učne enote kot ponovitev in utrjevanje besedišča ali za tehnologije (IKT) je v zadnjih 15 letih prineslo v slovenski samostojno učenje. prostor velike spremembe, tako pri načrtovanju in izvajanju 3 QUIZLET Permission to make digital or hard copies of part or all of this work for personal or Quizlet je aplikacija za izdelavo digitalnih učnih kartic za classroom use is granted without fee provided that copies are not made or distributed samostojno učenje in ponavljanje, ki omogoča na učenca for profit or commercial advantage and that copies bear this notice and the full osredinjeno učenje. Omogoča preprosto izdelavo kartic z citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). besedno ali slikovno iztočnico v različnih jezikih in izgovorjavo Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia v ciljnih jezikih. © 2020 Copyright held by the owner/author(s). 611 Po brezplačni registraciji na spletni strani Ko je posamezna zbirka kartic narejena, se lahko učenci s http://www.quizlet.com/ nam je na voljo ogromna zbirka pomočjo različnih nalog in iger samostojno učijo. ustvarjenih kartic. V letu 2019 je bilo ustvarjenih že preko 300 Učencem posredujemo povezavo do mape ali razreda, v milijonov zbirk kartic v različnih jezikih. Med temi zbirkami katerem imamo zbirke kartic oziroma jim delimo le posamezno lahko poiščemo ustrezno in jo prenesemo ter prilagodimo lastnim zbirko kartic. To lahko uredimo preko elektronske pošte oziroma potrebam. Ustvarimo pa lahko seveda lastne zbirke kartic. povezavo pretvorimo v QR kodo, do katere enostavno dostopajo. Dodamo pojme, besede, razlage in slike. Ko izberemo ciljni jezik, Zbirko kartic pa lahko delimo tudi v Googlovi učilnici (slika 4). nam aplikacija sama ponudi predloge opisov, prevodov in nabor fotografij, kar omogoča hitro ustvarjanje kartic (slika 1). Slika 1: Ustvarjanje posamezne kartice v Quizletu (Vir: Slika 4: Deljenje zbirke kartic z učenci (Vir: lasten, lasten, zajem zaslonske slike) zajem zaslonske slike) V primeru, da imamo pojme in razlage že zbrane, lahko le-te Ko učenci dostopajo do zbirke, lahko kartice uporabljajo na uvozimo tudi iz Wordove ali Excelove predloge. različne načine: z obračanjem kartic za učenje, z raznimi vajami Poleg ustvarjanja posameznih pojmov in kartic ponuja pisanja in slušnega zaznavanja, s testom in z igrami za aplikacija možnost, da ustvarimo diagram. Izberemo in naložimo preverjanje in utrjevanje (slika 5). ustrezno sliko, na njej označimo točke in vpišemo pojme in definicije (slika 2). Zbirka kartic se samodejno ustvari in je pripravljena za nadaljnje učenje. Slika 2: Primer zbirke kartic z diagramom (Vir: lasten, zajem zaslonske slike) Slika 5: Prikaz možnosti za učenje Za bolj pregledno organizacijo omogoča aplikacija, da si Zavihek learn je namenjen učenju besedišča po skupinah ustvarimo mape ali razrede, v katere nalagamo posamezne zbirke sedmih besed iz celotne zbirke kartic in preverja razumevanje in kartic (slika 3). zapis teh besed. Učenec ob učenju dobi takojšnjo povratno informacijo o pravilnem razumevanju in zapisu. Pod zavihkom flashcards so zbrane vse besedne kartice, ki jih je pripravil učitelj. S klikom na posamezno kartico se učencu prikaže definicija pojma (slika ali opis) in izgovorjava v tujem jeziku. Žal aplikacija izgovorjave v slovenskem jeziku še ne podpira. S plačljivo nadgradnjo pa lahko tudi glasovno posnamemo branje. Zavihek write je namenjen utrjevanju zapisa. Učenec ob prikazu slike ali opisa zapiše pojem in dobi takojšnjo povratno informacijo, ali je zapis pravilen ali ne in kje je napravil napako. Zavihek spell omogoča utrjevanje zapisa slišanih besed, ki so podprte s sliko in definicijo. Učenec dobi povratno informacijo o Slika 3: Primer prikaza organizacije zbirk za pravilnem zapisu in v primeru napačnega zapisa se mu pojem posamezen razred (Vir: lasten, zajem zaslonske slike) črkuje. 612 Zavihek test preverja učenčevo znanje besednih kartic z na telefon, se prijavijo in enostavno dostopajo do dodeljenih raznolikimi vajami in nalogami: zapis besedišča, naloge zbirk. izbirnega tipa, naloge povezovanja, naloge pravilno / napačno. Učenec dobi takojšno povratno informacijo, kaj je rešil pravilno in kaj ne ter katera rešitev je pravilna. Test si lahko tudi natisne oziroma ga pošlje učitelju. Quizlet ponuja tudi tri zabavne igre. Pri igri match učenci povezujejo pojem z razlago oziroma slikovno iztočnico. Pri tem lahko tekmujejo, kdo hitreje najde pare (slika 6). Slika 8: Igra Quizlet Live. Foto: A. Peruš 4 ZAKLJUČEK Slika 6: Igra match (Vir: lasten, zajem zaslonske slike) Quizlet je enostavna in zanimiva aplikacija, ki omogoča različne dejavnosti za lažje in zanimivejše učenje besed, struktur in Pri igri gravity učenci tekmujejo v pravilnem zapisu pojmov pojmov. Pri tujem jeziku ga uporabljam za učenje besedišča od (slika 7). 4. razreda naprej. Uporabljam ga za učenje besedišča in širjenje besednega zaklada. Primeren je za učenje tujega jezika, saj združuje besedišče, razlago, izgovorjavo in črkovanje. Uporabimo pa ga lahko tudi pri drugih predmetih za učenje določenih pojmov. Starejši učenci si lahko sami sestavljajo zbirke kartic in s tem pridobivajo kompetenco učenja učenja. Učenci so za učenje z aplikacijo Quizlet zelo motivirani in besedišče na zabaven način zelo hitro usvojijo. S slušno in vizualno podprtimi učnimi karticami in nalogami je postalo učenje besedišča zabavno in bolj učinkovito. Slika 7: Igra gravity (Vir: lasten: zajem zaslonske slike) VIRI IN LITERATURA Igra Live omogoča sodelovalno učenje, saj so učenci naključno razdeljeni v skupine. Igralci sodelujejo v skupinah, da pravilno dodelijo pojme ustreznim definicijam, saj ima vsak [1] Podgoršek, S. 2015. Pouk tujih jezikov s podporo učenec le del odgovorov (slika 8). Učitelj spremlja napredek informacijske in komunikacijske tehnologije : analiza stanja skupin na računalniku. v slovenskih srednjih šolah. Uporabna informatika, 3, 151- 161. DOI= Quizlet Live pa lahko uporabimo tudi v načinu Single Player, https://www.dlib.si/stream/URN:NBN:SI:DOC- kjer vsak igra proti vsem. W65134HZ/5df646d9-78f7-4480-bf9f-e9fdcd92d16d/PDF Osnovne funkcije aplikacije Quizlet so dostopne brezplačno, [2] Retelj, A. 2015. Pouk tujih jezikov v luči e-gradiv in e- lahko pa si račun nadgradimo na račun učitelja, ki je plačljiv, a storitev: od poučevanja do učenja tujega jezika z IKT. omogoča več prilagoditev in vpogled v delo posameznih učencev. Vzgoja in izobraževanje. 2-3, 73-78. Na voljo pa je tudi mobilna različica aplikacije, kar učencem olajša samostojno učenje doma. Učenci si prenesejo aplikacijo 613 Exploring and promoting digital analysis skil s: Testing optimal conditions of X-ray irradiation (A STEM collaboration example) Raziskovanje in promocija digitalnih veščin: Testiranje optimalnih pogojev rentgenskega obsevanja (primer sodelovanja STEM) Svit Pestotnik Stres Gimnazija Bežigrad Peričeva 4 1000 Ljubljana, Slovenija svit.pestotnik@gimb.org ABSTRACT KLJUČNE BESEDE In this paper, we describe establishing of a digital environment Digitalna technologija, digitalne veščine, analiza podatkov, for analytics in physics experiments. ICT skills are essential in STEM, rentgensko zaznavanje, slikanje, opazovanje establishing the potential for automated or digital analysis in the observation of physics experiments. We have proven that this claim is valid in the case of X-ray detection on a imaging 1 INTRODUCTION phantom. We photographed an irradiated imaging phantom In today's world, knowing digital approaches is increasingly under different initial conditions and tried to compare results crucial. On the other hand, the relationship between the various with each other in terms of different output parameters as optimal branches of science - chemistry, physics, computer science - even voltage used and signal to noise ratio. With the help of in the education system itself is still in its infancy. independently created automated Pyton software for the RGB Interdisciplinarity and cross-curricular integration depend on analysis of the images and using analytical tools as Root and individual initiatives. Particularly noteworthy is the link between Logger Pro programmes, we showed the interdependence information technology and science education to motivate young between the variables in the X-ray imaging. people to STEM content. In this context, digital skills are crucial for establishing closer links between science and education. We KEYWORDS presented one of the options in our paper. Digital technologies, digital skills, data analysis, STEM, X-ray In this paper, we describe an experiment done in collaboration detection, imaging, observation between the International Baccalaureate at the Gimnazija Bežigrad and the Faculty of Physics and Mathematics of the POVZETEK University of Ljubljana. The aim of this experiment was twofold: V tem prispevku opisujemo vzpostavitev digitalnega okolja za firstly, to explore how changing the voltage affects different analitiko v fizikalnih eksperimentih. IKT spretnosti so image quality properties in X-ray Imaging phantom detection; bistvenega pomena pri ugotavljanju možnosti avtomatizirane ali secondly, to explore how and to explore digital tools necessary digitalne analize pri opazovanju fizikalnih eksperimentov. to execute the experiment as a regular study and collaboration Dokazali smo, da ta trditev velja v primeru rentgenskega tool. The experiment and its data analysis allows for an zaznavanja na slikovnem fantomu. Fotografirali smo obsevan exploration of digital tools in STEM experiments and can fantom za slikanje v različnih začetnih pogojih in poskušali med represent a good basis for further collaboration between the seboj primerjati rezultate glede na različne izhodne parametre kot institutions. sta optimalna uporabljena napetost in razmerje signal / šum. S The goal of this research was to prove the correlation between pomočjo neodvisno ustvarjene avtomatizirane programske the voltage applied to the X-ray apparatus and the image quality opreme Pyton za RGB analizo slik in z uporabo analitičnih orodij of the recorded picture. We were also exploring the impact of the kot sta programa Root in Logger Pro smo pokazali soodvisnost distance between the fluorescent screen and the phantom med spremenljivkami v rentgenskem slikanju. irradiated by the x-ray apparatus on the intensity of the light measured. The experiment conducted is based on the theory of X-rays. The rays are produced by an apparatus, where a certain voltage is applied to a X-ray tube that accelerates the electrons towards Permission to make digital or hard copies of part or all of this work for personal or the molybdenum’s anode. The x-ray beams are the result of the classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full interaction of electrons with matter. They are shielded by a citation on the first page. Copyrights for third-party components of this work must collimator so that can only exit the sources at a certain spatial be honored. For all other uses, contact the owner/author(s). angle. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 614 The detection of X-rays was achieved by taking a picture of a fluorescent screen, which emitted fluorescent green light when hit by x-rays, with a camera. The acquisitions had to be taken in complete darkness with a long exposure time to enable enough light to accumulate on the sensor. After the data was converted to numerical form, a double error function was fitted on the 2D response image. The parameters, which I received as an output, were then used in the analysis. 2 METHODS The experiment was performed at the University of Ljubljana, Figure 4. The fluorescent screen Faculty of Mathematics and Physics. I used the experimental 2.1.3 Imaging phantom equipment for the X-ray exercise of the subject Laboratory Imaging phantom, or simply phantom, is a specially designed experiments V [6]. object that is scanned or imaged in the field of medical imaging The detection of the x-ray particles was double-phased. The to evaluate, analyze, and tune the performance of various apparatus used to produce x-rays was “Didaktiksysteme 554811”. imaging devices [3]. The first part of the experiment was acquiring data in the form of A phantom used to evaluate an imaging device should captured photos, whereas the processes and techniques employed respond in a similar manner to how human tissues and organs further on my research are analytical and systematical. would act in that specific imaging modality. For instance, 2.1 X-ray particles detection phantoms made for 2D radiography may hold various quantities of X-ray contrast agents with similar X-ray absorbing properties 2.1.1 X-ray Aparatus - Didaktiksysteme 554811 to normal tissue to tune the contrast of the imaging device or The machine I used to produce X-ray beams for my research is modulate the patients exposure to radiation. In the most simple LD’s Didaktiksysteme “X-ray Aparatus” 554811 [8] (outlay can case, the two different observed tissues can be simulated simply be seen in Fig.1). The maximum operating conditions of the high with two different materials, for example metal coated plastic voltage tube that accelerates particles into the molybdenum’s and air. anode is U=37kV. For safety measures the apparatus used in the The phantom used in this experiment was a plastic board experiment had maximum voltage of 35kV. The maximum covered with a layer of metal, that had holes of different radii current produced by the instrument is 1.0 mA. drilled in. The sizes of the holes were: - 2.0 mm, - 1.6 mm, - 1.4 mm, - 1 mm, - 0.8 mm, - 0.5 mm, - 0.3 mm. Each obstacle was repeated 7 times to allow for some statistical data to be col ected on a particular obstacle (hole) size. Figure 3. X-ray Apparatus overview 2.1.4 Photographic capture of photons 2.1.2 X-ray fluorescent screen The second part of the detection was done by a digital camera. The photographic part of the experiment was covered by two Firstly, a fluorescent screen [7] was used (see Fig.2). The screen layers of black PET foil, because the emitted photons from the x- is a lead glass pane that is coated with a fluorescent layer. The ray detection screen would not be detected accurately when lead glass forms a tight radiation seal, however, the photons mixed up with the sunlight. The camera used in this experiment produced by the removal of electrons in the atoms of the coating is Nikon D40 The exposure time was determined by a series of can still travel through the screen. This phenomenon is used to trials, and set to 6 seconds to achieve the optimum of the number detect the X-rays colliding with the screen. of photons captured. The setup can be seen from Fig. 3 and a sample outcome of a photograph taken of a phantom is shown in Fig. 4 and 5. 615 outputting values the analysis over the whole picture was done. The program tried to fit an error function [4] on the 2D response. Borders of such a signal is usually treated as a Gaussian function [5], so when a number of signals are treated together as one signal, convolution of the point response with the image shape makes the borders take form of an error function. The fitting of an error function was in my case used all around the given circular 2D signal (Fig.6). Figure 5. The experimental setup- camera 2.2 Analysis It has soon become clear that without digital tools the observation of the processes taking place in the imaging phantom and the setup as a whole would be impossible on the level of accuracy requested to draw reliable conclusions. Thus the second aim of the study was to use existing and to develop missing digital tools to enable RGB analysis of the images taken. 2.2.1 Python script- image color processing & Figure 8. 2D histogram of a captured photo The photos taken by the camera were then transferred to a computer, where further analysis was carried out. The captures The outputs that determined the double error function were: were analyzed using a Python script that determines a specific RGB light composure of a certain pixel on a straight line, whose - A, the height of the signal, direction and extremes are provided by the user. The result of the - W, the width of the signal, image color processing is a graph of light intensity in the - B, the height of the background, correlation with coordinate of the pixel explored. The base code - ∂, the width on the half of the height of the graph od was found on the internet [1] and was then changed so that it derivative of the error function suited my experiment’s needs. 2.2.2 Root script- intensity analysis and image splitting 2.2.3 LoggerPro analysis ROOT [2] was in this experiment used in two parts of analysis. The data acquired from the analysis by the code in Python and Firstly, the picture of the phantom had to be split up in several ROOT can be transferred to LoggerPro by importing the data as smaller pictures, which were only showing one hole in the a text file with different columns. After the data is appropriately phantom at a time. This step was required to enable easier represented, we can identify the average height of the signal and management with the original data. Other processes in the the average width of the border by using cursor coordinates analysis were then run on large amount of very similarly displayed by LoggerPro. The data gathered was then presented structured photos, which enabled the code to be less complicated. in the table to show the correlation. Graphs were drawn to explore different dependences. 3 RESULTS The images captured using the phantom with holes and the above described setup (Fig.3), were analyzed using the described digital tools. Our goal was to determine the sharpness of the holes’ images. The results acquired from the exploration were firstly in the form Figure 6. Irradiated phantom Figure 7. Image splitting of pictures (see example in Fig.7). After the analysis using the developed Python programming tools the results had a numerical Secondly, the color analysis done in ROOT analysis form, since they represented an average width of the signal and framework is similar to the one in Python. However, in this case the average height. Both obtained values are an important test of the options for the analysis are much wider. A light composition the sharpness of the picture border and the quality of the photo. analysis investigation can be done over the x-, y- axis and over the whole picture. To achieve the highest accuracy of the 616 We can clearly see that there is a constant increase in signal/background’s ratio, when the voltage is around 23kV. The picture that was analyzed had the best contrast among the other. If we compare the pictures at the bottom, we can clearly see that the graph drew us to a reasonable conclusion. The picture on the left was the one, where the x-ray particles were accelerated by a 23kV of voltage, whereas the right picture was captured with the irradiation of x-ray accelerated by 35kV voltage. The contrast on the left one is much greater than on the capture with higher input energy. Figure 9. Example of analyzed material (left) Figure 10. Python color intensity test (right) After the ROOT script was run on a set of little pictures, as presented above, the code tried to find the best fit for the mentioned double error function. The parameters that root used to find the best correlation, were then exported to a .txt file, where they could be used for further analysis. On the pictures captured with the lower input voltage the smallest holes of the size of 0.5mm were really hard to see and Figure 11. Captured photo of high contrast (left) the analysis of light intensity on those was not returning Figure 12. Captured photo of low contrast (right) consistent results. That is why I decided to perform the research only on the remaining 6 different sizes of gaps (0.8mm, 1mm, 3.2 Resolution dependence on the voltage 1.4mm, 1.6mm and 2mm). σ The voltages used in this experiment are displayed in the table is a parameter of the error function that essentially tells us how below: steep the border between the peak of the signal and background of the measurement is. It represents the width of a derivative function of the error function. The width of the derivative is a Table 3.Accelerating voltages used on the X-ray apparatus Trial no. 1 2 3 4 5 6 statistical value that tells us how well the border of the picture was captured, the quality of the image can be described. Voltage [kV] 35 32 29 26 23 20 The aim of this experiment was to explore how changing the voltage affects different image quality properties. 3.1 Signal to background’s dependence on the voltage Signal to backgrounds ratio is often a good criterion showing the Figure 13. Error function (left) quality of the picture taken. It represents the contrast between the Figure 14. Average width of the derivative function of the background light intensity and the details in the front. Since two error function (right) outputs from the root code were parameters A and B, respectively the intensity of the signal and the intensity of the background, a dependence of the ratio of the two was explored. The data that was processed with the mentioned codes After the process of averaging the data of different shots taken resulted in the graph, where the sigma-value does not increase or by Python, the numbers were transferred to LoggerPro. The decrease with the variation of voltage. There was no found graph drawn by the program is shown below. correlation since the changes in the values with different voltages are probably a result of a statistical error. The data gathered and averaged is collected in the table and the graph below. Table 4. σ's average values for different gap diameters and voltages Diameter of the 2 1.6 1.4 1 0.8 0.5 hole [mm] / Voltage [kV] 35 3.07 3.43 3.47 3.38 3.63 3.72 32 3.03 3.45 3.46 3.46 3.60 6.04 29 3.00 3.44 3.47 3.41 3.11 3.54 Graph 1. Correlation of light contrast with voltage 617 26 3.21 3.66 3.70 3.49 3.68 2.97 the experiment was performed optimally, and the results are quite relevant as they show how and to what degree digital skills are 23 2.92 3.33 3.48 3.17 3.28 3.55 important in analysis of data obtained in physics experiments. 20 3.93 4.39 4.46 8.93 10.17 4.01 5 CONCLUSION My initial thesis for the first part was that neither the pictures captured while phantom is irradiated by the highest nor the lowest voltage will have the highest contrast value, the signal to background ratio. I can say that my expectations for the results were that one of the pictures with lover voltage input will be the candidate for the highest ratio of contrast. After the exploration, I can with great certainty say that both my theses were correct, and my research only supported them. My initial thesis for the second part was, that the values gathered for the σ- parameter would imply optimal conditions based on the fact that the mentioned value would depend on the voltage that was varied. However, the numbers for σ I got do not point to such conclusions. In the experimental environment I was Graph 2. σ 's correlation with voltage working in there was no correlation between σ and U found. My We can clearly see that the differences between the values are second thesis therefore was incorrect and the evidence I got, not the consequence of the variation of voltage. proves that picture quality of the signal-background border does not vary with the inputted voltage. In conclusion, my first thesis was correct, while my second 4 DISCUSSION one was incorrect. The results I got are supported by a large There are several things I would like to address regarding the amount of data, which leads me to believe that the conclusions I accuracy of this experiment. To point out, the experiment was have drawn are relevant as well. performed manually so there were numerous procedures I had to Ultimately, the results could not have been obtained without go through and where mistakes were made. Errors in final data using digital skills. STEM collaboration between high school and are most probably results of such oversights. experts with highly developed digital skills is of utmost Firstly, the layer that covered the camera and prevented the importance in order to firstly promote digital skills at a relatively light from disturbing the sensor was on some spots torn apart, so early age of students, and secondly, to enable the students to learn the impact of the light cannot be fully negligible. them and use them in real-experimental setups, measurements Further on, the camera had to be focused on the fluorescent and analysis. screen before its cover was taken off under the mentioned black layer. This could also be a reason for inaccurate pictures captured. ACKNOWLEDGMENTS Moreover, the X-rays with the accelerating voltage below 23kV often did not have enough energy to collide with the atoms My thanks to University of Ljubljana, Faculty of Mathematics in the fluorescent layer enough so that a sufficient amount of light and Physics for letting me use their x-ray apparatus, used for the would be emitted. That is why measurements at the voltage of subject Laboratory experiments 5, and for all advice on how to 20kV are prone to high relative errors, and the trials with the approach the analysis of data. voltage of 18kV had to be discarded altogether. The last thing that I feel could easily be improved if I had REFERENCES more time and resources, are the analysis codes. The ROOT and Python analysis scripts I ran on captured photos often did not [1] Python Math: Convert RGB color to HSV color. [internet]. give very accurate output, because the starting parameters were [cited on March 30, 2020]. Available from: not set correctly. Even though I worked on improving the code https:/ www.w3resource.com/python- to the point, where the efficiency and reliability was relatively exercises/math/python-math-exercise-77.php. high, there were still some cases where the code using the [2] ROOT analysis programme. [internet]. [cited on described models did not converge with the initial parameters September 05, 2020]. Available from: http://root.cern.ch. provided. Especially the part of the experiment, where the Root [3] Imaging Phantom. [internet]. [cited on September 06, script was finding optimum double error function to fit on the 2020]. Available from: given data, was problematic, since a small difference in the way https://en.wikipedia.org/wiki/Imaging_phantom. function was structured had major impact on the output [4] Derivative of an error function. [internet]. [cited on parameters. September 05, 2020]. Available from: To conclude, the experiment could of course be performed https:/ www.numberempire.com/graphingcalculator.php?f more efficiently, professionally, accurately, the errors could be unctions=erf%28x%29%2C%282%2A%25e%5E- minimized. However, I believe that with given time, resources x%5E2%29%2Fsqrt%28%25pi%29. and my non-existing previous experience with such machinery, 618 [5] Error function. Wikipedia. [internet]. [cited on September [7] Fluorescence. Wikipedia. [internet]. [cited on September 05, 2020]. Available from: 05, 2020]. Available from: https://en.wikipedia.org/wiki/X- https://en.wikipedia.org/wiki/Error_function. ray_fluorescence. [6] Fizikalni praktikum 3. Poskusi z žarki. [internet]. [cited on [8] Instruction sheet 554 811. X-ray Apparatus. [internet]. September 05, 2020]. Available from: [cited on September 05, 2020]. Available from: http://predmeti.fmf.uni- https://www.ld-didactic.de/documents/en- lj.si/fizprak3?action=AttachFile&do=get&target=Xzarki.p US/GA/GA/5/554/554811e.pdf?__hstc=98968833.1bb630 df. f9cde2cb5f07430159d50a3c91.1530662400075.15306624 00076.1530662400077.1&__hssc=98968833.1.153066240 0078&__hsfp=1773666937. 619 Uporaba IKT pri pouku športne vzgoje v času dela na daljavo Use of ICT in physical education classes during distance work Anja Pirc Gimnazija Bežigrad Peričeva ulica 4 1000 Ljubljana, Slovenija anja.pirc@gimb.org POVZETEK year, when working remotely forced us to find the most effective means to cooperate and connect with students. In my work I Uporaba informacijsko-komunikacijske tehnologije v procesu strive mainly for practical lessons and movement, so in the past izobraževanja na Gimnaziji Bežigrad poteka že vrsto let. Številni I thought the use of online classrooms and other ICT tools makes učitelji pri svojem pouku že dolgo uporabljajo različna IKT- much more sense in other subjects than in Physical education. orodja, s katerimi si lajšajo delo ter izboljšujejo kakovost pouka. The introduction of distance learning in the past school year has V zadnjem času je v porastu zlasti uporaba spletnih učilnic posed new challenges for all of us, especially for Physical Moodle. Sama sem se spletnimi učilnicami seznanila že pred leti, education teachers, who use such forms to a lesser extent than intenzivno pa sem jih začela uporabljati v zadnjem šolskem letu, teachers of other subjects do. After a few months of intensive use, ko nas je delo na daljavo prisililo v iskanje čim bolj učinkovitih both online classrooms and various video conferencing platforms sredstev za sodelovanje in povezavo z dijaki. Pri svojem delu (Zoom, Skype) proved to be indispensable in the implementation stremim pretežno k praktičnem pouku in gibanju, zato se mi je v of lessons, both in terms of theoretical and practical work. preteklosti zdela uporaba spletnih učilnic ter drugih IKT orodij Conversation with students, their active presence and veliko bolj smiselna pri ostalih predmetih kot pri športni vzgoji. participation in online classrooms and video conferences showed Uvedba pouka na daljavo v preteklem šolskem letu pa je pred vse that they could be of great help in conducting lessons. nas postavila nove izzive, še zlasti za učitelje športne vzgoje, ki tovrstne oblike dela uporabljamo v manjši meri kot učitelji KEYWORDS ostalih predmetov. Po nekaj mesecih intenzivne uporabe so se tako spletne učilnice kot tudi različne videokonferenčne Online classroom, physical education, distance learning, high platforme (Zoom, Skype, Teams) pri izvedbi pouka izkazale za school, ICT nepogrešljive, tako z vidika teoretičnega kot praktičnega dela. Pogovor z dijaki, njihova aktivna prisotnost in sodelovanje v 1 UVOD spletnih učilnicah ter na videokonferencah so pokazali, da so le- te lahko v veliko pomoč pri izvedbi pouka. Informacijsko-komunikacijska tehnologija je v zadnjem času postala nepogrešljiv del izobraževalnega procesa. Delavci v KLJUČNE BESEDE vzgoji in izobraževanju ves čas stremimo k izboljšanju kakovosti Spletna učilnica, športna vzgoja, pouk na daljavo, srednja šola, izobraževanja, zato iščemo nove poti in izzive, ki bi nas pripeljali IKT k temu. Opremljenost šol z informacijsko-komunikacijsko tehnologijo je vedno boljša, povečuje se usposobljenost učiteljev ABSTRACT za uporabo tovrstne tehnologije, vedno večja pa je tudi ponudba The use of information and communication technology in the ustreznih izobraževalnih gradiv v te namene. Spletne učilnice in process of education at the Gimnazija Bežigrad has been going videokonferenčne platforme so le del tovrstne tehnologije, ki on for many years. Many teachers have long used various ICT pripomorejo k večji učinkovitosti izobraževanja in s pomočjo tools in their lessons to facilitate their work and improve the katerih lahko izboljšamo pouk, saj omogočajo sodelovanje quality of lessons. Recently, the use of Moodle online classrooms dijakov in učiteljev tudi izven šolskega prostora. Zadnji meseci has been on the rise. I became acquainted with online classrooms preteklega šolskega leta so pred učitelje osnovnih in srednjih šol years ago but I started using them intensively in the last school postavili poseben izziv, in sicer kako ostati v stiku z učenci od doma, kako jim nuditi čim bolj kakovosten pouk na daljavo ter kako spremljati njihovo delo in napredek. Zlasti spletne učilnice so pri tem odigrale pomembno vlogo. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 620 2 SPLETNE UČILNICE, 3 UPORABA SPLETNE UČILNICE VIDEOKONFERENČNE PLATFORME MOODLE IN OSTALIH IKT-ORODIJ PRI TER DRUGA ORODJA PRI UČENJU NA ŠPORTNI VZGOJI DALJAVO S spletno učilnico Moodle sem se srečala že pred leti, ko sem se 2.1 Učenje na daljavo na šoli udeležila izobraževanja o njeni uporabi. Dolgo časa sem O učenju na daljavo govorimo, ko učitelj in učenec nista hkrati menila, da spletne učilnice za svoj predmet ne potrebujem, saj prisotna na istem mestu. Ločeni so lahko v času in prostoru, sem pri športni vzgoji vedno dajala prednost praktičnem delu. sodelovanje pa se vzpostavlja z uporabo IKT. Pri izobraževanju Pred nekaj leti pa sem začela poučevati tudi v oddelku na daljavo se učenec uči samostojnega učenja, prilagojeno je mednarodne šole, kjer se sistem poučevanja in ocenjevanja učenčevim prostorskim in časovnim omejitvam ter precej razlikuje od tistega, na katerega sem bila navajena v sposobnostim, gradiva se lahko sprotno popravljajo in gimnaziji. V programu mednarodne šole se dijaki srečujejo z dopolnjujejo, dostopni so tekoči podatki … Učenje na daljavo veliko več teoretičnimi vsebinami, precej pa je tudi oddajanja pa ima tudi nekaj slabosti, kot so manjši nadzor nad učencem – različnih teoretičnih nalog, poročil in načrtov. Ker je bilo teh potrebna je precejšnja samodisciplina, dolgotrajno sedenje pred vsebin in nalog veliko, sem se odločila, da počasi tudi sama zaslonom, pomanjkanje socialnih stikov z drugimi učenci, začnem uporabljati spletno učilnico. usposobljenost sodelujočih za uporabo tehnologije, vprašljivo pa je tudi preverjanje znanja [1]. 3.1 Uporaba spletne učilnice pri delu na daljavo Če se je v preteklosti izobraževanje na daljavo uporabljalo Na začetku sem spletno učilnico uporabljala predvsem v namene predvsem kot dopolnilna oblika dela klasičnemu učenju, smo se nalaganja pisnih navodil ter oddajo nalog. S tem sem si precej ga bili v preteklem šolskem letu prisiljeni poslužiti vsi učitelji. olajšala stvari, saj so imele dijakinje teoretične vsebine in Epidemija korona virusa in s tem posledično zaprtje šol sta nas navodila vedno na voljo, zato sem si prihranila čas s ponovno prisilila v to, za marsikoga novo obliko dela. Kljub številnim razlago. Kasneje pa sem ugotovila, da mi spletna učilnica ponuja dilemam, ki so se pojavljale na začetku, menim, da se je v dani veliko novih možnosti za podajo učne snovi. Kar se je izkazalo situaciji izobraževanje na daljavo izkazalo za kar učinkovito uporabno zlasti pri učenju na daljavo v preteklem šolskem letu. obliko dela. Zaradi tuje govorečih dijakov je besedilo spletne učilnice v angleškem jeziku. 2.2 Spletna učilnica Moodle Mojo spletno učilnico je sestavljalo sedem poglavij. Poglavja Spletna učilnica je namenjena sodelovanju učiteljev in učencev so se navezovala na posamezna obdobja oziroma tematske izven klasičnega pouka, izven učilnice. V tem virtualnem okolju sklope, ki smo jih predelali pri športni vzgoji. Prvo poglavje se se srečujejo učenci in učitelji s pripravljenimi učnimi vsebinami. je nanašalo na tematski sklop fitnes (Slika 1). Dijakinje so morale Učencem so v spletni učilnici na voljo različna orodja za v obdobju, ko smo imeli na programu fitnes, pripraviti osebni izobraževanje, kot npr. povezave na spletne strani, datoteke z vadbeni program. Navodila za izdelavo programa so bila v različnimi vsebinami, ki se lahko prenašajo v obe smeri (od spletni učilnici, tako da so jim bila vedno dostopna. Svoj program učitelja k učencu ter obratno), forumi, ki omogočajo so morale oddati v nabiralnik prvega poglavja, kjer so si kasneje komunikacijo pa tudi različni kvizi, ki jih učenci lahko rešujejo. lahko tudi ogledale svojo pridobljeno oceno. Po enem mesecu Naloge, ki jih učenci oddajajo, lahko učitelj v spletni učilnici tudi dela v fitnesu so morale dijakinje napisati evalvacijo na svoj plan oceni, učenci pa si jih lahko kadarkoli tudi ogledajo [2]. vadbe in njegovo učinkovitost ter tudi evalvacijo oddati v poseben nabiralnik prvega poglavja. Prav tako so morale oddati 2.3 Videokonferenčne platforme in druga primer ogrevanja, ki so ga pripravile po navodilih. orodja Videokonferenčne platforme, kot sta Zoom in Skype, omogočajo, da se lahko večje število ljudi, ki so vsak na svoji lokaciji, sreča v živo, ob istem času [3]. Sama sem za namene srečanja z dijaki v živo, pogovor z njimi, razlago snovi ter ocenjevanje večinoma uporabljala Zoom. Ker pred tem nisem imela potrebnih izkušenj in znanja o uporabi videokonferenčnih platform, se mi je Zoom zdel najlažji za uporabo, brez težav pa so ga osvojili tudi dijaki. Pri svojem delu na daljavo sem pogosto uporabljala tudi spletno aplikacijo Kahoot. Gre za preprosto in učinkovito motivacijsko orodje za mlade, ki popestri učni proces [4]. Uporabljala sem ga predvsem za popestritev učnega procesa na daljavo ter za ponavljanje in utrjevanje predelane snovi, uporabila pa sem ga tudi za ocenjevanje. Slika 1. Tematski sklop fitnes 621 Drugo poglavje se je nanašalo na tematski sklop odbojka. Poglavje 5 je bilo namenjeno teoretičnim vsebinam, ki bi jih Dijakinje so od teoretičnih vsebin v tem sklopu morale poznati z dijakinjami morala predelati med praktičnim delom v šoli. sodniške znake pri odbojki. To poglavje je vsebovalo povezavo Namesto tega so v spletno učilnico prejemale dokumente s do spletne strani, ki prikazuje omenjene sodniške znake (Slika 2). teoretičnimi vsebinami, kjer so bila opisana pravila posameznih Pri plesu in ritmični gimnastiki so morale dijakinje sestaviti športnih panog, tehnični in taktični opis športa ter povezave do lastno plesno ali ritmično gimnastično sestavo. V ta namen sem spletnih strani, kjer so si dijakinje lahko ogledale pravilno jim pripravila navodila, ki so jih imele vedno na voljo v spletni izvedbo posameznih tehničnih in taktičnih elementov nekega učilnici pod poglavjem tri. Svoj načrt za sestavo so morale oddati športa (Slika 4). v poseben nabiralnik, prav tako pa tudi evalvacijo prikazane sestave na koncu tega tematskega sklopa (Slika 2). Slika 4. Poglavje z nekaterimi teoretičnimi vsebinami Za dokazilo o opravljeni vadbi so morale dijakinje vsak konec tedna napisati krajše poročilo o svojem delu za športno vzgojo ter aktivnostih, ki so jih opravile doma. Poročila so morale oddati v poseben nabiralnik v poglavju 6 (Slika 5). Tudi tukaj se je spletna učilnica Moodle izkazala za zelo uporabno, saj sem lahko sproti preverjala, kdo je poročilo oddal in kdaj. Postavila sem Slika 2. Tematska sklopa odbojka in ples z ritmično roke za oddajo posameznih poročil, dijakinje pa so vseeno imele gimnastiko možnost poročila oddati tudi naknadno. Na ta način sem lahko spremljala njihovo sprotno delo, hkrati pa jim omogočila, da so Na začetku šolskega leta sem nameravala v svoji spletni zaradi obilice drugega dela poročila oddale tudi kakšen dan učilnici zapolniti samo prva tri poglavja, saj za druge tematske kasneje. sklope nisem imela v načrtu ocenjevanja in preverjanja pisnih teoretičnih vsebin. Zaradi zaprtja šol in posledično dela na daljavo pa sem svojo spletno učilnico razširila. Z dijakinjami sem v tem času komunicirala pretežno preko spletne učilnice ter občasno Zooma. Četrto poglavje je tako vsebovalo navodila za delo. Dijakinje so vsak teden v spletno učilnico prejele navodila za delo, ki so se večinoma nanašale na osnovno telesno pripravo, kar so lahko izvajale doma. Posamezna navodila so bila označena z datumom, dijakinje pa si jih lahko odprle s klikom (Slika 3). Slika 5. Nabiralnik za oddajo poročil o aktivnostih Zadnje poglavje v spletni učilnici je bilo namenjeno medpredmetni povezavi. S kolegom, ki v tem razredu poučuje zgodovino, ter kolegom, ki poučuje športno vzgojo dijake, smo Slika 3. Poglavje z navodili za delo med učenjem na daljavo februarja pričeli z medpredmetno povezavo na temo antičnih olimpijskih iger. Ker nam je izvedbo celotne povezave v šoli 622 onemogočila karantena, smo se jo odločili nadaljevati na daljavo. veseljem, saj so jim popestrili pouk, med sabo pa so tudi To je bila precej zahtevna naloga, saj je bilo potrebno hkrati tekmovali (Slika 7). zbrati veliko več dijakov in spremeniti celoten potek ter Kvize sem sestavila na različne načine. Običajno je šlo za zaključek medpredmetnega povezovanja. Veliko smo z dijaki klasično obliko kviza s štirimi možnimi odgovori (Slika 8). Z sodelovali preko Zooma, zopet pa se je za nepogrešljivo pokazala dijaki sem se povezala preko Zooma, na mobilnih telefonih pa so spletna učilnica, kamor so dijaki prejeli teoretične vsebine, ki reševali kviz. Vsako vprašanje je bilo časovno omejeno. Med smo jih predelali že v šol in so bile temelj za zaključno seboj so tekmovali v poznavanju teoretičnih vsebin športa, na ocenjevanje ter navodila za ocenjevanje. V nabiralnik tega koncu pa smo dobili zmagovalca. To obliko kviza sem uporabila poglavja so morali oddajati tudi svoja poročila o delu v povezavi tudi pri ocenjevanju teoretičnih vsebin, saj se na koncu izpiše z medpredmetno povezavo (Slika 6). Samo ocenjevanje smo celotna statistika. Vpogled imamo število pravilno rešenih izpeljali v več delih (da smo lahko pokrili vse štiri kriterije, ki se vprašanj, za vsakega dijaka pa odstotek pravilnih rešitev. jih pri medpredmetnem povezovanju na mednarodni šoli Kadar pa nisem želela, da dijaki med seboj tekmujejo ali se z ocenjuje). Uporabili smo tudi spletno aplikacijo Kaoot, kjer so njimi nisem povezala preko Zooma, sem kviz sestavila v obliki dijaki reševali kviz. izziva. Kviz sem časovno omejila, kar pomeni, da so dijaki imeli na voljo nekaj dni, da so začeli z reševanjem. Po določenem datumu se je kviz zaprl in reševanje ni bilo več mogoče. Na ta način sem dijakom omogočila, da so vprašanja rešili, kadar so želeli. Tudi ta oblika se je izkazala za pozitivno, saj so si dijaki lahko sami zbrali tisti čas za reševanje, ki jim je najbolj ustrezal. Ta oblika kviza pa je vsekakor primernejša tudi za tiste dijake, ki ne želijo tekmovati, saj jih to postavlja v stresno situacijo. Slika 6. Poglavje za medpredmetno povezavo 3.2 Uporaba ostalih IKT orodij pri delu na daljavo Za srečevanje z dijaki sem v času dela na daljavo večinoma uporabljala videokonferenčno platformo Zoom. Občasno sem se poslužila tudi Skypa, vendar se je izkazalo, da je dijakom Zoom Slika 7. Primer Kahoot kviza z nekaj vprašanji o odbojki bližje, bolj enostavna pa se mi je zdela tudi njegova uporaba. Z dijaki sem se preko Zooma načeloma srečevala enkrat tedensko, nekajkrat pa sem poskusila izvesti tudi uro športne vzgoje. Šlo je večinoma za prikaz različnih vaj v sklopu osnovne motorične priprave. To je bil malo večji izziv, saj je bilo potrebno precej iznajdljivosti, kako postaviti računalnik, da me bodo dijaki videli med vsemi izvedbami, hkrati pa sem tudi jaz morala videti njih, da sem jih lahko popravljala. Tukaj so nastajale težave, saj se nam je večkrat zgodilo, da so dijaki zaradi slabe internetne povezave izgubili sliko, ali pa sem jo izgubila jaz. Pojavljale pa so se tudi težave z zvokom. Po nekaj poskusih smo ugotovili, da Slika 8. Primer vprašanja z možnimi odgovori pri Kahoot Zoom ni najprimernejša oblika za vodenje vadbe v živo, zato smo kvizu to opustili. Za zelo uporabno stvar pri učenju na daljavo pa se je izkazala 4 ZAKLJUČEK spletna aplikacija Kahoot. Po nekaj tednih dela sem želela popestriti učni proces ter preveriti znanje dijakov. Zanimalo me Informacijsko-komunikacijska tehnologija vstopa v vsa je, kako lahko pouk na daljavo naredim zanimivejši ter koliko so področja našega življenja. Vedno bolj je prisotna tudi v se dijaki v tem času sploh naučili. Na predlog sodelavca sem izobraževalnem procesu, s tehnologijo pa živijo tudi sodobni poskusila s Kahootom. Takoj sem bila zadovoljna z njim, saj se otroci in mladostniki. Učencem moramo ponuditi nove in je izkazal za zelo lahko učljivega in tudi dijaki so ga hitro osvojili. sodobne oblike poučevanja, ki jih bolj motivirajo in pritegnejo k Kahoot ponuja številne možnosti za izvedbo različnih kvizov, s učenju, hkrati pa tudi učitelju olajšajo delo. Kljub težavam, ki katerimi lahko preverjamo znanje dijakov in ga po potrebi tudi smo jih imeli zaradi učenja na daljavo, sem se iz te izkušnje ocenimo. Sama sem v te namene sestavila kar precej kvizov, s veliko naučila. Spoznala sem kar nekaj novih orodij za pomoč katerimi sem preverjala znanje dijakov o posameznih športnih pri poučevanju in popestritvi dela. Naučila sem se uporabljati panogah ter splošni motorični pripravi. Dijaki so kvize reševali z Zoom, sestavljati kvize v Kahoot aplikaciji ter nadgradila svoje znanje o uporabi spletnih učilnic. Vse se je izkazalo za zelo uporabno in dobrodošlo kot pomoč pri učenju. Pouk v učilnici 623 oziroma v mojem primeru v je še vedno tisti, ki je za doseganje [2] Damjan Bratkovič. 2001. Kako uporaba spletne učilnice vzgojnih, procesnih in izobraževalnih ciljev najpomembnejši in spodbuja interaktivni odnos med učencem in učiteljem v je z vidika poučevanja, učenja in socialnih stikov tudi osnovni šoli Stopiče. Diplomska naloga. Fakulteta za najprimernejši. Vendar pa nam je IKT pri vsem tem lahko v informacijske študije v Novem mestu, Slovenija. veliko pomoč. Tako z vidika motivacije kot dopolnitve k [3] Jovanović, M. M. 2020. Kako se udeležiti eDogodka v živo poučevanju ter olajšanju dela. Tudi sama bom IKT v večji meri preko Zoom-a na računalniku. vključevala v svoje delo. https:/ www.edogodek.si/sodobno-ucenje/zoom-preko- racunalnika/. [4] Slovensko izobraževalno omrežje. 2020. Popestrite učni VIRI proces z uporabo aplikacije Kahoot! [1] Batagelj, V. 1999. Analiza možnosti uporabe IKT pri https://podpora.sio.si/popestrite-ucni-proces-z-uporabo- podpori izobraževanja na daljavo v osnovni in srednji šoli. aplikacije-kahoot/. http://www.educa.fmf.uni- lj.si/izodel/dela/mirk/mirkanap.htm. 624 Digitalni umetniki ali pouk na daljavo Digital artists or distance learning Tatjana Praprotnik Žaucer OŠ Draga Kobala Maribor Tolstojeva ulica 3 2000 Maribor, Slovenija tatjanap@osdk.si POVZETEK unknown. At the given moment, new goals were set, to teach the student to organize, to be independent and responsible, to master Za usvajanje znanja pri učencih iščem različne načine the digital technique of entering online classrooms, the e-mail, to poučevanja, ki jih motivirajo. Pouk na daljavo je zaradi svetovne know how to give feedback and in doing so to learn the provided zdravstvene situacije pomenil nov izziv, postavljanje novih ciljev, teaching material. tudi nemoč, strah, predvsem pa plavanje v neznano. V danem trenutku so bili zastavljeni novi cilji, kjer se nauči učenca, da se During school lessons I am not limited by the choice of working organizira, je samostojen in odgovoren, obvlada digitalno methods, in distance learning I am; so I mostly used tehniko za vstop v spletne učilnice, e-pošto, zna dati povratno brainstorming, the method of explanation for later individual informacijo in se pri tem uči posredovano snov. student work, presenting one's own experiences, and getting results. The key to success was in one's own organization, Pri pouku v šoli z izbiro metod dela nisem omejena, pri pouku systematicity, and in transforming information into something na daljavo sem; tako sem največkrat uporabila možgansko useful. During distance learning, I improved my skills, nevihto, metodo razlage za kasnejše individualno delo učencev, exchanged experiences with my colleagues in the working group predstavitve lastnih izkušenj in pridobivanje rezultatov. Ključ and other colleagues at school, and sought information from uspeha je bil v lastni organiziranosti, sistematičnosti in v teachers at other schools. The problem arose with students who preoblikovanju informacij v nekaj uporabnega. V času pouka na have no expectations, are not independent and do not have daljavo sem se izpopolnjevala, izmenjavala izkušnje s parental support due to workload or antisocial environment. sodelavkami v aktivu in na šoli, iskala informacije pri učiteljicah na drugih šolah. Problem je nastal pri učencih, ki nimajo The key to success was in personalization, as students with clear pričakovanj, so nesamostojni in nimajo podpore staršev zaradi goals were not limited in time, with classmates and they did all službene obremenjenosti ali nesocialnega okolja. the planned tasks responsibly and independently, independently searched for connections with already known material and were Ključ uspeha je bil v personalizaciji, saj učenci z jasnimi cilji creative. Working with each one individually enabled personal niso bili omejeni v času, s sošolci in so odgovorno in samostojno development with the student’s expectations, talents, and needs. naredili vse načrtovane naloge, neodvisno iskali še povezave z With additional teacher training and with the exchange of že znano snovjo in bili kreativni. Delo z vsakim posebej je experiences, I will certainly be able to improve distance teaching omogočalo osebnostni razvoj z učenčevimi pričakovanji, talenti in the future, which will be done even more tailored to the student. in potrebami. Z dodatnim izobraževanjem in z izmenjavo izkušenj bom zagotovo v prihodnje lahko izboljšala poučevanje KEYWORDS na daljavo, ki bo opravljeno še bolj po meri učenca. Distance learning, learner, learning, online classrooms, KLJUČNE BESEDE communication Pouk na daljavo, učenec, učenje, spletne učilnice, komunikacija ABSTRACT 1 UVOD To acquire knowledge in students, I look for different ways of Za nami je izjemno in nenavadno šolsko leto 2019/20, ki je teaching that motivate them. Due to the global health situation, zahtevalo nov način dela, drugačen pristop do učencev, distance learning meant a new challenge, setting new goals, kreativnost in veliko delovne discipline. Čas od 16. 3. do 22. 5. including helplessness, fear, and above all, swimming in the (pouk od doma) oz. do 29. 5. 2020 (pouk od doma in v šoli) je pokazal, koliko so učenci samostojni, vešči dela z računalnikom in kako pomembno je delo učitelja pri izobraževanju. V veliko pomoč je učencem bilo zagotovo poznavanje spletnih učilnic, ki Permission to make digital or hard copies of part or all of this work for personal or jih uporabljam že od leta 2012. Namenjene so bile dodatnemu classroom use is granted without fee provided that copies are not made or distributed delu z učenci, kjer so našli naloge za sodelovanje na for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must Cankarjevem tekmovanju, poglabljali znanje za nacionalno be honored. For all other uses, contact the owner/author(s). preverjanje znanja v 6. in 9. razredu. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 625 Postavljeni smo bili pred nov izziv, kjer smo se lahko zanesli ravnanje književne osebe, znali poiskati o čem predvsem govori na svoje znanje, izkušnje in naša šola tudi na vodstvo. V aktivu besedilo, raziskovali slog pisanja, prepoznali zvrst in poustvarjali za slovenščino smo prevetrili učni načrt, sprejeli smernice z nadaljevanjem zgodbe, spreminjanjem celotne zgodbe ali vodstva šole, kjer je manj pomenilo več. Učencem smo namenili zapisali tvorbno nalogo. Pri poeziji so iskali pesniška sredstva, delo, ki bo sprejemljivo razmeram, njihovim sposobnostim in rimo, zgradbo pesmi in se preizkusili v kovanju rim. O avtorju računalniški opremi. Z učenci smo se pred zaprtjem šol so zapisali najosnovnejše podatke: književno obdobje, pomen, pogovorili o načinu dela jim vlili moči in upanje, da zmoremo. poklic, dela in kakšno zanimivost iz življenja. Izdelali so Povedali smo jim, da je pouk na daljavo njihova pravica in literarno izkaznico ali plakat. Naloge so bile razdeljene na odgovornost in to niso počitnice. Učenci so preverili dostop do obvezne za zadostitev temeljnih standardov znanja in tiste za svoje elektronske pošte, osvežili prvo stran zapisa v zvezku (moj učence, ki jim je slovenščina močno področje. Razlika se je e-naslov, možnost dostopa do spletnih učilnic, do e-DZ Založbe pokazala v zahtevnosti razmišljanja globine besedila, Rokus Klet in spletne strani Devetletka). jezikovnem znanju in njegovi rabi. Učenci s primanjkljaji so usvojili le minimalne standarde. 2 DELO NA DALJAVO 2.1 Spletne učilnice Poučujem od 6. do 9. razreda slovenščino, učenci so vešči računalnika bolj kot njihovi mlajši vrstniki, tako je bil začetek nekoliko lažji. Vsak nov začetek šolskega leta izkoristim uro ali dve za delo v računalniški učilnici, kjer učenci vstopajo v spletno učilnico, rešujejo naloge in jih preverjamo preko e-pošte. Pri delu jim pomagam, pomagajo si tudi sami med seboj. Način dela tako ponovijo, ga nadgradimo tudi kasneje s kakšno domačo nalogo. Domače naloge so izjema, saj so današnji učenci zelo zaposleni Slika 1: Izdelek učenca. s popoldanskimi aktivnostmi in se nalogam raje izognem, ker smo sicer vsi v neprijetnem položaj; učenec, ker je nima in Snov pri jeziku je bila najprej namenjena reševanju nalog učitelji, saj nimamo sredstev za dosego cilja opravljanja domačih razumevanja neznanega besedila, nato so sledile naloge nalog. spoznavanja nove snovi in naloge ponavljanja in utrjevanja. Vse Šola ima spletne učilnice razporejene po razredih za 1. in 2. je bilo pripravljeno v delovnem zvezku z različnim naborom vzgojno izobraževalno obdobje ter po predmetih za 3.vzgojno nalog po taksonomski stopnji. Na koncu vsakega sklopa je sledila izobraževalno obdobje, sedaj so dodali še za oddelek naloga formativne spremljave pouka, kjer so učenci odgovorili podaljšanega bivanja, knjižnico, interesno dejavnost in dneve na vprašanja, kaj so se naučili, kaj dobro znajo, česa še ne znajo, dejavnosti. kako bodo odpravili vrzeli v svojem znanju. Učenci so dobili v času pouka na daljavo tedenske naloge po Za dodatno delo sem poiskala interaktivne naloge na spletu, dnevih s prijaznim povabilom, ki je pomenilo zunanjo motivacijo. kjer so šestošolci utrjevali znanje samostalnika, pridevnika, Povabilo: »Le pogumno, le za mano ….« je zapisala glagola, števnika, osebnega zaimka in prislova; sedmošolci so slovenska pisateljica Anja Štefan. Tako vas v tem tednu utrjevali stavčne člene. Osmošolci so reševali naloge podredno nagovarjam, ko vam vlivam veliko moči, poguma in želje po zložene povedi (odvisniki) in devetošolci naloge utrjevanj novem znanju. Vse, kar je potrebno narediti v tem tednu, vas priredno zložene povedi (priredja). Takšnih nalog so vajeni, saj čaka v priponki. Ostanite zdravi, vzemite si čas za sprostitev in jih pogosto vključim v proces učenja, ko so utrujeni, za dvig pokličite tiste, ki jih imate radi [Praprotnik Žaucer, privatna motivacije in za tekmovalno spodbudo. komunikacija] . Učencem z dodatno strokovno pomočjo in tujcem sem Ali: Pozdravljeni šestošolci, z vami je lepo delati, trudite se pošiljala naloge preko e-pošte prirejeno njihovim sposobnostim. in me vedno znova presenetite s svojimi odličnimi razmišljanji V to skupino sem vključila tudi nekatere učence Rome. Pokazala in odgovornim delom. Hvala. se je potreba po takšnem vzpostavljanju stika, saj se v spletnih Vsak drobec znanja, ki ga učenec pridobi sam – vsak problem, učilnicah niso znašli. Bil je tudi primer romske deklice, ki sem ji ki ga sam reši – postane mnogo bolj njegov, kot bi bil sicer.(H. pošiljala prirejene naloge na e-naslov prijateljice in sta potem Spencer). S to mislijo vas vabim k raziskovanju življenja skupaj opravili nalogo. Šola ji je omogočila izposojo tablice, a je slovenskega književnika, Toneta Pavčka. Dela se lotite z vso skrbnostjo in samostojno, saj je to preverjanje pred ni bila vešča ne ona in ne njeni domači. Sledila sem prvinam ocenjevanjem, ki sledi naslednji teden. Sledite navodilom in se vsebinskega in procesnega znanja, ki se nato ocenjujejo pri ponovno potrudite [Praprotnik Žaucer, privatna komunikacija]. pouku slovenščine in jih konkretiziram z raznimi načini in Nato je sledila priponka s tedensko zadolžitvijo, zapisana po oblikami ocenjevanja, z besedili, vprašanji, nalogami, primeri dnevih. Potrudila sem se z navodili, ki so bila enoznačna, jezikovne rabe …[1]. zapisana z različno velikostjo pisave, potemnjena, podčrtana in 2.2 Odzivi učencev predvsem pregledna. Naloge pri književnosti (dramsko besedilo, proza) so bile Ključ uspeha je, da znamo poiskati v množici podatkov tiste razdeljene na pogovor/razmišljanje/povezovanje pred branjem, temeljne informacije, jih sistematizirati in pripraviti za nadaljnjo po branju so raziskovali besedilo. Tu so iskali motive za rabo in nadgradnjo. Znati moramo reševati probleme in 626 sodelovati med seboj. Prav odzivi učencev na delo so povratna Otrokom so bili v pomoč pri organizaciji dela, jim pomagali na informacija o uspehu, ki je lahko tudi proaktiven, pripravljen na vsakem koraku po svojih najboljših močeh. Pri tistih, ki so si poraz, a biti morajo dovolj vztrajni, da se poberejo. Vse to je znali sami organizirati razporeditev dnevnih dejavnosti, so svoje posledica kapitala in dela sodobne današnje družbe. Delo na delo že pred časom opravili. Učenci so namreč različni: daljavo je zahtevalo odkrivanje novega, neraziskanega področja. samostojni, delno samostojni, popolnoma nesamostojni. V Prvi teden so bili odzivi učencev le za pokušino. Osmo in kolikor je še negativna kombinacija s starši je lahko neodzivnost devetošolci so se odzivali zelo redko ali nikoli. Vsak poizkus za delo na daljavo nična. Presenetljivo pogumna sporočila so vzpostavitve stika se je končal brez uspeha. Šesto in sedmošolci upali zapisali nekateri starši; vse v dobri meri, da zaščitijo so delo sprejeli kot prijetno igro v tekmovalnem smislu, kdo bo svojega otroka, čeprav je doma sedel in preganjal dolgčas. naredil takoj in vse. Podobno je bilo še v 2. tednu. Verjela sem, Zapisali so, da otrok ni dobil nobene informacije o pouku na da potrebujejo čas za prilagoditev, za urejanje IKT. Dnevno sem daljavo, čeprav smo učitelji vsak za svoj predmet podali natančne beležila njihov odziv in jih konec 1. tedna opozorila na informacije, dodatne informacije so dobili od razrednikov, tudi neodzivnost, v 2. tednu sem poslala podatke o neodzivnosti mediji so pomagali pri osveščenosti in učenci so poznali spletno razredničarkam in staršem. Odzivi razredničark so bili v učilnico. Starši so bili dokaj zmedeni, hoteli so me prepričati, da pričakovanju, v pomoč in spodbudo, da se ti učenci priključijo. njihov otrok pošilja rezultate dela, šli so celo tako daleč, da so V 3. tednu je bila priključena večina otrok, sodelovanje je bilo me postavili v zmoto, da njihovega otroka ne učim, ker so korektno, čutili so, da je pouk na daljavo njihova dolžnost in pomešali slovenščino z angleščino. Sporočilo je vsebovalo pravica. Pri delu so bili uspešni, naloge so reševali po navodilih. številne klicaje. Prav branje navodil pri nekaterih učencih povzroča težave, saj K sreči so prevladali zdrav razum, skrb za otrokovo navodila berejo le približno ali celo ne, kar se odraža pri prihodnost in prilagoditev trenutnim razmeram ter celo preverjanju znanja in preizkusu znanja, ko delajo individualno. opravičilo. Drugi del staršev je znal dodatno motivirati svoje Nekoliko večji problem so predstavljali romski otroci, ki otroke, jih vključiti v proces učenja, ko so prešli v monotonost in doma nimajo računalnika, starši ne znajo pomagati in ne obup zaradi nastale situacije. Vsaka spodbuda, vsak realen stik z obvladajo slovenskega jezika. Vsak poizkus dobiti stik z njimi se učenci in starši, izmenjava izkušenj z drugimi učitelji nas je vse je končal brez odziva; na e-pošto niso odgovarjali, tudi ne na dvigovala pred neznanim in nas prepričala, da zmoremo. Večina eAsistenta, telefon je zvoni v prazno, številka je bila dela ostaja na ramenih staršev, ki morajo poleg tega v mnogih nedosegljiva, … primerih opravljati še svojo službo. Od njih se pričakuje, da ob Povratne informacije so ostali učenci pošiljali po e-pošti npr. doseženi V. stopnji izobrazbe nudijo svojemu otroku pomoč preko računalnika in telefona, preko e-Asistenta, s pomočjo na nivoju strokovnjaka s specialnimi znanji s VII. ali višjo spletne učilnice, nekaterim so to delo opravili starši, ker sami stopnjo izobrazbe[2]. niso znali. Pri manjšem številu učencev sem pogrešala sporočilo Mnogi starši so nam bili hvaležni za skrb, trud in primernost ob oddaji nalog, peščica je bila tako nevešča, da so sporočilo izbranih nalog, ki so jih glede na svoje sposobnosti in zastavljeni zapisali kar v zadevo. Ko bomo v novem šolskem letu lahko učni načrt morali opraviti. Tu se je potrdilo, da učenec sodi v šolo, vstopili v računalniško učilnico, bomo temeljito ponovili da je učitelj strokovno usposobljen za delo z njimi. Prav bi bilo, oblikovanje besedilne naloge – sporočilo na e-pošti, kar je sicer da v prihodnje starši ne bi vdirali na področje, ki je strokovno in v učnem načrtu v 8. in 9. razredu. Tako se bomo izognili zanj odgovarjata učitelj in ravnatelj. Radi pomagamo učencem, nepravilnostim, kot je primer učenca, ki je zapisal celotno smo pripravljeni na dodatne ure, tudi neplačane, če so zagotovilo sporočilo pravopisno pomanjkljivo v zadevo in ga zaključil z Lp, za izboljšanje znanja in pridobitev višje ocene, ker učenec ni kot to zapišejo vrstniki med seboj v telefonskem sporočilu. razumel snovi, je bil bolan ali odsoten iz katerega drugega Vsak odziv učenca sem zabeležila za svojo lastno evidenco, opravičljivega vzroka. Vsak otrok je za starše nekaj kjer je bilo razvidno, kdaj je poslal povratno informacijo, kaj je neprecenljivega, tega se zavedamo in prihajamo naproti, še toliko dobro rešil, kaj slabše, dodala sem še oznako za stik z z večjo ljubeznijo, če so nameni pošteni in iskreni. razredničarko in starši. V skupni rabi sem zabeležila še odzivnost učenca za potrebe šole. Uradno je delo na daljavo trajalo dnevno 2.4 Odzivi vodstva šole od 7. do 15. ure, a sem bila učencem na voljo 24 ur, tudi med V uvodu sem zapisala, da smo imeli učitelji veliko podporo v prazniki in v soboto ter nedeljo. Učenci, tudi starši, so pozabili vodstvu šole, sicer smo se celoten kolektiv izjemno dobro na čas in so pošiljali povratne informacije, vprašanja za delo, tudi povezali, kot vedno, se spodbujali, ponujali rešitve in si vlivali samo lepe misli ob različnih urah, ne oziraje se na delovni čas moči. Izjemno podporo sta nam nudili tudi učiteljici vešči učitelja. računalnika. Sporočila o primerih dobre prakse smo si Čas pouka na daljavo se je začel prevešati čez polovico, ko izmenjevali, bili navdušeni nad kolegom, ki je sodeloval v smo učenci in učitelji začutili pomanjkanje osebnega stika, zelo Izodromu, brali članke v Večeru o dobrem delu na šoli, poslušali smo pogrešali drug drugega. Zavedala sem se v tem trenutku, da intervju na RTV Maribor, ki je bil opravljen z našo kolegico, skupaj z njimi sodim v razred, da je očesni stik tisti, ki učenca čestitali kolegici za napredovanje, čestitali zlatemu priznanju na umesti v prostor, ga umiri in pripravi za delo. Poslana povratna državnem Cankarjevem tekmovanju (tu sem bila mentorica), informacija o učenčevem delu skupaj z njegovo fotografijo je to čestitali nagrajencem na območnem tekmovanju Zaščite in potrdila. reševanja Maribor (tu sva bili s kolegico mentorici), čestitali 2.3 Odzivi staršev raziskovalcem Mladi za napredek Maribora, brali okrožnice Ministrstva za izobraževanje, znanost in šport, sledili navodilom Zavedali so se svoje vloge in predvsem odgovornosti. Bili so v ravnatelja, … Vsak konec tedna smo mu poslali poročilo o pomoč svojim otrokom, z znanjem in v čustveno podporo. opravljenem delu, ki je obsegalo: 627 • pripravo na pouk, 16. aprila 2020. Ocenila sem znanje, ki je bilo ustrezno • pripravo gradiv za učence po oddelkih, obravnavano, utrjeno in z različnimi oblikami ter metodami tudi • vodenje dokumentacije, preverjeno. • drugo pedagoško delo potrebno za nemoten potek Učenec je svoje znanje o književnici Bini Štampe Žmavc dela na daljavo, povezal z usvajanjem snovi pri jeziku, kjer smo spoznavali • sodelovanje s starši, učenci in učitelji. besedilno vrsto vabilo. Na željo ravnatelja smo dodali še kakšno sporočilo učencev in staršev ter enkraten dnevniški zapis dela učitelja. Njegovo spremljanje našega dela je bilo spodbudno, prijazno, deloval je umirjeno, svetovalno in z veliko mero optimizma in zaupanja v svoj kolektiv. Pomembno je, da ob šolanju na daljavo ne mislimo le na izvedbo predmetnika in učnega načrta, ampak tudi na odnose[3]. 3 OCENJEVANJE 3.1 Ocenjevanje znanja Pridobivanje ocen je bila najbolj težka in občutljiva naloga. 2. ocenjevalno obdobje se je šele prav začelo, bil je čas pridobivanja nove snovi. Načrtovane pisne naloge ni bilo moč izvesti, ustno spraševanje se mi ni zdelo primerno, saj je obstajala velika možnost nedovoljenih pripomočkov, zagotovo pa neizvedljivo zaradi pomanjkanja tehničnega znanja in tehnike. Takšnega dela so bolj vešči srednješolci in študentje. V aktivu smo se dogovorili za enoten pristop pridobivanja ocen, na način, ki so ga poznali in obvladali. Delo so lahko opravili samostojno, brez tuje pomoči, zanesli so se lahko na svoje izkušnje. Raziskovali so življenje znanega sodobnega književnika, kjer so svoje zanimanje usmerili v: • ime in priimek književnika; • rojstvo; • književno obdobje; • poklic; • književna dela; • slog pisanja (pesniški z uporabo pesniških sredstev, tudi z besedami prenesenega pomena, …); Slika 2: Izdelek učenca. • nagrade (najpomembnejše); • zanimivosti iz življenja; • vključiš kakšno anekdoto (smešen, kratek dogodek) o 3.2 Zaključevanje ocen njem; Pri določanju zaključne ocene sem dala poudarek na ocenah, • dodaj svoje razmišljanje, odziv, tudi lepo misel; pridobljenih do 16. 3. 2020, teh je bilo več in pridobljene so bile • oglej si njegovo fotografijo; na različne načine: • na koncu navedi vire in literaturo. • pisni izdelki, • ustna ocena, Svojo izkušnjo so zapisali v obliki miselnega vzorca ali • govorni nastop, literarne izkaznice in zapis znali ustno upovediti. Nalogo so • drugače pridobljena ocena, … poslali v pregled, kjer sem jo preverila in dopolnila vsakemu Pri zaključevanju sem upošteva tudi oceno pridobljeno v 2. individualno kot vedno. Popravili so jo ter se tako pripravili za ocenjevalnem obdobju na daljavo oz. po prihodu v šolo ter ocenjevanje z raziskovanjem novega književnika po enakem sodelovanje in napredek, ki je bil zaznan v obdobju načinu dela in z enakimi ktiteriji. Pouk se je nato preselil v izobraževanja na daljavo. Zaključevanje ocene je potekalo z učilnice in oceno so pridobili v šoli po enakih navodilih kot utemeljitvijo v sodelovanju z učencem. preverjanje zanjo. V dveh razredih je bila ocena pridobljena na osnovi pripravljenega domačega branja. Učenci so imeli na voljo poleg knjige tudi e-bralnike. Navodila za delo in kriterije 4 DODATNO DELO ocenjevanja so dobili še v času pouka, način priprave je bil preverjen in utrjen. Ravnala sem se po navodilih zapisanih v 4.1 Dodatna strokovna pomoč Izobraževanje na daljavo, Priporočila za ocenjevanje znanja za Vključena sta bila dva učenca: učenka iz 8. in učenec iz 9. osnovno šolo, ki ga je izdal Zavod Republike Slovenije za šolstvo, razreda. V času pouka v šoli sta oba sodelovala in se trudila po 628 svojih močeh. Učenka je v času pouka na daljavo sledila delu in • dodatno izobraževanje učiteljev in učencev za potrebe ga opravila. Naloge sem ji pošiljala tedensko, sestavljene so bile pouka na daljavo, za zadostitev minimalnega standarda. Delo je opravila takoj, • navezati tedenski stik z video klicem, snov je razumela in se je trudila. Zapis sporočila pri oddaji nalog • pripraviti PPT predstavitve za razlago nove snovi, je razkrival željo po telesnem stiku, saj je zelo pogrešala objem. • pripraviti e-razvojni tim na šoli za uskladitev dela vse To je potrdila tudi prvo uro, ko sva se srečali v živo. h deležnikov (učitelji, učenci, starši), Učenec 9. razreda, ki je v februarju poslal prijavo za vpis v • uporabljati orodja primerna starostni skupini otrok, srednjo šolo, je vsa moja sporočila ignoriral. Ni pomagalo • ministrstvo ni dala pravočasno navodil, posnemali so sporočilo razredničarki in ne mami, odziva ni bilo. Ob prihodu v obstoječe. šolo se mi je vljudno opravičil, ker je popolnoma pozabil na Ohraniti: dodatno strokovno pomoč pri vseh učiteljih in ne samo pri meni. • sodelovanje v aktivu, • urnik 2+1 (kar narediš v šoli v eni uri, učenci doma n 4.2 Delo s tujci aredijo v dveh), • manj je več, Vključena sta bila 2 učenca s povsem različnim predznanjem • spletne učilnice, slovenščine. Prvi je bil tujec drugo leto in je slovenščino odlično • urejenost in primernost nalog, obvladal, saj se je jezika učil že pred prihodom v Slovenijo. Delo • primerna selekcija učne snovi (odstranitev balasta), z njim je bilo prijetno, sledila sva usvajanju standardov za • e-bralniki za pripravo domačega branja, nadarjene učence. Drugi je prišel v Slovenijo na začetku • e-DZ Založbe Rokus Klett, koledarskega leta in komunikacija med nama je bila v angleščini. • udeležiti se predavanj po Webinarju Založbe Rokus K Pomagala sem mu s slikovnim slovarjem in začela sva z učenjem lett, besed, ki so obsegale: poimenovanje predmetov v šoli, • prijazen in spodbuden stik z deležniki, pripomočki pri pouku, oblačila, barve, deli telesa, …. Znal se je • zaupanje vodstva šole, tudi predstaviti (kdo je, koliko je star, od kod prihaja, kaj ga • pouk na daljavo je pravica in odgovornost učencev. zanima, …). 4.3 Novinarski krožek 6 ZAKLJUČEK Bili smo tik pred obiskom BKTV (lokalne televizijske hiše v Pri izobraževanju na daljavo sem sledila učnemu načrtu, ki smo Mariboru) in zaključevali smo s prispevki za spletni časopis naše ga prilagodili v aktivu slovenščine. Delo na daljavo je zahtevalo šole. V času pouka na daljavo smo tako poslali še zadnje veliko truda, odrekanj, samostojnega dela in iskanja novih poti prispevke za spletni časopis in si obljubili, da se srečamo v za dosego ciljev. Pri delu so me vodile izkušnje, skrb za učence novem šolskem letu. in odgovornost do učiteljskega poklica. Ne vemo, kaj nam bo prinesla prihodnost, zagotovo se bomo morali naučiti živeti z virusom; v vzgoji in izobraževanju pa 5 EVALVACIJA učence naučiti usvajanja nove snovi preko spletnih učilnic in samostojnega dela. Znanje posredovanja učne snovi bom z Delo na daljavo je dalo misliti, kaj spremeniti in kaj obdržati ob različnimi izobraževanji nadgradila v korist sebe, za lažje delo podobni situaciji. Na pedagoški konferenci smo se strinjali, da se učencem, predvsem pa v pomoč staršem, ki jim mora ostati skrb je vsak znašel po svoje in smo preizkušali različna orodja. za vzgojo otroka, nam učiteljem pa izobraževalno poslanstvo. Pomanjkljivosti pri učencih: • slaba koncentracija • hiperpozorni (lahko delajo več stvari hkrati), LITERATURA IN VIRI • podoba pred besedo, • težave s komunikacijo, [1] Program osnovna šola SLOVENŠČINA Učni načrt • informacije so iskali samo na spletu, (posodobljena izdaja) Ljubljana, april 2018. • doma imajo premalo knjižnega gradiva, https://www.gov.si/assets/ministrstva/MIZS/Dokume • brez ciljev, nti/Osnovna-sola/Ucni- • ne premagajo ovire. nacrti/obvezni/UN_slovenscina.pdf Prednosti pri učenju na daljavo: [2] Različni avtorji.2020.Za učence s posebnimi • personalizacija, potrebami kvaliteten pouk na daljavo ni mogoč! Delo. • formativna spremljava pouka, https://www.delo.si/mnenja/pisma/za-ucence-s- • neodvisni od sošolcev (nikogar pri delu niso čakali), posebnimi-potrebami-kvaliteten-pouk-na-daljavo-ni- • znali nuditi pomoč sošolcu in jo poiskati (solidarnost), mogoc-299224.html • učili so se novih veščin, [3] Medveš Z. 2020. Normatvna logika mamesto • diferenciacija pouka. pedagoškega razmisleka. Delo. Potrebne izboljšave: DOI= https://www.delo.si/sobotna- • preiti v razvoj učenja pri pouku na daljavo, priloga/normativna-logikanamesto-pedagoskega- razmisleka-296463.html 629 Delavnice snovanja poslovnega modela v kontekstu digitalne preobrazbe Workshop on business model design in digital transformation Andreja Pucihar, Gregor Lenart, Marjeta Marolt, Doroteja Vidmar Univerza v Mariboru, Fakulteta za organizacijske vede Kidričeva cesta 55a 4000 Kranj, Slovenija andreja.pucihar@um.si, gregor.lenart@um.si, marjeta.marolt@um.si, doroteja.vidmar@um.si POVZETEK Da bi zadostile potrebam stroke, izobraževalne ustanove s 1 UVOD področja informatike v svoje kurikulume čedalje pogosteje vključujejo vsebine s področja podjetništva. Prispevek opisuje Univerza v Pragi vsako leto organizira mednarodni teden [1], s izvedbo delavnice snovanja inovativnega poslovnega modela na katerim spodujajo študente k sodelovanju na interaktivnih mednarodnem tednu, ki ga je organizirala Univerza v Pragi. Na delavnicah. K pripravi delavnic vsako leto povabijo tuje delavnici smo uporabili orodja za snovanje poslovnega modela predavatelje s partnerskih univerz in organizacij. Gre za način in tehnike snovalskega razmišljanja, kar je udeležence vodilo od dopolnjevanja kurikuluma z aktualnimi in bolj interaktivnimi prve ideje do izdelanega poslovnega modela za zamišljeno vsebinami, ki se vsakoletno spreminjajo, pri čemer lahko študenti rešitev. Prikazan je postopek preko katerega študenti s področja z udeležbo pridobijo 3 ECTS. Univerza v Mariboru je pristopila informatike pridobitvajo mehkejše veščine snovanja in testiranja k letošnjem 4. mednarodnem tednu z izvedbo delavnic snovanja poslovne ideje usmerjene na uporabnika. poslovnega modela za študente magistrskega študija managementa informacijskih sistemov. KLJUČNE BESEDE Aktualne raziskave kažejo, da več kot polovica podjetij s področja informatike v svojih prodajnih in marketinških službah Delavnica, poslovni model, digitalna preobrazba, snovalsko uporablja strukturirane pristope razvoja z namenom razmišljanje, mednarodni teden, Univerza v Pragi identificiranja priložnosti za ustvarjanje dodane vrednosti za ABSTRACT svoje stranke [2]. To potrjuje, da je vključevanje tovrstnih vsebin v kurikulum v času študija pomembno znanje, ki ga bodo In order to meet the needs of the business, educational diplomanti v bodoče potrebovali. Namen delavnic snovanja institutions in the field of informatics are increasingly including poslovnega modela je študentom omogočiti izkušnjo razvoja entrepreneurship-related content into their curricula. The article poslovne ideje do poslovnega modela, ki je pripravljen za describes the organization of a workshop on designing an lansiranje na trg. innovative business model at the International Week, organized Na delavnici izvajalci udeležence vodijo, da skozi postopek by the University of Prague. In the workshop, we used business metode snovalskega razmišljanja (angleško design thinking) [3] modeling tools and design thinking techniques, that guided the in z orodjem kanvas poslovnega modela [4] svojo poslovno idejo participants from the initial idea to the developed business model razvijejo, testirajo in prilagodijo. Poslovni model se tako oblikuje for their proposed solution. In the paper we describe the process glede na trg, na katerega želijo udeleženci vstopiti in stranke, by which students in the field of informatics and economy learn katerim želijo ponuditi svoj izdelek ali storitev. and acquire soft skills for designing and testing a user-centric Delavnice na mednarodnem tednu Univerze v Pragi so business idea. potekale štiri dni. Prvi trije dnevi so bili namenjeni delu znotraj skupin, četrti dan pa so potekale skupne predstavitve za vse KEYWORDS udeležence. Delavnice so bile intenzivne, delo v skupinah je Workshop, business model, digital transformation, design potekalo 8 ur na dan – od ponedeljka do četrtka, od 8h do 16h. thinking, international week, University of Prague Kljub temu, da gre za udeležence, ki so vajeni dela z informacijsko tehnologijo, v konkretnem primeru je šlo pretežno za študente, ki zaključujejo podiplomski študij management informacijskih sistemov, pri izvedbi tovrstnih delavnic uporabljamo papir večjega formata in barvne flomastre. Delavnice izvajamo v skupinah. Pri tem opažamo, da delo s Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed papirnimi orodji spodbuja interakcijo tako med udeleženci for profit or commercial advantage and that copies bear this notice and the full znotraj skupine kot sodelovanje in interakcije med različnimi citation on the first page. Copyrights for third-party components of this work must skupinami. Po izkušnjah izvajalcev, je tudi razprava, ki se med be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia udeleženci delavnic razvije medtem ko v skupnem prostoru © 2020 Copyright held by the owner/author(s). 630 razvijajo ideje in pripravljajo plakate, ki so vsem na vpogled, širša, bolj poglobljena in bolj kreativna. Gre za preizkušen program delavnice, ki ga izvajalci v različnih obsegih izvajajo že več let, tudi pri pedagoškem procesu. Program je pri udeležencih (tako študentih, udeležencih konferenc in v podjetjih) generalno dobro sprejet. V nadaljevanju bo predstavljena zasnova in izvedba delavnice na primeru mednarodnega tedna Univerze v Pragi 2020. 2 IZVEDBA DELAVNICE 2.1 Prvi dan delavnice Ker je bila delavnica organizirana na temo digitalizacije in digitalnih poslovnih modelov, smo prvi dan delavnice snovanja poslovnega modela uvodoma študentom predstavili aktualne Slika 1: Kanvas poslovnega modela (prirejeno po izzive poslovnega okolja, priložnosti digitalizacije in digitalne Osterwalder in Pigneur, 2010) preobrazbe ter inovativnih digitalnih poslovnih modelov. Različne informacijske tehnologije in internet so v zadnjih desetletjih krojile razvoj podjetništva [5]. V zadnjih letih govorimo o digitalni preobrazbi podjetij, pri čemer ne gre več zgolj za uporabo digitalnih tehnologij za podporo poslovnih procesov [6]. Digitalne tehnologije so korenito spremenile poslovno okolje, organizacijsko kulturo in pričakovanja potrošnikov [7]. Podjetja, ki se niso zmožna dovolj hitro prilagajati digitaliziranemu poslovnemu okolju, dolgoročno v njem ne morejo obstati, oz. se vanj ne morejo več vključiti [8]. Zato je pomembno, da podjetje svojo poslovno idejo kreira ali podpira z digitalnimi tehnologijami ter vse skupaj poveže s primernim poslovnim modelom [9], ki bo podjetju omogočal učinkovit dostop do trga in zajem finančne vrednosti. Tovrstno razumevanje smo želeli podati študentom in jih s tem spodbuditi h kreativnemu razišljanju in iskanju poslovnih idej, povezanih z uporabo sodobnih digitalnih tehnologij. Slika 2: Orodje persona (Vir: Businessmakeover.eu [10]) V nadaljevanju smo predstavili orodja za snovanje poslovnega modela ter tehnike in metode snovalskega 2.2 Drugi dan delavnice razmišljanja. Drugi dan delavnice je bil razdeljen na dopoldanski in Udeležencem smo koncept poslovnega modela predstavili na popoldanski del. V dopoldanskem delu smo z udeleženci orodju kanvas poslovnega modela [4], najpogosteje pregledali, katera orodja bodo morali uporabiti za predstavitev uporabljenega orodja za snovanje poslovnega modela (slika 1). svoje poslovne ideje. Prav tako smo predstavili več primerov Podrobneje smo predstavili 9 elementov poslovnega modela, ki znanih poslovnih modelov in se pogovorili o poslovnih idejah, o vključujejo: dodano vrednost, ključne vire (ključni partnerji, katerih so razmišljali in so jih želeli razviti in predstaviti v okviru ključne aktivnosti in ključni viri), ključne stranke (odnosi s delavnice. strankami, segmenti strank in kanali za komuniciranje s Študenti so bili razdeljeni v skupine po štiri udeležence. Vse strankami) ter strukturo stroškov in prihodkovne tokove. skupine udeležencev so že imele pripravljene okvirne poslovne Zadnji sklop uvodnega predavanja je obsegal ključne vsebine predloge. snovalskega razmišljanja, metode reševanja problemov in Vsaka skupina je imela enako nalogo. Pripraviti predstavitev izzivov preko iskanja novih idej. V okviru teh orodij smo za svoj poslovni predlog, ki vključuje 4 papirne plakate – dodana izpostavili orodje imenovano persona (slika 2), ki omogoča vrednost poslovne rešitve za uporabnika, izdelane persone opredelitev več različnih tipov (potencialnih) strank in kasneje uporabnikov, kanvas poslovnega modela in papirno prototipno prilagajanje poslovnega modela različnim strankam. Izpostavili rešitev. smo orodje za prikaz idej (storytelling) ter konceptualne slike za Predstavitev dodane vrednosti za uporabnika mora prikaz prototipnih rešitev – zamisli delujočih digitalnih rešitev. pojasnjevati, katere probleme uporabnikov bo poslovna rešitev Snovalsko razmišljanje omogoča preseganje izzivov in reševala (primer: brezglutenski burger; problemi, ki jih rešuje: reševanje problemov preko skupinskega dela. Spodbuja različne hitra potešitev lakote, hrana za ljudi, ki ne jedo glutena). poglede na obravnavani problem in zamišljanje različnih Opredeljena dodana vrednost je osnova za predstavitev person in možnosti za njegovo reševanje, ki jih lahko kasneje prenesemo v kanvas poslovnega modela, v katerem razvijemo ideje, na kakšen resnično poslovno okolje. način bomo opredeljeno vrednost izdelali in jo posredovali na različne načine različnim uporabnikom (primer: spletno 631 naročanje in dostava na dom, spletno naročanje in osebni ali blaga v trgovini avtomatsko obdeluje in prikazuje različne prevzem, …). podatke za uporabnika. Slika 3 prikazuje predstavitev ideje za Pri predstavitvi person skupina razvije več potencialnih tipov aplikacijo, ki glede na karakteristike in navade uporabnika uporabnikov (strank) in razmišlja o zanje specifičnih potrebah in omogoča optimalno izbiro in sestavo zdravega obroka, ki sproti zahtevah, ki bodo kasneje uporabljene za prilagodive glede na izbrane sestavine uporabniku ponudi podatke o oblikovanja (kanvasa) poslovnega modela (Primer: kdo bo prišel vsebnostih in hranilih vrednostih in predlaga tudi alternative na naš brezglutenski burger? 1. uporabnik, ki želi spotoma nekaj glede na preference uporabnika. Prav tako predlaga izbrano na hitro pojesti; 2. uporabnik, ki želi naročiti in prevzeti naročilo restavracijo oziroma lokacijo za prevzem po željah uporabnika ob dogovorjenem času, 3. uporabnik želi, da mu naročilo sestavljenega obroka. dostavimo). Predstavitev kanvas poslovnega modela tako izhaja iz dodane vrednosti in person, ki smo jih identificirali. V kanvasu poslovnega modela opredelimo kaj poslovni model ponuja vsakemu segmentu strank (katerim njihovim željam in potrebam bomo zadostili), preko katerih kanalov lahko dosežemo vse segmente strank ter odnose, ki jih bomo z njimi vzpostavili. Iz tega izhajajo elementi ključni partnerji, aktivnosti in resursi, ki jih potrebujemo, da lahko ustvarimo našo dodano vrednost (ponudbo). Na podlagi vsega naštetega lahko nato pripravimo strukturo stroškov in prihodkovne tokove, ter izračunamo ali se nam celoten poslovni model ali njegov del (npr. vključitev posameznega segmenta strank) finančno lahko izide. Na koncu vsaka skupina nariše še papirni prototip predlagane poslovne rešitve, katerega namen je, da si ostali udeleženci delavnice lažje predstavljajo delovanje in ključne elemente poslovne rešitve v praksi. V popoldanskem delu drugega dne so se udeleženci razdelili Slika 3: Prikaz predstavitve zamisli poslovne ideje na skupine in začeli delo na lastnih poslovnih idejah. Izvajalci delavnice so bili ves čas na voljo za pojasnila in usmerjanje 3 POVZETEK debate med udeleženci. V vseh skupinah se je razvila živahna debata o poslovnih Prispevek prikazuje primer uporabe orodij za snovanje idejah, različnih tipih uporabnikov in kaj to pomeni za njihovo poslovnega modela in tehnik snovalskega mišljenja in sicer na poslovno idejo – katere prilagoditve bodo morali sprejeti. mednarodnem tednu na Univerzi v Pragi. Izkušnje in odzivi Pogosta vprašanja so vključevala ali je smiselno končno sodelujočih študentov na trodnevni delavnici so izredno rešitev zožati in se usmeriti zgolj na en tip uporabnika ali en pozitivni. Kljub napornemu urniku so študenti zavzeto sodelovali distribucijski kanal. Do konca drugega dne so imele vse skupine pri snovanju poslovnih idej ob upoštevanju priložnosti in pripravljene skice za predstavitev svojih poslovnih rešitev. možnosti izrabe sodobnih, digitalnih idej. Skupina študentov je bila mednarodna, prihajali so iz različnih držav in študijskih 2.3 Tretji dan delavnice programov oziroma smeri. Največ jih je bilo iz ekonomske smeri in smeri informacijskih sistemov. Kljub temu, da se med seboj Tretji dan je bil dopoldanski del delavnice namenjen razjasnitvi niso poznali, so se povezali v skupine in zavzeto in živahno zadnjih vprašanj, ki so se v fazi snovanja poslovne ideje še sodelovali pri oblikovanju poslovne ideje. Med delom izvajalci pojavljale med udeleženci in risanju končnih različic plakatov za nismo zaznali problemov, ki bi študente odvračali od dokončanja predstavitev. V popoldanskem delu pa je imela vsaka skupina naloge. Vse skupine so dokončale svoje naloge in na zaključni približno pol ure časa za predstavitev svojega predloga rešitve, predstavitvi zavzeto predstavile svoje ideje, jih zagovarjale ter ki so jo predstavili s pomočjo štirih plakatov: opredelitve zamisli tudi sodelovale pri diskusiji z drugimi skupinami. Poslovne ideje rešitve in dodane vrednosti, persone, kanvas poslovnega modela so bile različne, inovativne, vse pa so temeljile na sodobnih, in prikaza prototipne rešitve. Sledila je živahna diskusija z digitalnih tehnologijah, kar je bila tudi na začetku izpostavljena izvajalci delavnice in ostalimi udeleženci. naloga. Študenti so sodelovanje na delavnici ocenili kot Vse štiri skupine so predstavile vse štiri zahtevane izdelke - zanimivo in pozitivno izkušnjo. Uporaba izbranih tehnik in plakate, pri čemer je nivo izdelkov nakazoval na dobro orodij jih je spodbudila k izražanju njihove inovativnosti. Izrazili razumevanje ključnih konceptov poslovnega modela in ustrezno so željo, da bi tudi pri študiju imeli možnosti tovrstnega uporabo metode snovalskega razmišljanja. razmišljanja, sodelovanja in izražanja. Predstavljene poslovne ideje so vključevale aplikacijo za Avtorji imajo dolgoletne izkušnje uporabe omenjenih orodij najavo prostovoljcev za pomoč in delo v zavetišče za živali, pri predmetih na Fakulteti za organizacijske vede Univerze v aplikacijo za pomoč pri izbiri oblačil za različne priložnosti, Mariboru. Pri izvedbi mednarodne delavnice je bila glavna skrb aplikacjo za mešanje energetskih napitkov, aplikacjo za izbiranje glede omejitve časa. Delavnica je namreč trajala 3 dni, kar je zdrave hrane z avtomatskim preračunavanjem hranilnih bistveno manj, kakor je v primeru uporabe tovrstnih tehnik pri vrednosti in sestavin. Dve rešitvi sta bili vezani na uporabo izvedbi predmetov. Zato smo pri pripravi trodnevne delavnice radiofrekvenčnih (RFID) kod in sicer ena v skladišču druga v posebno skrb namenili pripravi vsebine, na katero smo se želeli trgovini, kjer sistem za avtomatsko izmenjavo skladiščne enote 632 osredotočiti glede na sodelujoče študente ter pri izbiri orodij, ki Business Review. 2018. bi jih lahko uporabili pri snovalskem razmišljanju. Dobra [4] A. Osterwalder and Y. Pigneur, Business Model priprava vsebine, začrtani cilji in skrbno izbrana orodja glede na Generation. John Wiley and Sons, 2010. časovne zmogljivosti in omejitve so bili ključni za uspešno [5] B. Brenner, “Transformative Sustainable Business izvedbo delavnice. Models in the Light of the Digital Imperative—A Global Business Economics Perspective,” Sustainability, vol. 10, no. 12, p. 4428, Nov. 2018. ZAHVALA [6] G. C. Kane, “Digital Maturity, Not Digital Raziskovalni program št. P5-0018 – “Sistemi za podporo Transformation,” MITSloan Management Review, odločanja v digitalnem poslovanju” je sofinancirala Javna 2017. . agencija za raziskovalno dejavnost Republike Slovenije iz [7] A. Pucihar, “The digital transformation journey: content državnega proračuna. Izvajalci delavnice se zahvaljujemo tudi analysis of Electronic Markets articles and Bled kolegom iz Univerze v Pragi za povabilo k sodelovanju. eConference proceedings from 2012 to 2019,” Electron. Mark. , vol. 30, no. 1, pp. 29–37, Mar. 2020. [8] G. C. Kane, D. Palmer, A. N. Phil ips, D. Kiron, and N. VIRI Buckley, “Coming of Age Digitally: Learning, [1] P. University of Economics, “I-Week 2020,” 2020. . Leadership, and Legacy,” 2018. [2] Harvard Business Review and Genpact, [9] H. Chesbrough, “Business model innovation: it’s not “ACCELERATING THE PACE AND IMPACT OF just about technology anymore,” Strateg. Leadersh. , DIGITAL TRANSFORMATION FULL REPORT,” vol. 35, no. 6, pp. 12–17, 2007. 2016. [10] Innovalor, “Businessmakeover,” 2020. [Online]. [3] J. Liedtka, “Why Design Thinking Works,” Harvard Available: https://businessmakeover.eu/tools/persona. 633 Pomoč pri pouku na daljavo za učitelje, učence in starše Online education assistance for teachers, pupils and parents Peter Purg Osnovna šola Antona Martina Slomška Vrhnika Pod Hruševco 33 1360 Vrhnika, Slovenija peter.purg@guest.arnes.si POVZETEK delu s poudarkom na tehnični pomoči pri izobraževanju na daljavo. Letošnje šolsko leto je posebno. Iz nekaj teledelavcev (delavcev Z razglasitvijo epidemije pri nas se je izkazalo, da se kljub na daljavo) smo na šolah delavci na daljavo postali praktično vsi, večletnemu IKT opismenjevanju, temu še vedno vsi ne saj je epidemija ohromila možnost klasičnega izobraževalnega pripisujejo zadostne pomembnosti. To se je še posebej pokazalo dela. Ker je bila situacija nova, novo delo nikakor ni potekalo z 12. marcem 2020, ko je tudi šole doseglo izredno stanje, na brez izzivov in zapletov, še posebej na področju informacijsko katerega vnaprej noben iz lastnih izkušenj ni mogel biti komunikacijska tehnologije (IKT). Na šolskem področju za pripravljen. Učitelji smo se čez noč kot nindže prelevili v učitelje pomoč skrbimo računalnikarji – organizatorji informacijskih za virtualno poučevanje, enaka virtualna okretnost pa se je dejavnosti (ROID). Prispevek izpostavi najpogostejše težave pri pričakovala tudi od učencev in njihovih staršev. Ravno tako smo izobraževanju od doma in kako smo težave odpravljali s primeri se ROID-I prelevili ne le v učitelje računalništva na daljavo, dobrih praks. temveč tudi v tehnične pomočnike, katerih delo je obsegalo dolge KLJUČNE BESEDE telefonske pogovore, oddaljeno pomoč, izdelavo video vodičev, pisnih vodičev in še in še. Po svetu se takemu delu, ki smo ga mi Teledelo, pomoč na daljavo, oddaljeno namizje, uporabniki, poimenovali delo od doma, imenuje “teledelo”.[5] Teledelo izobraževanje na daljavo vključuje tri različne pomene, ki so vsi povezani z delom od ABSTRACT doma. Prispevek se bo bolj posvetil tehničnemu vidiku in težavam, ki so stale na poti prav vsem sodelujočim v Year 2020 is really special. Having a few teleworkers (remote izobraževanju, ki do takrat teledela nismo bili vajeni. To delo workers) in every field of work, suddenly everyone had to namreč prinaša vrsto prednosti kot tudi pomanjkljivosti, tako za become teleworker in a matter of days, as the pandemic has delavca, kot tudi uporabnika storitev – v našem primeru na paralysed the possibility of classic work. As the situation was področju izobraževanja. [5] Stiska, ki so jo nekateri doživljali new, the work from home was by no means without challenges zaradi pomanjkanja kompetenc na področju uporabnega and complications, especially in the field of ICT. In the school računalništva, kot tudi socialnih vidikov, je bila izrazita.[10] sphere, the ROIDs coped with the newly appeared difficulties. Prav zato bo prispevek pokazal, kako smo premagovali stisko in The article will highlight the most common problems with kako smo teledelo obrnili v premagovanje takih situacij. educating from home and how we solved the problems with some examples of good practices. 2 POMOČ UČITELJEM, UČENCEM IN KEYWORDS STARŠEM Telework, remote assistance, remote control, users, distance V času izolacije med epidemijo je bila potrebna podpora ROID education na različnih nivojih. Posebej sem se moral posvetiti potrebam učiteljev, ki so najpogosteje imeli težave z nedelujočim računalnikom, manjkajočo programsko opremo, znanjem kako 1 UVOD se vpisati v določen forum. Vzporedno pa so pomoč potrebovali Četudi se je šolsko leto 2019/2020 začelo kot vsako šolsko leto tudi učenci in z njimi tudi starši, ki sta bili neločljivi kategoriji do zdaj, je vanj izrazito zarezala epidemija COVID-19. uporabnikov, saj so v dani situaciji starši sodelovali pri učnem Prispevek bo prikazal soočanje z izzivi epidemije pri učiteljskem procesu od doma. Učenci in starši so naleteli na podobne težave kot učitelji, vendar za razliko od učiteljev so imeli največ težav zaradi nepoznavanja programske opreme (vpis in uporaba Moodl-a – učno okolje, Office 365, vpis v AAI račune), nekaj Permission to make digital or hard copies of part or all of this work for personal or krat je prišlo tudi do težav, kjer ni delovala kamera ali mikrofon. classroom use is granted without fee provided that copies are not made or distributed V želji po dobrem in kvalitetnem opravljanju svojega dela, for profit or commercial advantage and that copies bear this notice and the full moramo biti ROID na šolah zvedavi ter raziskovalno naravnani. citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Skladno s tem, smo že prvi dan dela od doma lahko pričakovali, Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia da se bo dan začel z vnemo in zanimanjem. Predvsem nas je © 2020 Copyright held by the owner/author(s). 634 zanimalo, kdaj se bo pokazala prva potreba po naši pomoči v in s tem so lahko v polnosti uporabljali računalnik kot orodje. V obliki prvega klica, ali e-pošte, … V tej novi in nepredvidljivi nekaterih primerih je bila potrebna tudi pomoč z video situaciji smo bili ROID nepogrešljiv kader, brez katerih (tako konferencami, ki ne sodijo v pravo tehnično pomoč, so pa v sem ugotovil po pogovoru s kolegi ROID in pogovoru z učitelji, primeru potrebnega uvida, kaj je uporabnik do takrat delal, ob učenci in starši) ne bi zmogli speljati pouka na daljavo ali vsaj na upoštevanju manjše potencialne varnostne luknje, značilne za takem nivoju oddaljeno pomoč, izjemno uporabne.[6] Začetna odločitev Osnovne šole Antona Martina Slomška Vrhnika je bila, da pouk na daljavo spremljamo z gradivi, ki jih podajamo preko spletne strani. Do sem, ni bilo večjih zagat, saj Vendar pri tem učenci kot uporabniki niso sami, kadar so na so starši, kot tudi večina učencev, vsaj na predmetni stopnji, vidiku težave z računalnikom. tovrstno obliko dela že obvladali. Kasneje pa smo v skladu s Tudi njihovim staršem ter tudi učiteljem se je kar hitro potrebami začeli z video konferencami, nekatere šole v manjšem, zgodilo, da so potrebovali kakšno pomoč za katerega še niso nekatere pa v večjem obsegu. Tukaj je bila naša pomoč izjemno imeli znanja. Pomoč je najprej potekala diagnostično preko pomembna. Začele so se prve tehnične težave, kot so nedelujoč telefona. Nato, ko to ni pomagalo je bilo ključno, da je urejeno v mikrofon, video kamera, slaba povezava ali celo pomanjkanje in najkrajšem možnem času, zato je bilo smiselno uporabiti kar napačna programska oprema. oddaljeno namizje. Uporabniki so v veliki večini povedali, da so Najpomembneje pri vsem je bilo, da sem uspel zaznati težavo že vse poskusili in nič ne deluje. Takratna pomoč preko pri vsakem od deležnikov – učiteljih, učencih in starših, ter oddaljene pomoči je potekala v veliki večini kot učenje na skupaj z njimi poiskal najprimernejšo rešitev, ki je bila po meri daljavo. Najprej so nam pokazali kaj so že naredili in nato smo predznanja vsakega od njih. se lotili reševanja korak po koraku. Nekateri učenci so bili sramežljivi in so najprej prosili pomoč 2.1 Težave pri delu od doma kar svojega učitelja, ki jih je preusmeril na šolskega ROID, v našem primeru name. Ob opisni težavi sem najprej poskusil Skladno z novonastalo situacijo so se pojavile tudi težave, ki so pomagati tako, da sem podal dobro povratno informacijo ter zajemale vse spektre in oblike. ROID-i pa smo se z njimi soočali prosil za čim več podatkov, ki so bili baza za nadaljnje reševanje ažurno in v želji po čim hitrejši odpravi za zagotovitev težave. nemotenega dela ter sledenja učnemu načrtu. S strokovnega vidika so nastale težave na področju Vsesplošni cilj naših skupnih učiteljskih naporov je bilo uporabnega računalništva, ki jih uporabniki s časom uspejo rešiti, izobraževanje, zato sem sam, kot tudi drugi ROID-ji, s katerimi ko se z njimi samozavestno spopadejo sami. Pri tem smo jim smo bili v medsebojni mreži, k temu tako pristopil. K pozitivni pomagali ravno z namenom, da se v prihodnje sami naučijo rešiti usmeritvi je prispevalo tudi splošno znano, da se lahko največ podobne težave. naučimo iz težave oz. problema, saj je to odlična priložnost, da Ni pa povzročalo preglavic samo to, tudi pomanjkanje uporabniki vidijo v živo, kako je dobro postopati pri rešitvi računalnikov in mobilnih naprav za delo je bila precejšna zagata, težave in pri tudi sami preizkusijo posledičnost lastnega ki so jih uporabniki reševali. Velikokrat se je pojavilo, da je v ukrepanja pri vnašanju konstruktivnih rešitev težave. več članski družini bil na voljo samo en računalnik, ki so si ga Na začetku reševanja težav je bilo smiselno, da z izmenjevali in si naredili nekakšen urnik uporabe računalnika. S informacijami, ki sem jih imel, naredim največ, kar sem lahko. tem je prišla tudi možnost, da so uporabniki lahko razporedili čas Na prvem mestu je bila ocena tega, koliko lahko uporabniki z po želji, kar je včasih pomenilo tudi cel dan s prekinitvami. [12] mojim vodenjem naredijo sami. Kot večina ROID-jev sem tudi jaz uporabnikom, ki so bili po mojem mnenju vešči uporabe računalnika, najprej poslal povezavo na relevantni forum z 3 E-GRADIVA možno rešitvijo, da je lahko uporabnik poskušal sam rešiti težavo Glede na to, da so se določeni primeri začeli ponavljati kot s podano pomočjo. Na tak način sem zagotovil, da je vzorec, smo se po pogovoru z drugimi ROID-i odločili, da je opolnomočeni uporabnik ostal motiviran za reševanje problema, smiselno narediti e-vodiče kot obliko e-gradiva, ki je lahko ki je nastal, in sam reguliral samostojno učenje preko IKT podano v različnih oblikah. Oblika vodičev, ki smo jih tehnologije. [9] Pri manj veščih, ki so tožili, da napaka še vedno pripravljali, je bila fleksibilna, od video vodičev do e-gradiva, obstaja, sem ubral drugo pot, ki je vodila k drugi obliki rešitve karkoli bi pomagalo rešiti nek osnovni ponavljajoči se problem, istega problema. kot je bil vpis v e-učilnico, forume itd. Tako smo zagotovili, da Asistenca vsem deležnikom šolskega dela od doma prek so lahko uporabniki brez dodatne pomoči uspešno rešili nekatere oddaljene pomoči na računalniku je vsekakor zagotavljala stvari sami. prihranek časa in je bila temu tudi namenjena.[6] Obenem je bila Pri tem smo na pripravljeno gradivo dobivali različne odzive. to odlična priložnost, da se je lahko uporabnik veliko naučil iz Nekateri so pisali, da jim bolj ustrezajo video vodiči, spet drugi novonastale situacije. V primeru, da je bila težava majhna, jo je so bili mnenja, da se lažje znajdejo iz pisnih virov. To je povsem lahko naslednjič odpravil sam. V primeru, da se je pojavila večja avtonomna odločitev, ki jo ima tisti, ki oblikuje e-gradivo. O težava, se je lahko pri ogledu in pogovoru med reševanjem učil, uporabnosti vira, ki ga uporabniki prejmejo, se odločajo sami. kako postopati naslednjič v primeru, da se bi se podobna težava Lahko ga sprejmemo kot uporabnega, lahko pa ga celo zavržejo ponovila.[6] Najbolj zanimiv izid je bil, da so bili na koncu v zaradi nerazumevanje njegove uporabne vrednosti. To pa je večini vsi deležniki presenečeni, kako malo je bilo potrebno, da odvisno od stopnje učenčeve računalniške pismenosti. računalnik deluje: “A to je vse? Mi sedaj že vse deluje …?” S Najpomembnejše vodilo pri pripravi e-gradiv je bilo tem vedenjem je to postala vsakodnevna dogodivščina, ki je po upoštevanje didaktičnih načel. Načela za pripravo e-gradiv so: prvotni frustraciji osrečevala uporabnike na drugi strani ekrana 635 aktivnost, postopnost, sistematičnost, pojasnjevanje s primeri in situaciji nihče izmed nas ni pomislil na možnost izkoriščanja nazornost, z namenom, da jih uporabnik lažje sprejme oz. oddaljenega namizja. Glede na izgrajeno predhodno stopnjo razume.[9] Vsekakor pa je bilo pri pripravi izjemno koristno medsebojnega zaupanja, je tako kot v šoli, sodelovanje potekalo vnaprejšnje poznavanje tipa učencev, staršev ali učiteljev. Na ta v iskanju ustrezne rešitve. način je bilo lahko posredovano gradivo pripravljeno tako, da je najbolj ustrezalo njihovim potrebam. 4.1 TeamViewer 3.1 Primeri nastalega e-gradiva Program, ki je bil v veliko pomoč pri oddaljeni pomoči, omogoča vrsto različnih orodij. Najbolj pomembna je ta, da lahko dostopaš Prej omenjeno gradivo je lahko v pisni oz. slikovni obliki in je in imaš možnost ne le videti uporabnikovega zaslona, ampak tudi lahko bilo izključno za tehnično podporo pri opravilih ali tudi kot to, da lahko prevzameš nadzor nad njim in z njim upravljaš kot s navodilo itd. svojim. Po namestitvi je zelo uporaben, potrebna je le povezava Primer za vpis v Office 365 (glej Slika 1). do interneta in posredovanje uporabnikove identitete (ID) ter gesla. Slika 1. Primer narejenega vodiča v pisni in slikovni obliki Slika 3. TeamViewer Podano je lahko kot interaktivna vsebina ali kot video vodič (glej Slika 2). Spodnji primer je bil v obliki videa, ki je vseboval Tako se lahko prijaviš v sistem in opraviš delo na samem tudi razlago in uporabo gradiva, ki so ga učenci dobili. V video izvoru težave. Program kljub delitvi identitete in gesla zagotavlja je možno s pomočjo vtičnika H5P preko spletne strani: visoko varnost, saj uporablja šifrirano sejo s pomočjo AES 256 https://video.arnes.si/ narediti tudi interaktivne videe, s katerimi šifrirnega standard kot tudi z RSA izmenjavo privatnega in lahko učitelj sproti preveri, ali je uporabnik to razumel, in kako javnega ključa. [6] mu je gradivo všeč. To lahko naredi s kratkimi dodatki, kot so da/ne vprašanja, kot tudi z anketo, ki jo izpolni vmes. Tako 4.1.1 Primer uporabe dobimo hitro povratno informacijo ali je gradivo kvalitetno Dober primer pomoči je, ko sem dobil e-poštno sporočilo, da zasnovano in kaj še manjka do tega, da bo uporabnikom pomoč uporabnikom nič ne dela na računalniku. To je največkrat slišana ustrezala in pomagala. težava, ki jo ROID-i slišimo, če tudi je običajno napaka majhna. V omenjenem primeru se je pojavila napaka, kjer uporabnikom na enkrat ni več delala kamera in tudi programskega paketa Office niso več imeli na računalniku. Najprej smo začeli s pogovorom preko telefona. Na ta način so uporabniki (starš in učenec s šole) uspeli namestiti program TeamViewer (glej Slika 3) in sporočili svoj ID in geslo. To je omogočilo neposreden vpogled v izvor težave, ki jih je močno ovirala zato, ker so ob navodilih za nalogo imeli možnost nastavitve novega urejevalnika besedila. Problem je bil v tem, da jim je osnovni urejevalnik ni več deloval oz. ga niso našli in jim dokumenta ni odpiralo kot privzeti program. Ta problem smo hitro in uspešno rešili. Nato so ob pregledu imeli gonilnik za kamero, ki kljub Slika 2. Primer pomoči pri opravljanju nalog temu ni delovala. Ob vprašanju, ali se je kdo od družinskih članov igral z računalnikom, je bil odgovor pritrdilen, kar me je usmerilo k razmišljanju, da je nekdo s fizično tipko na 4 SERVIS ZA ODDALJENO POMOČ računalniku izklopil delovanje kamere. Po tovrstni intervenciji je bila težava v pičlih 15 minutah rešena in uporabniki opremljeni Različnih servisov oz. programov, ki omogočajo dostop do z novimi znanji in uvidi, zelo srečni, da se je zadeva rešila, ter da oddaljenega namizja je veliko. Najbolj pogosta izbira za osebno lahko ponovno uporabljajo računalnik. uporabo je TeamViewer. Program je brezplačen, preprost za Na podoben način, z zagotavljanjem pomoči učencem in namestitev in uporaben na različnih platformah.[6] TeamViewer njihovim staršem, je potekal moj vsakdanjik med epidemijo. se je izkazal kot uporabno orodje tako za pomoč učiteljem, kot Pomoči pa niso bili potrebni le učenci in starši. Največ pomoči učencem in staršem, ob predpostavki izgrajenega temeljnega sem namenil ravno sodelavcem, učiteljem in učiteljicam, pri zaupanja med mano in uporabniki potrebnimi pomoči. V tej 636 katerih poznavanje delovanja programov in računalnika ni nakazuje na potrebo po večji stopnji opismenjevanja IKT in tem, njihova močna točka in to raje prepustijo tistim, ki to že znajo. da uporabnike zavestno pripravljamo na večjo stopnjo samostojnosti. 5 REZULTATI Epidemija je bila ne glede na vse izzive in novo nastale situacije, VIRI ki so otežile običajno izobraževalno delo, kljub vsemu izredna [1] V. L., R. A. 2020. Raziskava: koronavirus v Italiji prisoten priložnost za testiranje dela od doma in oplemenitenje šibkih že decembra. DOI= https://siol.net/novice/svet/raziskava- členov, ki do zdaj niso bili identificirani. koronavirus-v-italiji-prisoten-ze-decembra-528206 Dobre rezultate je prinašalo e-gradivo, kjer je bilo vključeno [2] Tratnik, K.. 2020. 31. december: nekaj primerov na upoštevanje kombinacije učno zaznavnih stilov (vizualni, slušni Kitajskem, 3. april: več kot milijon okuženih po vsem in kinestetični).[9] Hkrati smo lahko opremili večje število ljudi svetu. DOI= https://www.rtvslo.si/zdravje/novi- in ker je bilo gradivo pripravljeno na tako nazoren način so uspeli koronavirus/31-december-nekaj-primerov-na-kitajskem-3- v večini rešiti manjše probleme popolnoma sami in s tem april-vec-kot-milijon-okuzenih-po-vsem-svetu/519329 pridobili na samozavesti pri uporabi računalnikov in programov. [3] Vlada RS, 2020. Slovenija razglasila epidemijo novega V primeru, da pa uporabnik ni znal priti do rešitve sam ali z koronavirusa. DOI= https://www.gov.si/novice/2020-03- uporabo e-gradiva, se je najboljše obnesla pomoč na daljavo. To 12-slovenija-razglasila-epidemijo-novega-koronavirusa/ je bilo preprosto narediti s programom za oddaljeno namizje in [4] Drobnjak, S., Jereb, E., 2007. Ali nas čaka življenje na reševati, kot da sediš za njihovimi računalniki, na tak način smo daljavo?. Univerza v Mariboru, Fakulteta za ROID-i lahko točno ugotovili, kakšno težavo ima uporabnik ter organizacijske vede, Kranj DOI=http://www.zjk.si/wp- se lotili analitičnega reševanja. content/uploads/2020/03/Sini%C4%B9%CB%87a- Kljub vsem domiselnim rešitvam, je zaradi Drobnjak_Eva-Jereb-Ali-nas-%C3%84%C5%A4aka- preobremenjenosti strežnikov ali slabe povezave še prihajalo do %C4%B9%CB%9Divljenje-na-daljavo.pdf dodatnih težav, ki jih sam nisem uspel rešiti. V tem primeru je [5] Arko, A., 2002. Razvoj in značilnosti dela na daljavo. bilo nepogrešljivo sodelovanje s tehniki s strani Arnesa, ki so Diplomsko delo. Ljubljana: Ekonomska fakulteta. DOI= vedno zelo ažurno reševali tovrstne težave. Z zagotovitvijo vseh http://www.cek.ef.uni-lj.si/u_diplome/arko219.pdf korakov na poti reševanja težav, je sistem deloval stabilno in [6] Banič, Ž., 2013. Oddaljeno namizje s pomočjo tehnologije dobro. HTML5. Diplomsko delo. Ljubljana: Visokošolski strokovni študijski program prve stopnje računalništva in informatike. DOI= http://eprints.fri.uni- 6 ZAKLJUČEK lj.si/1969/1/Bani%C4%8D_%C5%BD-1.pdf Šolanje na domu je svojevrsten izziv. Pri samem izobraževalnem [7] Šetinc, T., 2015. Servisi za oddaljen dostop do procesu je veliko težav povzročala ravno IKT, ki jo je zagodla računalnikov. Diplomsko delo. Maribor: FERI. DOI= vsakemu od deležnikov vsaj enkrat. Tukaj smo bili nepogrešljivi https:/ dk.um.si/Dokument.php?id=78719 ROID s pomočjo na daljavo in s tem razrešitvi tehničnih težav [8] Perc, D., 2019. Program za opravljanje s povezavami učiteljev, učencev in staršev. Največ težav sem odpravil ravno oddaljenega namizja. Diplomsko delo. Kranj: FOV. DOI= preko programa Teamviewer, pri čemer je pomanjkljivost tega https:/ dk.um.si/Dokument.php?id=132313 programa, da se lahko osredotočiš zgolj na enega uporabnika. To [9] Strmšek, T., S., 2013. Priprava e-učnih gradiv in učnih sem rešil s pripravo e-gradiva, kjer sem dal navodila za uporabo pripomočkov. Ljubljana: Strokovno učno gradivo. DOI= ali razrešitev težav več uporabnikom hkrati. https:/ arhiv.acs.si/ucna_gradiva/Priprava_e- Kaj lahko pričakujemo v prihodnosti? To se je zagotovo ucnih_gradiv_in_ucnih_pripomockov.pdf vprašal skoraj vsak. Četudi se delo od doma povečuje, e-gradiva [10] Švajger, T., 2020. Mesec dela od doma 24ur.com: tragične in oddaljena pomoč ne morejo popolnoma nadomestiti in navdihujoče zgodbe ter mačke na tipkovnicah. DOI= poučevanja na šolah. [9] Tako tudi pomoči, ki jo lahko https:/ www.24ur.com/novice/korona/delo-od-doma.html uporabniku nudi tehnik v živo z razlago in odzivom, ni [11] Likozar, M., 2015. Teledelo v Sloveniji. Diplomsko delo. ekvivalentna pomoči preko oddaljenega namizja. Gotovo smo po Ljubljana: FDV. DOI= http://dk.fdv.uni- izkušnji izolacije mnogo bolje pripravljeni na tovrstne situacije, lj.si/diplomska/pdfs/likozar-matjaz.pdf] nikakor pa ne moremo računati na to, da bi ob ponovitvi [12] Božič, U., 2002. Učenje na daljavo na delovnem mestu: epidemije vse potekalo brez težav in gladko. Pri IKT je prostora poslovna priložnost ponudnikov računalniškega še za mnogo izboljšav, kakor je tudi jasno, da se njihove izobraževanja. Diplomsko delo. Ljubljana: Ekonomska pomembnosti zdaj zaveda večje število uporabnikov. Vse to fakulteta. DOI= http://www.cek.ef.uni- lj.si/u_diplome/bozic561.pdf 637 Učenje na daljavo v času pandemije covid-19 Distance learning during the pandemic covid-19 Polona Rajher III. gimnazija Maribor Gosposvetska cesta 4 2000 Maribor, Slovenija polona.rajher@gmail.com POVZETEK eating is often a topic in the media. Despite the frequent mention of the importance of a healthy diet, research has shown that V prispevku je predstavljeno interaktivno učenje o pomenu adolescents often resort to unhealthy foods. More than half of the zdrave prehrane in presnove, ki je v času odraščanja za adolescents surveyed said they were eating healthy, but the mladostnike ključnega pomena, saj omogoča zdrav telesni razvoj. results showed that only 28% actually did. Consumers often buy Mladostniki se v našem učnem sistemu pogosto srečajo s food at the store based on the appearance of the packaging, and pomenom zdrave prehrane, prav tako pa je zdrava prehrana adolescents are even more receptive to the visual appearance and pogosto tema v medijih. Kljub pogostem omenjanju pomenu advertising of a particular product. As a result, unhealthy foods zdrave prehrane, je raziskava pokazala, da mladostniki are often mistaken for healthy foods and eaten in good faith. The velikokrat posežejo po nezdravi hrani. Več kot polovica paper presents distance learning about the importance of a anketiranih mladostnikov je mnenja, da se prehranjujejo zdravo, healthy diet and metabolism, which takes place during the covid vendar so rezultati pokazali, da je v resnici takšnih zgolj 28%. - 19 pandemic. In order to approach adolescents in a different Potrošniki pogosto v trgovini kupujemo hrano glede na izgled way the importance of a healthy diet for their development and embalaže, mladostniki pa so glede na vizualni izgled in metabolism, a study was conducted in which students first tested oglaševanje določenega izdelka še bolj dovzetni. Posledično their knowledge of healthy eating, completed a survey of their nezdravo hrano pogosto zamenjajo za zdravo in jo v prepričanju, eating habits, and then participated in interactive Šworkshops on da je dobra, jedo. V prispevku je predstavljeno učenje na daljavo the importance of healthy eating and metabolism. Through the o pomenu zdrave prehrane in presnove, ki je potekalo v času Energy for life application, students learned the importance of a pandemije covid – 19. Da bi mladostnikom na drugačen način healthy diet and how nutrients are metabolised in our bodies, and približali pomen zdrave prehrane, je bila opravljena raziskava, v then tested their knowledge with a questionnaire. At the end of kateri so dijaki najprej preverili svoje znanje o zdravi prehrani, the workshop, students used the application Veš kaj ješ? and izpolnili anketo o njihovih prehranjevalnih navadah in bili nato made examples of healthy menus. vključeni v interaktivne delavnice o pomenu zdrave prehrane in presnove. Na teh delavnicah so dijaki s pomočjo aplikacije KEYWORDS Energy for life na interaktivni način spoznali pomen zdrave prehrane in kako se hranila presnovijo v našem telesu. Svoje Healthy nutrition, workshop, metabolism, aplication znanje so nato preverili z vprašalnikom. Na koncu delavnice so dijaki s pomočjo aplikacije Veš kaj ješ? naredili primere zdravih 1 UVOD jedilnikov. Zdrava prehrana je nekaj o čemer se zadnje čase zelo pogosto KLJUČNE BESEDE govori. Pomen zdrave prehrane je ključen za zdrav razvoj, saj Zdrava prehrana, delavnice, presnova, aplikacija telo za izgradnjo notranjih ogranov, mišic, kostnine in živčevja nujno potrebuje hranila, ki jih vsebuje hrana. V zgodnjem ABSTRACT otroštvu se običajno prehranjujemo bolj zdravo in uživamo The article presents interactive learning about the importance of raznoliko prehrano, ki nam omogoča zdrav razvoj. Otrokov healthy nutrition and metabolism, which is crucial for jedilnik določajo starši oz. skrbniki in posledično ne moremo kot adolescents as they grow up, as they enable healthy physical posamezniki vplivati na izbor hrane in uživati zgolj hrane, ki nam development. Adolescents are often confronted with the je všeč. V času pubertete, pa mladostniki počasi začnejo sami importance of healthy eating in our learning system, and healthy določati svoj jedilnik in pri tem večkrat ne upoštevajo smernic zdravega prehranjevanja. Nepravilen izbor živil in njihovo uživanje pa lahko pusti posledice, ki se pokažejo kot nepravilna, neenakomerna rast za vse življenje, prav tako pa lahko vpliva na Permission to make digital or hard copies of part or all of this work for personal or oblikovanje prehranjevalnih navad v kasnejšem življenju. [6] classroom use is granted without fee provided that copies are not made or distributed Zaradi upada upoštevanja smernic zdrave prehrane skozi for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must obdobje pubertete je bila posledično opravljena raziskava katere be honored. For all other uses, contact the owner/author(s). namen je ugotoviti prehranske navade mladostnikov, v kateri so Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia sodelovali dijaki tretjih letnikov III. gimnazije Maribor. Dijaki © 2020 Copyright held by the owner/author(s). 638 so sprva izpolnili vprašalnik, ki je preveril njihove prehranske • skorbut (nastane zaradi pomanjkanja vitamina C v navade, nato pa so preko didaktične delavnice, pri katerih so daljšem časovnem obdobju), uporabljali interaktivni aplikaciji, ki mladostnike spodbudita k • hipertenzija (povišan krvni tlak zaradi hrane, ki boljšem razumevanju pomena zdrave prehrane in njene vsebuje visoke vrednosti nitratov), presnove, spoznavali načela zdravega prehranjevanja. Z vidika • zobna gniloba (posledica prekomernega uživanja varovanja zdravja je namreč zdrava prehrana za mladostnike sladke hrane in slabe ustne nege). izredno pomembna, saj imajo ravno v tem obdobju veliko večje Obstaja še množica drugi bolezni, vendar njihovega nastanka potrebe po beljakovinah, vitaminih in mineralih ter energiji. [1] ne morejo povezati izključno z slabimi prehranskimi navadami. [8] 2 POMEN ZDRAVE PREHRANE Ker so bolezni, ki jih povzroča nezdrava prehrana velik javnozdravstveni problem, se veliko pozornosti namenja k Mladostniki se že v času osnovne šole pri pouku gospodinjstva omilitvami posledic le teh. srečajo s pomenom zdrave prehrane, kjer se učijo o prehranski piramidi in različni pripravi hrane. Nato se o prehrani in presnovi učijo pri pouku biologije, kjer največ poudarka namenijo 3 INTERAKTIVNO POUČEVANJE presnovi ter vgradnji hranil v človeško telo in posledicah Ustaljena praksa poučevanja mladostnikov o pomenu zdrave nepravilne prehrane in prehranskih navad. Njihove prehranske prehrane, očitno ne prinaša dobrih rezultatov, saj se delež navade so v času osnovne šole običajno dobre, vsaj v prvi in mladostnikov, ki imajo slabe prehranske navade in posledično drugi triadi. V tretji trijadi pa mladostniki med glavnimi obroki zdravstvene težave, ki se lahko razvijejo tudi v odrasli dobi. pogosto uživajo prigrizke za katere je značilno, da vsebujejo Razlog za slabe navade mladostnikov, bi lahko bili tudi zastareli veliko energije, zaradi prisotnosti sladkorjev in maščob, ne načini poučevanja v šoli, saj so učenci zaradi uporabe interneta, vsebujejo pa hranilnih snovi, ki jih telo potrebuje za krepitev mobitelov in televizije navajeni na interaktivno pridobivanje odpornosti. Ena izmed praks mladostnikov v tretji triadi je informacij. Frontalen način poučevanja, katerega uporablja opuščanje zajtrka in neustrezen ritem prehranjevanja ter večina učiteljev, v večini primerov ne doprinaša k trajnostnem premajhne količine zaužite zelenjave. Vendar se prehranske znanju, saj so učenci do takšnega pridobivanja informacij vedno navade osnovnošolskih otrok v tretji triadi v veliki meri manj motivirani pri učnem procesu [4]. Učitelj mora dan danes razlikujejo od navad srednješolskih otrok, saj le ti velikokrat učence spodbujati, da sami pridejo do določenih spoznanj, ne da nimajo primerne šolske malice. [5] jim zgolj posreduje znanje. Z uporabo in upoštevanjem Zdravo prehrano bi lahko opredelili z naslednjimi konstruktivističnega pristopa pri izkustvenem učenju lahko smernicami: učitelj učencem pomaga povezati ugotovitve s praktičnimi • redna prehrana (vsaj 5 obrokov dnevno), zakonitostmi. Uporaba IKT (informacijsko komunikacijske • uživanje hrane glede na prehransko piramido, tehnologije) lahko omogoči posredovanje učne snovi na bolj • raznolikost hrane, atraktiven način. Pri pouku lahko uporabimo tako računalnike, • počasno uživanje hrane, ki jo dobro prežvečimo, kot tudi mobilne telefone, sploh v primeru, ko imamo v vzgojno • izogibanje sladkim in mastnim jedem, izobraževalnem zavodu težave zagotoviti primerno število • izogibanje prigrizkom [2]. računalnikov za večjo skupino učencev. Uporaba mobilnih Iskanje krivca slabih prehranskih navad mladostnikov ni telefonov pri pouku ima tudi svoje omejitve in predstavlja enostavno, saj na njihove navade vpliva mnogo različnih določene izzive, sploh od učiteljev. Prednost mobilnih telefonov dejavnikov. Živimo v okolju, ki spodbuja debelost, saj smo kot je v tem, da jih ima večina učencev in da so običajno zmogljivejši družba izredno potrošniko naravnani in nam mediji dnevno od šolskih računalnikov [3]. posredujejo vedno nove in nove proizvode. Poleg tega, pa nas okolje spodbuja k temu, da smo vedno manj aktivni (električna 3.1 Aplikacije za poučevanje o zdravi prehrani in kolesa, električni skiroji, uporaba osebnega vozila.. ). Podatki za presnovi Slovenijo kažejo naraščajoče gibanje prekomeno hranjenih in Na spletu je množica različnih aplikacij in spletnih strani, ki debelih mladostnikov in odraslih pri nas, kar kaže, da se navade opisujejo zdravo prehranjevanje in presnovo, vendar je zgolj pogosto prenašajo s starejše na mlajšo generacijo [7]. Debelost peščica didaktično primernih za uporabo v učnem procesu. pri mladostnikih je namreč eden izmed največjih problemov Večina aplikacij je namenjena ali izobraževanju ali zabavi, današnjega časa, saj prekomerna telesna teža v mladostniškem vendar le malo je takšnih, ki bi združevale oba spektra. Ena obdobju zelo pogosto nakaže na prekomerno telesno težo tudi v izmed aplikacij, ki je tako poučna, da uporabnik pridobi in utrdi odraslem obdobju. Pri mladostniku neuravnotežena prehrana svoje znanje, kot tudi zabavna, da se ne naveliča in je pripravljen povzroča manjšo delovno storilnost, utrujenost, manjšo dlje časa ostati motiviran, se imenuje Energy for life. Aplikacija sposobnost pomnenja in kronične bolezni. Strokovnjaki so sicer ne ponuja uporabe v slovenskem jeziku, temveč je zgolj v ugotovili, da so številne bolezni neposredno povezane s hrano, angleškem in španskem jeziku. Posledično se lahko aplikacijo kar pomeni da je od prehrane odvisno naše zdravje. Nepravilna uporabi kot primer medpredmetnega povezovanja biologije in prehrana pa je večkrat povezana z različnimi slabimi navadami angleščine. Prednost aplikacije je tudi v tem, da je popolnoma kot je telesna neaktivnost in kajenje. Bolezni katere lahko brezplačna in omogoča več različnih učnih modulov. Aplikacija neposredno povežemo s prehrano so: s pomočjo igrifikacije – uporaba dinozavra, ki pritegne pozornost • beri-beri (posledica, dolgoročnega pomankanja uporabnika, uči novih konceptov in ga motivira za interakcijo, vitamina B1), kar izboljša učni proces. Zaradi enostavnega umesnika je ta 639 aplikacija dostopna vsem učencem različnih starosti, tako v opravljanjem nakupov. Aplikacija nam omogoča uporabo osnovni, kot tudi v srednji šoli. Vizualen prikaz in strokovna kamere pri pametnem telefonu in s tem skeniranje črtne kode natančnost izrazov, se določi s pismenimi sposobnostmi izdelka, katerega prehransko vrednost želi uporabnik preveriti. uporabnika. Velik poudarek je na znanstveni pismenosti, Aplikacija nam nato s pomočjo barvnega semaforja prikaže povezan z vizualnimi dražljaji, ki uporabnika spodbujajo k katerih hranil je v izdelku v zadostnih, prekomernih ali aktivni uporabi aplikacije. Aplikacija je zasnovana tako, da se jo premajhnih količinah. Pri sliki 4 lahko vidimo kako je razčlenjen lahko uporablja ob spremstvu vodje učnega procesa ali pa se jo prehranski semafor, ki uporabniku sporoča še dopustno vrednost uporablja samostojno. Slika 1 prikazuje dinozavra, ki določenih hranil v izdelku. Aplikacija Veš kaj ješ? ni namenjana mladostnika nagovarja, kaj vse lahko s pomočjo aplikacije izve. zabavi in je posledično manj atraktivna kot aplikacija Energy for Uporabnik lahko izbira med različnimi področji, ki jih lahko s life, zato je vsaj uvodna uporaba aplikacije priporočljiva pod pomočjo aplikacije osvoji in utrdi svoje znanje. Slika 2 prikazuje vodstvom učitelja. Učitelj mora pred uporabo mobilnih telefonov modul prebavil, katerega uporabnik lahko izbere v aplikaciji in s kot učnega pripomočka med poukom oceniti smiselnost, pri pomočjo njega pregleda kaj vse njegovo telo potrebuje za kateri učni snovi ga bo uporabil in katere učne cilje bo s pomočjo delovanje. Nato uporabnik preveri kaj se zgodi, če tega hranila njih usvojil. Prav tako ni namen vsakodnevne uporabe mobilnih ne dobi (nastanek različnih obolenj). Prav tako, ga aplikacija telefonov pri učnem procesu, saj bi s tem njegova atraktivnost spodbuja k nadaljnjem razmišljanju in preizkušanju naučenega izzvenela, prav tako pa bi lahko postal moteči faktor v razredu znanja. zaradi morebitne nedovoljene uporabe iz strani učencev. Slika 1: Prikaz različnih modulov aplikacije Slika 3: Prikaz aplikacije Veš kaj ješ? Slika 4: Prikaz prehranskega semaforja 4 RAZISKAVA Slika 2: Prikaz modula hranila Da bi ugotovili odnos do zdrave prehrane mladostnikov in preverili znanje o pomenu zdravega prehranjevanja in presnove, Aplikacija Veš kaj ješ? omogoča uporabniku preveriti je bila opravljena raziskava, v kateri so sodelovali dijaki tretjih energijsko vrednost hrane. Prav tako uporabniku omogoča, da s letnikov III. gimnazije Maribor. Za namen raziskave je bilo pomočjo prehranskega semaforja ugotovi, katerih živil naj se izbranih 42 dijakov, ki so sprva izpolnili vprašalnik, ki je bil zaradi prekoračenih vrednosti določenih hranil izogiba. Namen sestavljen iz 14 vprašanj, katerih namen je bil ovrednotiti znanje aplikacije je pomoč pri sestavi jedilnika, katerega lahko vsak učencev o zdravi prehrani in presnovi, prav tako pa je bil namen posameznik sestavi glede na svoje prehranske navade. Slika 3 vprašalnika preveriti njihove prehranske navade. Nato so bile prikazuje primer uporabe aplikacije na pametnem telefonu med izvedene 3 učne ure, pri katerih so dijaki s pomočjo aplikacije 640 Energy for life ugotovili pomen zdrave prehrane in presnove, da izboljšamo prehranske navade mladostnikov, uporaba nato pa so s pomočjo aplikacije tudi preverili svoje znanje. Pri interaktivnega pouka s pomočjo aplikacij. Aplikacije, ki jih dan učni uri je bila vloga učitelja zgolj kot usmerjevalec učnega danes lahko učenci uporabljajo pri pouku, se lahko dostopajo procesa in ne posredovalca znanja. Po uporabi aplikacije so bili preko mobilnih telefonov, kar pomeni, da lahko tudi vzgojno učenci pozvani kakšne so njihove prehanske navade in opisu izobraževalni zavodi z omejitvami pri omogočanju dovolj njihovega tedenskega jedilnika. Ker so imeli pri jedilniku večje velikega števila računalnikov za vse učence, omogočijo svojim težave, so nato s pomočjo aplikacije Veš kaj ješ? preverili kakšne učencem izvedbo pouka na takšen način. Ali bo uporaba takšnih jedi so primerne za določen del dneva in katerih jedi se morajo aplikacij drastično vplivala na prehranske navade učencev je izogibati pri svoji prehrani. Po zaključku dela z aplikacijo so neodgovorno trditi, vendar njihova uporaba lahko pripomore k učenci s pomočjo razgovora posredovali kaj so se naučili in boljšem ozaveščanju zdravega načina prehranjevanja in izročke oblikovane skupaj z učiteljem zapisali v zvezke. Nato so razumevanju presnove hranil ter zdravemu načinu življenja. ponovno izpolnjevali vprašalnik, s katerim je bilo preverjeno, kaj so se naučili. Določeni rezultati vprašalnika so bili pričakovani, saj se je tako znanje kot tudi odnos do zdrave prehrane izboljšal. LITERATURA IN VIRI Presenetljivo je bilo to, da je bilo 54% odstotkov učencev mnenja, da se prehranjuje zdravo, vendar je bilo nato v [1] Gavin, L M, Dowshen, S A, Izenberg, N.(2007). Otrok nadaljnjem delu rezultatov vprašalnika prikazano, da so zmotno v formi. Praktični vodnik za vzgojo zdravih otrok – od prepričani v svoj zdrav način prehranjevanja. Kar 48% učencev rojstva do najstniških let. Ljubljana: Mladinska knjiga. navaja premalo časa kot glaven krivec za njihove slabe [2] Kodele, M, Suwa – Stanojević, M, Gliha, M. Prehrana. prehranske navade, 35% učencev pa navaja, da stres močno Ljubljana: DZS, 2000. pripomore k njihovimi prehranskimi navadami. Kot glaven [3] Lobe, B. in Muha, S. Internet v vsakdanjem življenju slovenskih otrok in mladostnikov (online). 2012. razlog zakaj kupijo določen proizvod so učenci podali izgled in (citirano 5. 9. 2020). Dostopno na naslovu: njegovo oglaševanje. Večina učencev ne pregleda hranilnih http://www.safe.si/uploadi/editor/1297947005MLAD vrednosti pred nakupom produkta. Pri vprašanju katera pijača INAN ETU_porocilo.pdf. ima najvišjo vrednost sladkorja, je sprva od 42 učencev pravilno [4] Ormrod, J.E. (2014). How Motivation Affects odgovorilo zgolj 5 učencev, kar nakazuje na njihovo zmotno Learning and Behavior. Education Psychology, znanje o hranilih v sladkanih pijačah. Pri zapoznelen vprašalniku Developing Learners’ (online) . 2014. (citirano 1. 9. pa je pravilno odgovorilo 18 učencev. Večina učencev, kar 34 od 2020). Dostopno na naslovu: 42 je odgovorila pri zapoznelen vprašalnikov, da bodo več https://www.education.com/reference/article/motivati pozornosti namenili svojim prehanskim navadam. on- affects-learning-behavior/. [5] Polajžar, A, Razgor, E, Regner, A. (2009). Zakon spreminja prehranske navade srednješolcev »bolje 5 ZAKLJUČEK pozno kot nikoli«. Celje. [6] Sizer, F., Whitney, E. (2006). Nutrition. 10th ed. Ključno je, da se o zdravi prehrani začnemo pogovarjati čim prej Belmont: Thomson Wadsworth. v začetku izobraževalnega procesa. Vendar zgolj frontalno [7] Zupančič, A., Hoyer, S. Prehranjevalne navade poučevanje ne prinaša željenih rezultatov, saj se delež študentov. Obzor Zdr N 2006; 157-163. prekomerno debelih mladostnikov v zadnjem časovnem obdobju [8] Žitnik, N. Trtžnokomunikacijski program zdrave drastično povečuje. V raziskavi je predstavljen eden kot načinov, prehrane med dijaki in študenti. Ljubljana: 2009. 641 Uporaba elektronskih gradiv za delo na daljavo v času epidemije pri mlajših učencih v osnovni šoli Use of electronic materials for remote work during the epidemic with younger students in primary school Suzana Rebec Osnovna šola Vide Pregarc Bazoviška ulica 1 1000 Ljubljana, Slovenija suzana.rebec@guest.arnes.si POVZETEK KEYWORDS V članku je predstavljeno delo na daljavo z uporabo Remote work, interactive content, online classrooms, online informacijsko-komunikacijske tehnologije (v nadaljevanju: IKT) quizzes v času epidemije. Delo od doma je od učitelja za komunikacijo s starši in učenci zahtevalo vsakodnevno uporabo IKT. Potrebna je bila prilagoditev načina prenosa informacij, učne snovi, načinov 1 UVOD preverjanja in ocenjevanja znanja, poučevanja učencev z učnimi Delo oziroma študij na daljavo se je pojavilo že v 18. stoletju. V težavami in učencev priseljencev. Za uspešno in nemoteno delo Severni Ameriki so ljudje dobili učno gradivo kar po pošti. S ter doseganje ciljev in pozitivnih rezultatov je bila uporabljena pomočjo prejetega gradiva so se doma učili in pripravljali na cela vrsta interaktivnih vsebin, programov za komunikacijo, ocenjevanje znanja. Te oblike študija pa zaradi izoliranosti in spletna učilnica, vrsta programov za izdelavo kvizov, nalog, osamljenosti učencev niso bile uspešne. posnetkov, predstavitev. Pri njihovi uporabi smo se učitelji Študij na daljavo (angl. distance education) predstavlja soočali tako s težavami kot tudi primeri dobre prakse uporabe IK izobraževanje, ki poteka ločeno od mesta poučevanja, danes ob tehnologije. uporabi sodobnih IKT, oziroma preko interneta. Pri tem so zahtevane specifične tehnike načrtovanja izobraževalnih gradiv, KLJUČNE BESEDE poučevanja in komuniciranja. Sodobne oblike izobraževanja na Delo na daljavo, interaktivne vsebine, spletne učilnice, spletni daljavo izvajamo v virtualnih učnih okoljih, kjer so vključena kvizi interaktivna, večpredstavnostna učna gradiva, ki omogočajo aktivno učenje. [3] ABSTRACT Z napredkom v informacijski tehnologiji (IT) lahko danes to The article presents remote work using Information and težavo delno odpravijo nove tehnologije, kljub temu pa to ni communication technology (hereinafter “ICT”) with working zanesljiv način za uspešno poučevanje in doseganje pozitivnih from home during the epidemic. Working from home required rezultatov pri učencih. Pri tem je potrebno upoštevati tudi the teacher to use ICT on a daily basis to communicate with učenčevo zadostno aktivnost pri opravljanju nalog. Veliko vlogo parents and students. It was necessary to adjust the method of ima učenčevo prizadevanje za lastno delovanje, kar pa je information transfer, learning programme, methods of checking povezano s predhodnim znanjem učenca, njegovo samopodobo and assessing knowledge, teaching students with learning in že usvojenimi učnimi navadami. difficulties and immigrant students. For successful and smooth E-učenje pogosto definirajo kot učenje s pomočjo IKT. work as well as achieving goals and positive results, a whole Učenje je, po definiciji UNESCO/ISCED iz leta 1993, vsaka range of interactive content, communication programs, online sprememba v vedenju, informiranosti, znanju, razumevanju, classroom, programs for making quizzes, assignments, stališčih, spretnostih ali zmožnostih, ki je trajna in ki je ne recordings, presentations were used. In using them, teachers moremo pripisati fizični rasti ali razvoju podedovanih vedenjskih faced both problems and examples of good practice in the use of vzorcev. [2] IC technology. Učenci morajo biti bolj samostojni pri učenju in tudi bolj ustvarjalni. Ker se učijo samostojno, si lahko tempo učenja prilagodijo lastnim potrebam in se osredotočijo samo na določene dele vsebine, ki jim povzročajo težave. Prednost je tudi v sprotnem preverjanju znanja in interakciji z učiteljem. Hkrati Permission to make digital or hard copies of part or all of this work for personal or imajo učenci tudi hitrejši dostop do podatkov preko spleta. [3] classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full Pri tem pa se postavlja vprašanje, dilema, kako uspešno se citation on the first page. Copyrights for third-party components of this work must lahko posamezni učenec uči v domačem okolju s pomočjo be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia tehnologije, ki jo ima doma, in predhodnemu znanju o uporabi © 2020 Copyright held by the owner/author(s). le-te. Ali lahko zagotovimo vsem učencem glede na različne stile 642 učenja enake možnosti za usvojitev zahtevanega znanja? Kako 4 DELO NA DALJAVO dobro smo učitelji sploh opremljeni z znanjem za poučevanje na Od prvega dne dela na daljavo je bilo izrednega pomena daljavo? sodelovanje s kolegi po celotni vertikali. Vsak je prispeval del svoje računalniške pismenosti za kvalitetnejše in lažje delo. 2 NAČRTOVANJE E-IZOBRAŽEVANJA IN Vsakodnevno smo spoznavali nove aplikacije, programe za IZVEDBA navodila za vsakodnevno delo, sestavljanje nalog, kvizov, posnetkov, predstavitev, preverjanj in preizkusov znanja, za Za izvedbo e-izobraževanja je potrebno zagotoviti ustrezno učno komunikacijo in podajanje povratnih informacij. platformo, dostop preko interneta ter strojno in programsko Učenci so bili pri delu od doma kar naenkrat postavljeni v opremo. Učni viri morajo biti interaktivni, večpredstavni. položaj, ko so morali snov prebrati, gledati ali poslušati, vendar Omogočiti je potrebno zadostno pedagoško podporo, in sicer niso mogli spremljati razlage v živo, ob prisotnosti učitelja. izdelavo e-gradiv, izvedbo e-predmetov ter usposabljanje Učitelj pa je moral skrbeti, da bodo kljub danim okoliščinam pedagogov za izvajanje e-izobraževanja. Pomembna je tudi zastavljeni cilji doseženi. Pri tem je bilo ključnega pomena tudi, tehnična pomoč, organizacija izvedbe e-predmetov, ali so imeli doma ustrezno računalniško opremo. administracija, upravljanje in evalvacija. [1] Ob upoštevanju dejstva, da je morala biti snov za učenca V kolikor bi bilo delo na daljavo vnaprej načrtovano in dobro predstavljena skozi raznovrstne aktivnosti, da bi si jo lažje premišljeno, bi bilo e-poučevanje učitelju lažje. V primeru zapomnil, je bilo potrebnega veliko načrtovanja in preizkušanja zaprtja šol tako rekoč čez noč pa smo bili učitelji potisnjeni v metod, ki jih do sedaj še nismo izkusili v praksi niti učitelji. povsem nov način poučevanja, kljub poznavanju tehnologije in Pri izbiri medijev kot učno gradivo se je večkrat pojavila programov za e-poučevanje nam povsem neznan. dilema, ali bo izbran medij dovolj dober, bo učencu dovolj jasno Ob začetku dela na daljavo je bilo potrebno najprej predstavljena vsebina za doseganje ciljev. vzpostaviti komunikacijo s starši in se dogovoriti, na kakšen način in kako pogosto bo potekala komunikacija. Ob dobri strojni 4.1 Dostopnost računalniške opreme in e- opremi je bil naslednji korak iskanje primerne programske gradiva opreme na internetu. Ta je ključnega pomena pri delu na daljavo, saj omogoča učitelju in učencem lažje predajanje informacij, Kot sem že omenila, je bilo v začetku dela na daljavo nujno kvalitetnejše delo in posledično pozitivnejše rezultate. Ključnega preveriti, kako dobro so družine opremljene z računalniško pomena je bilo sodelovanje tako med kolegi kot tudi z učitelji opremo. V prvem tednu smo tako morali imeti v mislih tudi drugih šol. S predajanjem informacij dobre prakse in deljenjem dejstvo, da vsi učenci morda ne morejo dostopati niti do spletne že pripravljenih vsebin je bilo olajšano delo slehernemu učitelju. učilnice. Poznavanje programske opreme namreč še ni dovolj za Druga težava so bila e-gradiva, e-učbeniki in delovni zvezki. uspešno delo, ogromno časa zahteva poznavanje posameznega Učitelji, ki poučujemo v več oddelkih in delamo z učenci z programa, pripravljanje vsebin, ki bi jih lahko posredovali s učnimi težavami, nismo imeli dostopa do e-gradiv različnih iz pomočjo izbranega programa, pa snemanje zvoka, videa, razredov. Tu so bile založbe učiteljem v veliko pomoč, saj so fotografiranje, urejanje podatkov. odklenile svoje platforme, da bi učitelji lahko nemoteno Pri usposabljanju za izvajanje e-izobraževanja smo imeli uporabljali učno gradivo pri delu z vsemi učenci. učitelji na voljo tudi nekaj spletnih izobraževanj, s pomočjo Pojavljale so se težave v komunikaciji, saj nekateri starši niso katerih smo lahko dopolnili svoje znanje o uporabi spletnih imeli niti svojega elektronskega naslova, nekateri starši pa so v programov. začetku celo zavračali pomoč. Tako je bilo nujno vzpostaviti povezavo preko telefona, da bi poiskali skupno rešitev za komuniciranje. 3 SLEDENJE AKTIVNOSTI UČENCEV Veliko težavo je za določene učence predstavljala tudi fizična odsotnost učitelja. Starši so bili potisnjeni v vlogo pomočnika pri Učitelj ima pri delu na daljavo izjemno pomembno vlogo. opravljanju vsakodnevnega šolskega dela, kar pa je marsikomu Čeprav ni v fizičnem stiku z učencem, lahko usmerja učne predstavljalo veliko težavo. Nekaj staršev je bilo kljub karanteni aktivnosti in spodbuja uporabo primernih učnih strategij. Učence v službi, nekateri starši niso razumeli snovi, ki jo je moral njihov usmerja k učnim ciljem ter pospešuje aktivno sodelovanje in otrok predelati, starši, ki so se priselili iz tujine pa zaradi komunikacijo med učenci. Sproti lahko odgovarja na morebitna jezikovnih ovir ravno tako niso zmogli pomagati svojemu otroku. vprašanja učencev, pri tem pa je nujno, da zagotavlja kvalitetne Učenci so imeli kar naenkrat manj nadzora pri šolskemu delu. in razumljive povratne informacije. Za tiste učence, ki so pri svojem delu tudi sicer samostojni in Učence motivira in spodbuja razvoj njihovih suvereni, to ni predstavljalo težav. Učenci, ki pa imajo sicer učne samoregulacijskih procesov (postavljanje ciljev, uporaba težave, manj samokontrole in delovne vneme, pa so predstavljali strategij, planiranje in upravljanje s časom, samoevalvacija, dodaten izziv tako staršem kot učiteljem, saj je brez osebnega samoopazovanje, iskanje pomoči), kar je vsekakor lažje pri stika učencu težko pomagati. Težava se pojavi pri učencih v učencih drugega in tretjega triletja, ker so že samostojnejši. prvem triletju, ki se na samostojnost pri delu še navajajo, vendar Vsakodnevno tudi spremlja delo učencev in opazuje njihov se podobne težave pojavljajo tudi pri nekaterih starejših učencih. napredek. Glede na uspešnost dela in povratne informacije preverja in 4.2 E-gradiva, e-programi ocenjuje izdelke učencev. Ob koncu pa pripravi sumativno preverjanje znanja in učence oceni. Pri svojem delu smo uporabljali različna orodja za podajanje učne snovi. Nekaj jih je v uporabi že dalj časa, kar nekaj 643 programov pa smo morali spoznati povsem na novo. V prvem dejavnosti poleg branja, pisanja in govorjenja je ključna za tednu dela od doma smo tako veliko časa preživeli za uspešno učenje jezika. Vseeno pa mora imeti učenec dnevno računalnikom in iskali primerne programe, ki bi nam bili v možnost, da se pogovarja z učiteljem tudi s pomočjo video klica pomoč pri poučevanju na daljavo. ali po telefonu. PowerPoint PowerPoint, ki smo ga do sedaj večinoma uporabljali bolj kot pomoč pri predstavitvah v živo, se je izkazal kot dober pripomoček tudi za snemanje vsebin (slika 1). Omogoča kar nekaj dodatnih funkcij, ki so lahko v pomoč učitelju za kvalitetnejšo in razumljivejšo pripravo obravnavane snovi. Slika 3. Raba glagolov v povedih – poslušanje v eBralcu Spletna učilnica Slika 1. PowerPoint predstavitev števil do 1000 z Arnesova spletna učilnica (slika 4) je bila od samega začetka glasovno razlago (Vir: Suzana Rebec, 2020) dela na daljavo ključnega pomena za prenos učne snovi. Učitelji razredniki in ostali učitelji smo v učilnico dnevno dodajali Zoom vsebine za lažje delo učencev doma. Poleg snovi za posamezne Zoom je služil tedenskim videokonferencam z učitelji. V času predmete so v spletni učilnici učenci lahko našli dejavnosti za dela na daljavo je postal nepogrešljiv način izmenjave popoldansko ustvarjanje v okviru podaljšanega bivanja, tedensko informacij, primerov dobre prakse, prenosa aktualnih vsebin, so dobivali naloge za učenje slovenskega jezika učenci vezanih na epidemijo in delo na daljavo, poročanja o delu in priseljenci, učenci z učnimi težavami so lahko s pomočjo vaj, morebitnih težavah ter reševanju le-teh. kvizov, križank, nalog v posebni mapi utrjevali svoje znanje. Discord Discord se je izkazal kot dober pripomoček za vsakodnevno delo z učenci na individualni ravni (slika 2). Pomanjkljivost programa je ta, da video način komunikacije ni bil mogoč, čeprav program to omogoča. Nedelovanje je bilo posledica preobremenjenosti sistema, slabe računalniške opreme ter slabe internetne povezave. Slika 2. Aplikacija Discord za vodenje Slika 4. Učne vsebine v spletni učilnici vsakodnevnih učnih ur Glede na aktualne vsebine in obeležitve pomembnih datumov EBralec so bile za popestritev dela doma izbrane določene vsebine in EBralec je program na internetu, ki omogoča poslušanje učencem ponujene dodatne aktivnosti, tako gibalne kot vnesenega besedila v slovenskem jeziku (slika 3). Bil je v veliko ustvarjalne (slika 5). pomoč pri poučevanju slovenskega jezika kot tujega jezika z učenci priseljenci. Poslušanje kot ena temeljnih sporazumevalnih 644 Slika 7. Učni list v aplikaciji Liveworksheets – stopnjevanje pridevnikov (2. razred) Slika 5. Aktivnosti ob svetovnem dnevu Zemlje v spletni učilnici (Vir: Suzana Rebec, 2020) Programi za izdelovanje kvizov, križank, učnih listov Uporabni programi za izdelovanje kvizov, križank za utrjevanje snovi, učnih listov za ponavljanje so bili zagotovo »Liveworksheets« (slika 6 in 7), »Learningapps« (slika 8 in 9), »Quizmaker« (slika 10), »That-quiz« in »Puzzlemaker«. Vsi našteti programi so omogočili pripravo dodatnih vsebin tako za učinkovitejše poučevanje na daljavo kot tudi za lažje učenje in Slika 8. Naloga v aplikaciji Learningapps – utrjevanje po pomnjenje. branju književnega besedila (4. razred) Slika 9. Naloga v aplikaciji Learningapps – utrjevanje po branju književnega besedila (5. razred) Slika 6. Učni list v aplikaciji Liveworksheets – notranji organi (3. razred) 645 pomanjkanje samodiscipline. Nekateri starši kot tudi učenci so bili v začetku, pa tudi kasneje, neodzivni, kar je dodatno otežilo delo učitelju. Težava je bila tudi samostojnost pri uporabi programske opreme, sploh pri mlajših učencih, ki še niso tako vešči uporabe. V kolikor bomo učitelji primorani ponovno delati na daljavo, bo tokrat delo zagotovo potekalo drugače, lažje, IKT pa nam bo v veliko oporo pri delu. 6 ZAKLJUČEK Slika 10. Kviz v aplikaciji Quizmaker – utrjevanje po Pri delu na daljavo v času epidemije je bilo dobro poznavanje in branju književnega besedila (3. razred) uporaba IKT nujno za uspešno delo. Mlajši učenci so pri uporabi IKT potrebovali pomoč odraslih, saj le-te še ne poznajo v tolikšni meri, da bi lahko samostojno delali. 5 DISKUSIJA Ključnega pomena za uspešno delo je bilo dobro načrtovanje V nastali situaciji smo bili skoraj v celoti odvisni od e- in priprava e-gradiva, vsakodnevno sledenje aktivnosti učencev, tehnologije, ki se je v več pogledih izkazala kot zelo uporaben in poskrbeti pa je bilo treba tudi, da so imeli vsi učenci doma dostop nepogrešljiv del poučevanja na daljavo. Zagotovo ne more do računalniške opreme in e-gradiv. zamenjati osebnega stika, lahko pa je v veliko pomoč pri delu Vse predstavljene aplikacije so pripomogle k uspešnejšemu učitelju in pri učenju učencu. delu, spletna učilnica pa je bila steber za prenos učne snovi, saj Programi, e-gradiva in drugi pripomočki pri pouku na daljavo so bile tam zbrane vse vsebine, napotki, pomoči in naloge za so bili v času karantene edina možna vez med učiteljem in učenci utrjevanje znanja. ter njihovimi starši. Izkazali so se kot odličen pripomoček pri podajanju snovi, aplikacije za video in glasovne klice so bile nujen del vsakdana pri delu z učenci priseljenci in učenci z VIRI IN LITERATURA učnimi težavami, za posamezne oddelke pa stik z razrednikom. [1] Lapuh Bele, J. (2009). Učinkovitost učenja iz spletnih Videokonference so postale obvezen del komunikacije znotraj učnih virov. Doktorska disertacija. Ljubljana: Pedagoška kolektiva na tedenski ravni in nam omogočile izmenjavo fakulteta. informacij, pomenile so tudi začasno zamenjavo osebnega stika, [2] Marentič Požarnik, B. (2003). Psihologija učenja in pouka. ki je zelo pomemben za dobro sodelovanje. Ljubljana: DZS. Srečevali smo se tudi z nekaterimi težavami in [3] Medved, I. (2015). Vpeljava načela vključitev in pomanjkljivostmi. Nekaterim učencem ni bil v dovolj veliki meri izključitev z razlago na daljavo. Magistrsko delo. omogočen dostop do računalniške opreme, saj je bilo doma več Ljubljana: Pedagoška fakulteta. Dostopno na: otrok in samo en računalnik. Nekaj učencev je v začetku delalo http://pefprints.pef.uni- celo preko telefona svojih staršev. Prenekateri starš kot tudi lj.si/3107/1/Ines_Medved_magistrska_naloga_Vpeljava_n učitelj je imel težave pri nameščanju programske opreme, kot a%C4%8Dela_vklju%C4%8Ditev_in_izklju%C4%8Ditev tudi pri njeni uporabi. Pri učencih pa je bila včasih težava tudi _z_razlago_na_daljavo.pdf [6. 7. 2020] 646 Steganografija Steganography Roman Rehberger Šolski center Kranj Višja strokovna šola 4000 Kranj, Slovenija rehberger@siol.net POVZETEK Steganografija je znanstvena disciplina, ki se ukvarja s prikrito 1 UVOD izmenjavo informacij. Temeljno načelo steganografije je Steganografija je postopek zakrivanja sporočil na način, da samo skrívnost komunikacije, to je prikrivanje obstoja posredovanih pošiljatelj in prejemnik poznata oz. razumeta vsebino sporočila. informacij znotraj na videz neškodljivega medija ali nabora To omogoča eni strani, da komunicira z drugo stranjo, ne da bi podatkov. Sodobna steganografija uporablja prednosti digitalne se tretja oseba zavedala, da med njima poteka komunikacija. tehnologije in najpogosteje vključuje skrivanje sporočila znotraj Podatki se običajno skrivajo v neškodljivem ovitku, tako da tudi nekaterih večpredstavnostnih datotek, na primer slike in zvočne če tretja oseba odkrije ovitek, ne more posumiti na podatke, ki se ali video datoteke. Drugi cilj steganografije je vodni žig, to je skrivajo znotraj ovitka. Če skrite podatke vendarle odkrije tretja postopek podpisovanja digitalnih medijev z namenom varovanja oseba, je tehnika steganografije neuspešna. pravic intelektualne lastnine. Članek predstavi uporabo različnih Pri steganografiji gre za skrivanje sporočila v druge metod za skrivanje informacij in seznanja z izzivi steganografije neškodljive vire informacij, kot so besedilo/dokumenti, avdio, glede zlonamerne programske opreme, shranjevanja in varovanja video posnetki in slike, ki niso vidne nepooblaščenim podatkov. Opiše tudi nekatere metode odkrivanja uporabnikom. Lahko se skrije celotno particijo na trdem disku ali steganografskih datotek s pomočjo steganalize. vdela podatke v razdelek glave datotek in omrežnih paketov. Učinkovitost teh metod je odvisna od tega, koliko podatkov KLJUČNE BESEDE lahko skrijejo in kako enostavno jih je zaznati. Steganografija, digitalni mediji, vodni žig, steganaliza Uporabljata se dva glavna cilja steganografije, in sicer skrivna komunikacija in vodni žig. Skrívnost komunikacije ABSTRACT zajema veliko načinov zagotavljanja alternativnih rešitev za slike, Steganography is a scientific discipline, which deals with a secret avdio, video datoteke itd. Vodni žig je postopek podpisovanja exchange of information. Its primordial principle is concealment digitalnih medijev (slik, besedil, avdio in videoposnetkov) z of communication, i.e. hiding the existence of forwarded namenom varovanja pravic intelektualne lastnine. Vodni žig information within a seemingly harmless medium or dataset. pomaga vstaviti prstni odtis, ki ga je mogoče prepoznati [1][2]. Contemporary steganography uses advantages of digital Steganografija je pogosto orodje različnih vrst kriminalcev, technology and most frequently includes hiding messages in saj omogoča komunikacijo, ne da bi jo odkrili. Tipični primeri so some media files such as pictures, and sound or video files. komunikacija med terorističnimi celicami, razširjanje Another goal of steganography is watermark, i.e. a process of nezakonitega materiala, pridobivanje poslovnih skrívnosti ali signing digital media to protect the rights of intellectual property. njihova uporaba kot orodje za skrivanje zlonamerne programske The article presents use of different methods of hiding opreme ali ukazov, ki daljinsko nadzorujejo zlonamerno information and gives information on challenges of programsko opremo. Steganografija je eno od pomembnih orodij steganography regarding malicious software, storing and vohunov in zlonamernih hekerjev ter borcev za človekove protecting data. Some methods of detecting steganographic files pravice in političnih disidentov. Zaradi svojega temeljnega with the help of steganalysis. načela "nevidnosti" informacij se pogosto uvršča med nezakonite dejavnosti. KEYWORDS Za odkrivanje steganografskih datotek uporabimo katero od Steganography, digital media, watermark, steganalysis metod steganalize, s pomočjo katerih je mogoče prepoznati in razkriti skrivna sporočila s preučevanjem variacij vzorčnih bitov in nenavadne velikosti datotek. Permission to make digital or hard copies of part or all of this work for personal or 2 STEGANOGRAFIJA classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full Postopek steganografije običajno vključuje vstavljanje skrivnega citation on the first page. Copyrights for third-party components of this work must sporočila v prenosni medij, ki se v tem primeru imenuje nosilec be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia in ima vlogo prikrivanja skritega sporočila besedila, slike, zvoka © 2020 Copyright held by the owner/author(s). ali video zapisa. Če želi pošiljatelj poslati skrivno sporočilo 647 prejemniku s pomočjo stegosistema, ga s steganografsko metodo Orodja za sledenje dokumentov: Skrite podatke lahko vgradi skozi naslovni predmet. Postopek vdelave ustvari stego uporabimo za identifikacijo zakonitega lastnika dokumenta. Če objekt. Pošiljatelj jasno pošlje stego objekt po omrežju, brez je dokument spremenjen ali se ga distribuira nepooblaščenim šifriranja, na primer s pomočjo spletne ali mobilne aplikacije. Na strankam, ga lahko izsledimo in odkrijemo, katera stranka je drugi strani mora prejemnik uporabiti isto steganografsko prekršila pogodbo o distribuciji licence [5][6]. metodo, da izvleče skrivno sporočilo iz prejetega stego predmeta. Avtentikacija dokumenta: Skriti podatki, zbrani v Za dodatno zaščito je možna tudi uporaba steganografskega dokument, lahko vsebujejo digitalni podpis, ki potrjuje njegovo ključa, ki kodira skrivno sporočilo, preden se ga vstavi v nosilec. pristnost [5][6]. V tem primeru mora imeti prejemnik enak steganografski ključ, Splošna komunikacija: Ljudje so zainteresirani za te tehnike, kakršnega je uporabil pošiljatelj za izpis skrivnega sporočila [3]. ki zagotavljajo večjo varnost pri svojih vsakodnevnih Uporabo ključa v slikovni datoteki ponazarja slika 1. komunikacijah. Internet, korporacije in elektronski pogovor se še vedno vidijo kot priložnost za nadzor [5][6]. Digitalne volitve in elektronski denar: Digitalne volitve in elektronski denar temeljijo na tajnih in anonimnih komunikacijskih tehnik [5][6]. Radarski sistemi: Sodobni tranzitni radarski sistemi lahko integrirajo informacije, zbrane v radarski bazni postaji, pri čemer se izognejo potrebi po pošiljanju ločenega besedila in slik na bazne postaje sprejemnika [5][6]. Daljinsko zaznavanje: Sestavimo lahko vektorske zemljevide in digitalne posnetke spletnega mesta, kar še izboljša Slika 1. Steganografski ključ v slikovni datoteki [4] analizo obdelovalnih površin [5]. 2.1 Uporaba steganografije 2.2 Tehnike in metode steganografije Kot številne druge varnostne metode in orodja se tudi Predstavljamo nekaj pomembnih steganografskih metod in steganografijo lahko uporablja na različnih področjih in tehnik. dejavnostih. Prostorska domena: Steganografske tehnike prostorske Napredne strukture podatkov: Oblikujemo podatkovne domene, znane tudi kot nadomestne tehnike, na delih slike strukture za prikrivanje nenačrtovanih informacij, ne da bi pri ustvarijo prikrit kanal, v katerem bodo spremembe verjetno tem kršili združljivost s staro programsko opremo. Na primer, če nekoliko manjše in prikrite človeškim očem. Eden od načinov je potrebujemo dodatne informacije o fotografijah, jih lahko skrivanje slikovnih podatkov v najmanj pomembnem bitu (LSB). postavimo na fotografije. Informacije bodo potovale s Pri tej metodi se LSB vsakega bajta na sliki uporablja za fotografijami, vendar ne bo motila stare programske opreme, ki shranjevanje tajnih podatkov. Pomanjkljivost te tehnike je, da je ne ve za njen obstoj. Poleg tega lahko oblikujemo napredne treba za sliko uporabiti vsak slikovni piksel v sliki, zato je za podatkovne strukture, ki nam omogočajo uporabo majhnih kosov sliko treba uporabiti format stiskanja brez izgube, kot je bmp ali trdih diskov za prikrivanje pomembnih informacij [5][6]. gif. Če uporabimo stiskanje izgube, se lahko nekateri skriti Medicinski posnetki: Bolnišnice in zdravniki lahko sestavijo podatki izgubijo [6]. kartoteke bolnikov, ki vsebujejo posnetke (slike) in njihove Preoblikovanje domene: To tehniko je mogoče opredeliti podatke. Ko zdravnik analizira radiološki pregled, se bolnikove kot domeno tehnik vdelave, za katere je predlagano več informacije vtisnejo v sliko, kar zmanjša možnost napačne algoritmov. Proces vdelave podatkov v frekvenčno domeno diagnoze in/ali goljufije. Pri vgradnji dodatnih podatkov v signala je veliko varnejši od principov vdelave, ki delujejo v medicinske slike se zahteva izjemna previdnost: dodatne časovni domeni. Tehnike preoblikovanja domen imajo prednost informacije ne smejo vplivati na kakovost slike [5][6]. pred LSB tehnikami, ker skrivajo informacije na področjih slike, Močni vodni žigi: Ustvarjalci digitalnih vsebin vedno ki so manj izpostavljene stiskanju, obrezovanju in obdelavi slike uporabljajo tehnike za opisovanje omejitev, ki jih postavljajo na [6]. njihovo vsebino. Ta tehnika je lahko preprosto sporočilo "Leto Tehnika širjenja spektra: Prenos spektra v radijskih avtorskih pravic s strani nekoga" in vsebuje sistem za upravljanje komunikacijah prenaša sporočila pod nivojem hrupa za katero digitalnih pravic, ki ga je razvil Apple za trgovino iTunes, ali koli frekvenco. Ko se uporablja za steganografijo, razpršeni vodni žigi v vsebini vatikanske knjižnice [5][6][7]. spekter obravnava naslovno sliko kot hrup ali poskuša dodati Vojaške agencije: Dejanja vojakov lahko temeljijo na skritih slikovni psevdo hrup [8]. in zaščitenih komunikacijah. Tudi s šifrirano vsebino zaznavanje Statistična metoda: Te tehnike modulirajo ali spreminjajo signala na sodobnem bojišču lahko privede do hitre identifikacije statistične lastnosti slike, poleg tega, da jih ohranijo v postopku in napada vpletenih strani v komunikacijo. Zaradi tega vojaška vdelave. Ta sprememba je običajno majhna, zato lahko izkoristi oprema v svojih komunikacijah uporablja modulacijo in tehnike človeško šibkost pri zaznavanju spreminjanja svetilnosti [8]. razširjenega spektra [5][6]. Tehnika izkrivljanja: Tehnike izkrivljanja zahtevajo Obveščevalne agencije: Pravosodne in obveščevalne poznavanje izvirne slike med postopkom dekodiranja, pri čemer agencije so zainteresirane za preučevanje teh tehnologij in dekoder preverja razlike med prvotno sliko in izkrivljeno sliko, prepoznavanje njihovih pomanjkljivosti, da lahko odkrijejo in da bi obnovil skrivno sporočilo. Prejemnik na drugi strani doda spremljajo skrita sporočila [5][6]. zaporedje sprememb slike. Informacije so torej opisane kot shranjene z izkrivljanjem signala [3][8]. 648 Ukrep uspešnosti: Kot merilo učinkovitosti za popačenje Danes se jo uporablja s spreminjanjem postavitve dokumenta in slike zaradi vdelave se lahko za stego posnetke uporabi razmerje dodajanjem dodatnih presledkov in z uporabo skritih znakov v med najvišjim signalom in šumom (PSNR), ki je razvrščeno po besedilu. Pomanjkljivost besedilne steganografije je šibkost pred meritvah izkrivljanja. Opredeljen je kot [5]: napadi. Dodane presledke, črte in znake je mogoče zlahka zaznati z odpiranjem besedila v urejevalniku besedil. Prikrito sporočilo bo izgubljeno, če bo dokument ponovno formatiran [8]. Besedilo lahko vstavimo v glasbene ali video datoteke tako, da datoteko namestimo na vnaprej določena mesta, tako da bo V enačbi je R največje nihanje vrste podatkov vhodne slike. razlika ustrezala črki v abecedi. Slike imajo lahko več določenih Na primer, če ima vhodna slika dvojno natančno vrsto podatkov slikovnih pik, glasbena datoteka nekaj vzorcev in video datoteko, s plavajočo vejico, potem je R 1. Če ima 8-bitno nepodpisan nekateri okvirji se nekoliko spremenijo, v glavnem pa ohranijo celoten podatkovni tip, je R 255 itd. MSE označuje povprečno svojo funkcionalnost nedotaknjeno. Spremembe so tako majhne, kvadratno napako, ki je dan kot da je ob gledanju ali poslušanju gradiva težko opaziti dodano besedilno sporočilo [5][10][11]. Steganografija v slikovnih datotekah: Je najpogosteje uporabljena. Slikovni steganogrami so lahko krhki ali robustni glede na metodo, uporabljeno v slikovni datoteki. Slike enake velikosti lahko enostavno skrijemo v slikovne datoteke nosilca z Indeks kakovosti strukturne podobnosti (SSIM) temelji na uporabo zadnjih 2 ali 3 bitov vsake RGB vrednosti vsakega izračunavanju treh pojmov, in sicer izraza svetilnosti, piksla vsebnika, kot da se dve sliki prekrivata, ena od njih pa je kontrastnega in strukturnega izraza. Celoten indeks je skoraj nevidna. Sprememba se nam na pogled zdi nespremenjena. multiplikativna kombinacija treh pojmov [5]. "Skrito" sliko se pridobi s črtanjem, z uporabo določenega programa, bitov slike nosilca in povečanjem svetlosti [9][5]. Mrežna steganografija: Podatke lahko skrijemo v protokolu za nadzor omrežja, katerega se uporablja kot nosilec v omrežnih protokolih TCP, UDP ali ICMP. V modelu OSI obstajajo kanali, Skupne metode prikrivanja podatkov v digitalnih slikah kamor s pomočjo steganografije lahko vstavimo skrivna vključujejo: sporočila v neporabljenih glavah TCP/IP paketa [8]. Maskiranje in filtriranje: Te metode skrivajo podatke na Avdio steganografija: Steganografijo z zvočnimi datotekami način, podoben vodnim žigom na papirju. To lahko storimo na je težko zaznati, ker majhne spremembe v zvočni datoteki lahko primer s spreminjanjem svetilnosti delov slike. Vidne lastnosti zaznamo kot šum ali degradacijo, ki jo lahko povzroči postopek slike se sicer spreminjajo, vendar je popačenje komaj opazno. Ta snemanja. Pri tej metodi je tajno sporočilo običajno skrito v metoda je glede na stiskanje veliko bolj robustna od modifikacije zvočnem signalu, ki se spremeni v binarno zaporedje povezane LSB, saj so informacije skrite na vidnih delih slike [5][9]. zvočne datoteke. Vendar je to veliko težji način uporabe Transformacije: To je bolj zapleten način skrivanja naslovnega predmeta kot steganografija slike in besedila. Ker so informacij v sliki. Na sliki se uporabijo različni algoritmi in avdio in video datoteke večje velikosti, se dodatne prostore v preobrazbe, da se v njej skrijejo informacije. DCT (Neposredna njihovih glavah lahko uporabi tudi za vstavljanje skritih transformacija kosinusa) je ena takih metod. Ta algoritem podatkov. stiskanja uporablja za pretvorbo zaporednih blokov slike 8 x 8 Slike lahko vstavimo v video datoteko tako, da zamenjamo slikovnih pik v 64 koeficientov DCT. Orodja za steganografijo okvir v videoposnetku ali dele slike na več določenih okvirih. Te lahko uporabijo LSB kvantiziranega koeficienta DCT za slike si lahko ogledamo tako, da video posnetek zaustavimo ali skrivanje informacij. Poleg DCT lahko slike obdelujemo s hitro predvajamo z večjo hitrostjo. Ko se videoposnetek predvaja z Fourierovo transformacijo in valutno transformacijo. Z drugimi normalno hitrostjo, je sprememba tako majhna, da človeško oko lastnostmi slike, kot je svetilnost, je mogoče manipulirati. ne zazna razlike [5][11]. V prihodnosti bo najpomembnejša uporaba steganografskih Video steganografija: Je tehnika skrivanja vseh vrst datotek tehnik verjetno na področju digitalnega vodnega označevanja za ali informacij v digitalni video format. Prednost te tehnike je sledenje avtorskih pravic in lastništva elektronskih medijev. V velika količina podatkov, ki jo je mogoče skriti v notranjosti in organih pregona je tudi vedno večja zaskrbljenost glede uporabe dejstvo, da gre za gibljiv tok slik in zvokov. To si lahko steganografije za izmenjavo nezakonitega gradiva prek slik na predstavljamo kot kombinacijo slikovne stenografije in zvočne spletnih straneh, zvočnih in drugih datotek [7]. steganografije. Video kot kombinacijo slik se uporablja kot nosilec za skrite informacije. Diskretna kosinusna transformacija 2.3 Steganografija v digitalnih medijih t.i. DCT spremeni vrednosti, npr. 8.667 do 9, v ta spremenjeni del se skrije podatke v vsaki od slik v videoposnetku, česar Glede na pojavnost v digitalnih medijih govorimo o človeško oko ne opazi. Uporablja se formate H.264, Mp4, MPEG, steganografiji v besedilnih, slikovnih, avdio in video datotekah AVI ali druge [8][11]. ter o mrežni steganografiji. Steganografija v besedilnih datotekah: Skrivanje sporočil 2.4 Značilnosti steganografskih datotek v besedilnih datotekah je najlažja in najstarejša tehnika, ki vključuje sprememba oblike obstoječega besedila, spreminjanje V steganografiji mora sporočilo, ki je skrito znotraj datoteke, besed v besedilu in ustvarjanje naključnih zaporedij znakov. upoštevati nekatere od spodaj navedenih značilnosti. 649 Skrivanje zmogljivosti: Ta funkcija obravnava velikost Vodni žig se vstavi neposredno v datoteko, po navadi z informacij, ki jih je mogoče skriti znotraj naslovne datoteke. rahlimi nihanji svetlosti slikovnih pik. Te spremembe so zelo Večja zmogljivost skrivanja omogoča uporabo majhnega ovitka subtilne in jih človeško oko ne vidi. Vzorci večkrat omogočijo in tako zmanjša širino pasu, ki je potrebna za prenos stego- obnovitev vodnega žiga, tudi če odstranimo dele medijev. Na primer, če imamo RGB sliko velikosti 200 x 200 večpredstavnostne datoteke. Nekateri vodni žigi lahko preživijo slikovnih pik, to pomeni, da imamo 120.000 barvnih vrednosti, tudi po omejenem številu urejanj večpredstavnostne datoteke, ki ki jih je treba uporabiti kot naslovnice skrivnega sporočila (200: vključuje spreminjanje kontrasta in filtriranje. širina x 200: višina x 3: R, G , B). Če za skrivanje sporočila uporabimo samo en bit po barvnem kanalu, imamo kapaciteto 3.2 Testiranje in izboljšanje vstavljanja vodnega skrivanja 120.000 bitov ali 15.000 bajtov, če za skrivanje žiga sporočila uporabimo 2 bita na barvni kanal, imamo 30.000 bajtov, Za testiranje in izboljšanje tehnik vstavljanja vodnih žigov je bilo če pa uporabimo samo en barvni kanal in en bit na piksel, bo razvitih več metod za napad ali razbijanje le-tega: uničenje zmogljivost skrivanja 40.000 bitov ali 5.000 bajtov. vodnega žiga (napadi robustnosti), onemogočanje odkrivanje Zaznavna preglednost: Zaznavna preglednost je pomembna predstavitvenih napadov, ponarejanje vodnih žigov, značilnost steganografije. Vsak medij ima določene podatke za interpretacijski napadi, izkoriščanje pravnih napak. skrivanje informacij. Če se v ovitku skriva več informacij ali Uničenje vodnega žiga: Način uničenja vodnega žiga temelji podatkov, potem to povzroči razkroj medija. Kot rezultat so na poskusu odstranitve vodnega žiga brez poškodbe stego-mediji in naslovnice na videz drugačni. Če napadalec opazi večpredstavnostne datoteke. Poznamo dve skupini takšnih to izkrivljanje, potem naša steganografska tehnika ne uspe in napadov: obdelavo signalov ter analitične in algoritmične napade. obstaja možnost, da napadalec razkrije ali poškoduje naše izvirno V prvo skupino spadajo skupne operacije obdelave sporočilo. večpredstavnostnih datotek, kot so stiskanje, filtriranje, Robustnost: Robustnost je zmožnost skritega sporočila, da spreminjanje velikosti, tiskanje in skeniranje. Druga skupina ostane nepoškodovano, tudi če je stego-medij podvržen temelji na odstranitvi ali oslabitvi vodnega žiga z uporabo transformaciji, ostrenju, linearnemu in nelinearnemu filtriranju, posebne metode vstavljanja in odkrivanja vodnega tesnila. skaliranju in zamegljevanju, obrezovanju ter različnim drugim Primer takega napada je generiranje nove večpredstavnostne tehnikam. datoteke s kombiniranjem različnih variant iste datoteke z Odpornost na nedovoljene posege: Od vseh lastnosti je ta vodnim žigom. Na takšen način se zmanjšuje moč vodnega žiga. funkcija skoraj najpomembnejša. Če je napadalec uspel uničiti Onemogočenje odkrivanja vodnih žigov: Za preprečitev steganografsko tehniko, potem lastnost odpornosti proti zaznave vodnega žiga se uporablja različne tehnike manipulacije napadalcem otežuje spreminjanje ali poškodovanje izvirnih z vsebino tesnila, vendar tako, da žig ni odstranjen. Primeri takih podatkov. napadov vključujejo spreminjanje lokacije vodnega žiga v večpredstavnostne datoteke, njihovo vrtenje ali spreminjanje 3 VODNI ŽIG velikosti. Ponarejanje vodnih žigov: Ti napadi temeljijo na napačnih Vodni žig je postopek podpisovanja digitalnih medijev (slik, ali večkratnih interpretacijah vodnega žiga. Napadalec lahko na besedil, avdio in videoposnetkov) z namenom varovanja pravic primer poskuša v ciljno večpredstavnostno datoteko vstaviti intelektualne lastnine. Vodni žig pomaga vstaviti prstni odtis, ki dodaten vodni žig, ki je enake trdnosti kot originalni vodni pečat. ga je mogoče prepoznati [8]. Na ta način je nemogoče nedvoumno in pravilno določiti Digitalni vodni žig temelji na vstavljanju dodatnih informacij lastništvo datoteke. v izvirno datoteko (imetnik) na način, da se kakovost nosilca ne Izkoriščanje pravnih napak: Takšni napadi lahko izzovejo spremeni do te mere, da bi postalo opazno dodajanje žiga [1][9]. vodni žig z izkoriščanjem možnih napak v naslednje komponente: pravna zakonodaja v zvezi z varstvom avtorskih 3.1 Uporaba vodnega žiga pravic in lastništva digitalne informacije, verodostojnost Danes se vodni žig uporablja za naslednje namene: lastnikov in napadalcev, finančna lastništva lastnikov in Varovanje avtorskih pravic: Onemogoči krajo lastništva napadalci, izvedenci in odvetniške pristojnosti. digitalne multimedije. Pomembno je, da žiga ne moremo odstraniti nepooblaščeno in je odporen različnim spremembam nosilnega signala [7]. 4 STEGANALIZA Zaščita pred kopiranjem: Nadzira naprave za kopiranje Steganaliza je postopek odkrivanja steganografskih datotek, ki podatkov in preprečuje kopiranje zaščitene večpredstavnostne temelji na preučevanju variacij vzorčnih bitov in nenavadno vsebine. velikih datotek. Steganaliza bi bila lahko preprosto opredeljena Avtentikacija: Avtentikacija večpredstavnostnih vsebin kot odkrivanje steganografije s strani tretje osebe. To poteka na doda žig po celotnem nosilnem signalu. različne načine in običajno temelji na tem, koliko je predhodnih Shranjevanje dodatnih informacij: Dodajanje podatkov, ki informacij na voljo. Ali ima analitik dostop do vseh medijev in lahko služijo kot zapiski z večpredstavnostnimi datotekami. algoritmov, bo to močno vplivalo na metodo, ki jo uporablja. Uporablja se posebne metode dodajanja žiga, ki podpirajo Cilji steganalize so med drugim, da prepoznamo sumljive shranjevanje večjega nabora podatkov, hkrati pa ohranjajo nize podatkov, na primer signalov ali datotek, znotraj katerih je združljivost s starejšimi brskalniki medijev. potencialno skrivno sporočilo. Določiti je potrebno, ali so bili tajni podatki šifrirani v steganografski datoteki. Prav tako je 650 potrebno ugotoviti obstoj hrupa ali nepomembnih informacij obstoj skritega sporočila. Slike lahko vsebujejo izkrivljanja in znotraj domnevnega signala ali datoteke. Iz steganografske spremembe v barvi in svetilnosti[9]. datoteke moramo izvleči in dešifrirati vstavljeno sporočilo. Ponavljajoči se vzorci: Z analizo ponavljajočih se vzorcev je Za razliko od kriptoanalize, pri kateri je očitno, da šifrirani mogoče prepoznati uporabljeno steganografsko orodje ali skrite podatki vsebujejo sporočilo, se steganaliza po navadi začne z informacije. Preskušanje vzorcev se opravi s primerjanjem nekaj sumljivimi zbirkami podatkov, od katerih nobeden ni originalnega steganografskega nosilca s steganografsko datoteko, skrivno sporočilo. Z uporabo različnih naprednih metod ki vsebuje skrito sporočilo [9]. statistične analize steganalizator zmanjša nabor sumljivih Primerjava steganografskih datotek: S primerjavo informacij, dokler ne najde prave steganografske datoteke. različnih steganografskih datotek je mogoče najti vzorce, ki Informacije je mogoče skriti skoraj povsod na internetu in zato predstavljajo podpis oz. specifično steganografsko orodje. postopek precej otežujejo steganalizo. Zaznavanje takšnih podpisov je mogoče z uporabo posebnih avtomatiziranih orodij za iskanje pikslov, ki odstopajo od neke 4.1 Odkrivanje steganografije standardne vrednosti v določenem razdelku slik [9]. Steganaliza je učinkovita, kadar vemo, kje iskati skrivne Dopolnitev ali rezanje: Slika, izdelana z nekaterimi orodji za informacije, in/ali znamo prepoznati posamezne napade. steganografijo, ne ustreza nekaterim fiksnim velikostim, zato jo Mesta skrivnih informacij: Ena možnost je besedilo, ki je je potrebno rezati ali dopolniti s črnimi površinami. Možnost lahko skrito znotraj strani, če je enake barve kot ozadje. vdelanega sporočila v sliko nakazujejo tudi razlike v velikosti Tudi majhne razlike v prostorski razporeditvi besed in črt steganografske datoteke ter nenavadno veliko ali majhno število vsebujejo tajne podatke. edinstvenih barv znotraj palete slik [9]. Nebesedilni elementi, kot so slike, avdio ali video datoteke, na strani lahko vsebujejo skrite povezave ali sporočila. Povezave so lahko skrite s spremenjenim videzom. Na primer besedilo ni 5 ZAKLJUČEK poudarjeno ali ne spremeni barve ali oblike, ko gremo z miško Steganografija je prikrita izmenjava informacij, pri kateri samo nad njim. Najlažje najdemo skrite povezave na strani z iskalnim pošiljatelj in prejemnik razumeta vsebino posredovanega nizom "HREF =" znotraj HTML-ja spletne strani. S pritiskom na sporočila. Glavna cilja steganografije sta skrivna komunikacija tipko Tab se aktivirajo tudi povezave [10]. in vodni žig. Skrívnost komunikacije zajema zagotavljanje Komentarji so lahko prav tako priročen kraj za skrivanje alternativnih rešitev za besedilne in medijske datoteke. Vodni žig tajnih podatkov, ker je vsebina komentarjev vidna samo v kodi je postopek podpisovanja digitalnih medijev namenom varovanja HTML. Mnogi spletni brskalniki ignorirajo informacije v HTML, pravic intelektualne lastnine. Za dodatno zaščito je možna tudi ki jih ne morejo razlagati. Tako lahko na primer nenavadni uporaba steganografskega ključa, ki kodira skrivno sporočilo, strukturni elementi znotraj oznak HTML vsebujejo tajne podatke preden se ga vstavi v nosilec. [10]. Steganografija omogoča komunikacijo, ne da bi jo odkrili. Informacije se lahko skrije tudi v kodo HTML vsakega okvira Zaradi svojega temeljnega načela "nevidnosti" informacij se strani. pogosto uvršča med nezakonite dejavnosti. Kot varnostno Oblike staganografskih napadov: Prepoznavanje oblik metodo pa se jo lahko uporablja tudi na različnih povsem staganografskih napadov je lahko učinkovito za izvedbo legalnih področjih in dejavnostih, kot so: strukturiranje podatkov, steganalize. Lahko imamo na primer opraviti z napadom znanega medicinski posnetki, močni vodni žigi, vojaške aktivnosti, nosilca, pri katerem znana izvirna datoteka vsebuje skrivno sledenje in avtentikacija dokumentov, volitve in elektronski sporočilo. V steganografski datoteki je včasih možno prepoznati denar, radarski sistemi in daljinsko zaznavanje. Vsem pa je steganografsko orodje, torej algoritem, ki je bil uporabljen za skupno vsebovanje skrivnega sporočila za različne namene. vstavljanje skrivnega sporočila. Glede na pojavnost v digitalnih medijih govorimo o steganografiji v besedilnih, slikovnih, avdio in video datotekah 4.2 Osnovne tehnike steganalize ter o mrežni steganografiji. Med pomembnimi staganografskimi Analiza skritih podatkov vključuje različne dejavnosti: tehnikami in metodami so: prostorska domena, preoblikovanje odkrivanje, črpanje ter onemogočanje ali uničevanje skritih domene, širjenje spektra, statistična metoda, ukrep uspešnosti, informacij. tehnika izkrivljanja, maksiranje in filtriranje ter transformacije. Skrivanje informacij znotraj digitalnega medija povzroči V steganografiji mora v datoteki ali mediju skrito sporočilo spremembe v značilnostih tega medija, na primer z neko obliko upoštevati določene značilnosti, na primer zmogljivost skrivanja degradacije ali druge nenavadne lastnosti. Preglejmo nekatere glede na velikost informacij, zaznavno preglednost, odpornost na najbolj priljubljene tehnike steganalize. nedovoljene posege in robustnost oz. zmožnost skritega Nenavadni vzorci: Nenavadni vzorci v steganografskih sporočila, da ostane nepoškodovano. datotekah pomenijo, da je znotraj njih morda skrito sporočilo. Z Steganaliza ponuja učinkovite metode za uspešno zaznavanje različnimi orodji in tehnikami je mogoče prepoznati te vzorce. in preprečevanje skritih informacij, zlasti v kriminalnih Če želimo najti skrite podatke v neuporabljenih particijah, lahko dejavnostih. Skrivanje informacij znotraj digitalnega medija uporabimo različne filtre za prepoznavanje paketov TCP/IP, ki povzroči spremembe v značilnostih tega medija. Steganaliza z vsebujejo skrite ali napačne podatke. S pregledom besedila v opazovanjem in prepoznavanjem teh sprememb omogoča zaščito urejevalniku besedila lahko najdemo majhne nepravilnosti pri pred skrito komunikacijo. umeščanju besed in vrstic ali prevelike razmike, ki pomenijo 651 VIRI IN LITERATURA https:/ www.seer.ufrgs.br/rita/article/view/rita_v15_n1_p8 3-110/3587. [1] Decker S., Sharma R. K., 2001 Practical Challenges for Digital WatermarkingApplications (online), DOI= [7] Dhir V., Kaur H., 2019 An Empirical Analysis on Digital https:/ link.springer.com/content/pdf/10.1155/S111086570 Steganography To Secure The Data By Hiding (online), 2000574.pdf. DOI=http://www.ijsrr.co.in/images/full_pdf/1556021350_ sb16.pdf. [2] Kianersi R., 2017 A new approach for color image steganography using HSI color model (online), DOI= [8] Kaur H., Jyoti Rani I., 2016 A Survey on different https://www.academia.edu/31373101/A_new_approach_fo techniques of steganography (online), DOI= r_color_image_steganography_using_HSI_color_model. https://www.matec- conferences.org/articles/matecconf/pdf/2016/20/matecconf [3] Lake J., 2019 What is steganography and how does it _icaet2016_02003.pdf. differ from cryptography? https://www.comparitech.com/blog/information- [9] Chugh G., 2013 Image steganography techniques: a review security/what-is-steganography. article (online), DOI= http://acta.fih.upt.ro/pdf/2013- 3/ACTA-2013-3-17.pdf. [4] Hölbl, M., 2008. Skrivanje podatkov - steganografija. Monitor (online), DOI= [10] Debattista, K., 2010 The Threats of Steganography https://www.monitor.si/clanek/skrivanje-podatkov- (online), DOI= https://techtalk.gfi.com/threats- steganografija/123365. steganography. [5] Elbeji, R., Friendly 2018 Introduction To Steganography, [11] Unlu O., Karacan H., 2015 Lattice approach to video (online), DOI= https://medium.com/@rabi3elbeji/friendly- steganography (online), DOI= introduction-to-steganography-4cf032240904. https:/ www.researchgate.net/profile/Hacer_Karacan/publi cation/269405458_Lattice_approach_to_video_steganogra [6] Rocha A., Goldenstein S., 2008 Steganography and phy/links/5b8d286792851c1e12449d29/Lattice-approach- Steganalysis in Digital Multimedia, (online), DOI= to-video-steganography.pdf. 652 Varnost informacijskih sistemov Information systems security Roman Rehberger Šolski center Kranj Višja strokovna šola 4000 Kranj, Slovenija rehberger@siol.net POVZETEK sistemov. Dobri postopki za zagotavljanje varnosti informacijskih sistemov skušajo preprečiti nevarnosti in Računalniki in druge digitalne naprave so postale bistvenega ranljivosti znotraj in zunaj organizacije ali podjetja. Sestavljati pomena za poslovanje, izobraževanje, trgovino itd., vendar jih morajo procesi in načrti za zagotavljanje temeljnih načel postajajo tudi vedno bolj tarča napadov. Da lahko podjetje ali varnosti, ki so zaupnost, celovitost in razpoložljivost. posameznik zaupno uporablja računalniško napravo, je potrebno najprej zagotoviti, da naprava na kakršen koli način ni ogrožena 1.1 Zaupnost in da bodo vse komunikacije varne. Pričujoči članek prinaša pregled temeljnih načel varnosti informacijskih sistemov kot tudi Pri zaščiti informacij želimo omejiti dostop do zaupnih poglobljen pregled nekaterih orodjih in ukrepov, ki jih je mogoče informacij le na pooblaščene uporabnike, ki jim je le-ta dovoljen; sprejeti za ublažitev varnostnih groženj in izboljšanje varnosti v vsi drugi ne bi smeli ničesar vedeti o vsebini informacij, kar je organizacijah, ter opisuje pomembnost varnosti mobilnih naprav bistvo zaupnosti. Ukrepe za zaščito zaupnih informacij je treba in osebnih podatkov. sprejeti glede na pomembnost podatkov. Večja kot je pomembnost podatkov, večje je tveganje. Za varovanje KLJUČNE BESEDE zaupnosti informacij pred kibernetskimi napadi se lahko uporablja različne metode: šifriranje podatkov, biometrično Informacijska varnost, orodja za varnost informacij, mobilna preverjanje, uporaba močnega ID-ja uporabnika in gesla ter varnost, varnost osebnih podatkov ozaveščenost uporabnikov [1]. ABSTRACT Včasih varnostna zaupnost vključuje posebne treninge za osebe, ki imajo dostop do občutljivih dokumentov. Takšni Computers and other digital devices have become essential for treningi zajemajo seznanitev s tipičnimi varnostnimi tveganji, ki business, education, trade etc., however, they are also becoming lahko ogrožajo informacije, ter možnostmi zaščite pred tveganji. targets of attacks. To enable a company or an individual to use a Uporabniki pridobijo tudi znanje o kreiranju gesel in se naučijo computer device confidentially, it must be assured first, that the preprečevati neupoštevanje pravil glede ravnanja s podatki, ki bi device is not endangered in any way and that all communications ga sicer zagrešili ponevedoma in z dobrimi nameni, a bi lahko are safe. This paper brings an overview of basic principles of imelo katastrofalne posledice [2]. safety of information systems, a comprehensive overview of some tools and measures, which can be taken to palliate safety 1.2 Celovitost threats and to improve safety in organizations, and it describes the importance of safety of mobile devices and personal data. Celovitost pomeni zaščito informacij in podatkov na spletu pred spreminjanjem kibernetskih kriminalcev in zagotavlja KEYWORDS doslednost in točnost informacij v omrežju. Celovitost informacij in podatkov v kibernetskem prostoru je mogoče ohraniti z Information safety, tools for information safety, mobile safety, ustreznimi koraki, kot so dovoljenja do datotek, nadzor dostopa safety of personal data uporabnikov in digitalni podpis. Celovitost je zagotovilo, da informacije, do katerih dostopamo, niso bile spremenjene. 1 TEMELJNA NAČELA INFORMACIJSKE Informacijska integriteta tudi pomeni, da informacija VARNOSTI resnično predstavlja njen predvideni pomen. Informacije lahko izgubijo svojo integriteto s škodljivimi namerami, na primer, ko Vse postopke zagotavljanja varnosti in preprečevanja različnih nepooblaščena oseba izvede spremembo. Integriteto se lahko tveganj lahko združimo v pojem varnost informacijskih izgubi tudi nenamerno, na primer, ko računalnik zaradi napajanja poškoduje datoteko ali nekdo, ki je sicer pooblaščen za spremembo, pomotoma izbriše datoteko ali vnese napačne Permission to make digital or hard copies of part or all of this work for personal or podatke [3]. classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must 1.3 Razpoložljivost be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Tretje temeljno načelo informacijske varnosti je razpoložljivost. © 2020 Copyright held by the owner/author(s). Razpoložljivost je varnostna politika, ki zagotavlja, da lahko 653 vsak posameznik, zaposlen v organizaciji (javni ali zasebni), s dostopa (ACL) in nadzor dostopa na podlagi vlog (RBAC) pooblaščenim dostopom uporablja informacije in podatke na (slika 2). spletu v skladu z določeno stopnjo dostopa, potrjeno s strani Za vsak vir informacij, ki ga organizacija želi upravljati, se organizacije. Razpoložljivost pomeni, da lahko do informacij lahko ustvari seznam uporabnikov, ki lahko izvajajo določena dostopajo in jih spreminjajo vsi, ki so za to pooblaščeni, v dejanja, ki jih imenujemo seznam za nadzor dostopa ali ACL. Za ustreznem časovnem okviru. Ustrezen časovni okvir lahko glede vsakega uporabnika so dodeljene posebne pravice dostopa, kot na vrsto informacij pomeni različno. Podjetja, kot je so branje, pisanje, brisanje ali dodajanje. Samo uporabniki s temi Amazon.com, bodo zahtevala, da bodo njihovi strežniki na voljo pravicami lahko izvajajo željene funkcije. štiriindvajset ur na dan, sedem dni v tednu. Druga podjetja morda ACL-ji so preprosti za razumevanje in vzdrževanje, vendar ne bodo nezadovoljna, če njihovi spletni strežniki nekajkrat na pa imajo več pomanjkljivosti. Primarna pomanjkljivost je, da se leto ne bodo dosegljivi [1]. z vsakim informacijskim virom upravlja ločeno. Ko se število uporabnikov in virov povečuje, je ACL težje vzdrževati. To je privedlo do izboljšane metode nadzora dostopa, ki se imenuje 2 ORODJA ZA VARNOST INFORMACIJ nadzor dostopa na podlagi vlog ali RBAC. RBAC namesto Za zagotovitev zaupnosti, celovitosti in razpoložljivosti dajanja določenih pravic uporabnikom za dostop do vira informacij lahko organizacije izbirajo med različnimi orodji. informacij najprej dodeli vloge uporabnikom in jim nato dodeli Vsako od teh orodij je mogoče uporabiti kot del splošne politike dovoljen dostop. To omogoča administratorjem, da ločeno informacijske varnosti, ki bo obravnavana v ndaljevanju. upravljajo z uporabniki in vlogami, kar poenostavlja administracijo in izboljša varnost. 2.1 Preverjanje pristnosti Orodja za preverjanje pristnosti se uporabljajo za zagotovitev, da je oseba, ki dostopa do informacij, dejansko tista, za katero se predstavlja. Preverjanje pristnosti je mogoče doseči z identifikacijo uporabnika po treh dejavnikih: nekaj, kar vedo; nekaj, kar imajo; ali nekaj, kar so. Najpogostejša oblika overjanja je ID uporabnika in geslo. V tem primeru se avtentikacija opravi s potrditvijo nečesa, kar uporabnik pozna (svojo ID in geslo). Toda to obliko Slika 2. Nadzor dostopa na podlagi vlog [5] overjanja je mogoče enostavno zlomiti in včasih so potrebne močnejše oblike avtentikacije. Identificirati nekoga samo po 2.3 Šifriranje nečem, kar imajo, na primer ključu ali kartici, je lahko tudi Organizacija mora večkrat prenašati informacije po spletu ali jih problematično. Če se identifikacijski žeton izgubi ali ukrade, se prenesti na zunanje medije, kot sta DVD ali bliskovni pogon. V identiteto uporabnika zlahka zlorabi. Končni dejavnik, to je nekaj, teh primerih bi lahko tudi s pravilno avtentifikacijo in nadzorom kar nekdo je, je veliko težje zlomiti. Ta dejavnik prepozna nepooblaščena oseba dostopala do podatkov, zato je uporabnika na podlagi fizičnih lastnosti, kot sta skeniranje oči ali priporočljivo šifriranje. Šifriranje je postopek kodiranja prstni odtis. Prepoznavanje nekoga po njihovih fizičnih podatkov ob njegovem prenosu ali shranjevanju, tako da jih lastnostih se imenuje biometrija. lahko preberejo samo pooblaščeni posamezniki. Kodiranje Varnejši način za preverjanje pristnosti uporabnika je opravi računalniški program, ki kodira navadno besedilo, ki ga je preverjanje pristnosti z več faktorji. Če združimo dva ali več treba prenesti; nato prejemnik prejme šifrirano besedilo in ga predhodno naštetih dejavnikov, postane vdor v sistem težji. dešifrira. Da bi to delovalo, se morata pošiljatelj in prejemnik Primer večfaktorske zaščite je uporaba žetona RSA SecurID, ki dogovoriti o načinu kodiranja, da lahko obe strani pravilno ustvarja novo kodo za dostop vsakih šestdeset sekund. Če se komunicirata. Obe strani si delita šifrirni ključ, ki jima omogoča, želimo prijaviti v informacijski vir s pomočjo naprave RSA, da drug drugemu zakodirata in dekodirata sporočila. Temu združimo štirimestno kodo PIN (nekaj, kar vemo) s kodo, ki jo rečemo simetrično šifriranje. Ta vrsta šifriranja je problematična, ustvari naprava. Edini način pravilne avtentifikacije je tako ker je ključ na voljo na dveh različnih mestih. poznavanje kode kot tudi naprave RSA (slika 1). Namesto simetričnega šifriranja se uporablja asimetrično šifriranje, pri katerem se uporabljata dva ključa: javni in zasebni ključ. Če želimo poslati šifrirano sporočilo, pridobimo javni ključ, ga kodiramo in pošljemo. Prejemnik nato zasebni ključ uporabi za dekodiranje. Javni ključ lahko prejme vsak, ki želi Slika 1. Žeton RSA SecurID [4] prejemniku poslati sporočilo. Vsak uporabnik potrebuje en 2.2 Nadzor dostopa zasebni in en javni ključ za zaščito sporočil. Zasebni ključ je potreben za dešifriranje nečesa, kar je poslano z javnim ključem. Ko je uporabnik overjen, je naslednji korak zagotoviti, da lahko dostopa le do tistih informacijskih virov, za katere je overjen s 2.4 Varnost z geslom strani organizacije. To se izvede z uporabo nadzora dostopa, ki Uporaba preprostega uporabniškega ID-ja/gesla ne velja za varen določa, kateri uporabniki so pooblaščeni za branje, spreminjanje, način preverjanja pristnosti, saj je enofaktorsko preverjanje dodajanje in/ali brisanje informacij. Obstaja več različnih pristnosti izredno enostavno zlomiti. Za zagotovitev, da gesla ne modelov nadzora dostopa. Najpomembnejša sta seznam nadzora morejo biti ogrožena, je treba sprejeti dobro varnostno politiko o 654 geslih. V nadaljevanju je nekaj pogostejših politik, ki bi jih podjetniških strežnikih, ampak bi morala obstajati tudi varnostna morale sprejeti organizacije. kopija posameznih računalnikov, ki se uporabljajo v celotni organizaciji. Dober rezervni načrt mora biti sestavljen iz več Zapletenost gesla komponent, ki jih navajamo spodaj. Eden od razlogov, da so gesla ogrožena je, da jih je mogoče enostavno uganiti. Nedavna raziskava je pokazala, da so prva tri Popolno razumevanje organizacijskih informacijskih virov gesla, ki so jih uporabniki uporabljajo v letu 2020 gesla, 123456, Kakšne podatke organizacija dejansko ima? Kje so shranjeni? 12345678 in password [6]. Geslo ne sme biti preprosto ali Nekateri podatki so lahko shranjeni na strežnikih organizacije, beseda, ki jo je mogoče najti v slovarju. Ena prvih stvari, ki jo bo drugi podatki na uporabnikovih trdih diskih, nekateri v oblaku in naredil heker je, da bo poskusil zlomiti geslo s preizkušanjem nekateri na drugih spletnih mestih. Organizacija mora narediti vsakega izraza v slovarju. Namesto tega je dober pravilnik o popoln seznam vseh informacij, ki jih je treba varnostno kopirati geslih tisti, ki zahteva uporabo najmanj osmih znakov in vsaj ene in določiti najboljši način za njihovo varnostno kopijo. velike črke, enega posebnega znaka in ene številke. Redno varnostno kopiranje vseh podatkov Redno menjanje gesla Pogostost kopiranja varnostnih kopij mora temeljiti na tem, kako Bistveno je, da uporabniki redno spreminjajo gesla. Uporabniki pomembni so podatki za podjetje, skupaj z zmožnostjo podjetja, bi morali spremeniti gesla vsakih šestdeset do devetdeset dni, s da nadomesti vse izgubljene podatke. Kritične podatke je treba čimer bi zagotovili, da nobenega gesla, ki je bilo ukradeno ali varnostno kopirati najmanj enkrat na dan, manj kritične podatke uganjeno, ni mogoče uporabiti. pa bi bilo mogoče varnostno kopirati najmanj enkrat na teden. Nedeljenje gesel Shranjevanje rezervnih nizov podatkov izven organizacije Usposobiti je potrebno zaposlene, da ne bodo delili gesel. Ena od Če so vsi varnostni podatki shranjujejo v istem objektu kot glavnih metod napadalcev za krajo gesel je, da jih preprosto izvirne kopije podatkov, bi en sam dogodek, na primer potres, razberejo tako, da povprašajo uporabnike ali skrbnike. Pred požar ali tornado, uničil tako originalne podatke kot varnostno vdorom napadalec pokliče službo za pomoč ali skrbnika sistema kopijo! Bistveno je, da je rezervna kopija shranjena na drugi in se pretvarja, da je pooblaščeni uporabnik, ki ima težave pri lokaciji. prijavi. Nato napadalec z zagotavljanjem osebnih podatkov o pooblaščenem uporabniku prepriča varnostno osebo, da Test obnovitve podatkov ponastavi geslo. Drug način, da napadalec pride do gesla je lažno Redno je treba varnostne kopije preizkusiti tako, da se nekateri predstavljanje po e-pošti. Do lažnega predstavljanja pride, ko podatki obnovijo. To bo zagotovilo, da bo postopek deloval in bo uporabnik prejme e-pošto, ki je videti, kot da je iz zaupanja zagotovilo zaupanje organizacije v rezervni načrt. vrednega vira, na primer njihove banke ali od delodajalca. V e- Organizacije bi morale preučiti svoje delovanje, da ugotovijo, pošti uporabnika prosi, da klikne povezavo in se prijavi na kakšen učinek bi imeli izpadi oz. izguba podatkov za poslovanje, spletno mesto, ki posnema pristno spletno mesto in vnese če njihova informacijska tehnologija ne bi bila na voljo za dolgo njegovo ID in geslo, ki jih napadalec nato zajame. Zelo obdobje in kako bi to vplivalo na njihovo poslovanje. pomembno je tudi, da gesel ne hranimo zapisanih na dostopnih Dodatni pojmi, povezani z varnostnim kopiranjem so: ali vidnih mestih, raje iznajdemo način, kako si bomo svoje geslo naprave za neprekinjeno napajanje (UPS) in nadomestna spletna lažje zapomnili (Glej poglavje 2.10). mesta. Slika 3 povzema neka načela za kreiranje močnih in varnih Za primere izpada električne napetosti so v sistemskem gesel. Podobno sliko bi lahko priporočili vsakemu uporabniku, prostoru nameščene naprave za neprekinjeno napajanje (UPS). da si jo namesti na vidno mesto ob svojem računalniku. To so baterije, ki s pomočjo inteligentne elektronike v primeru električnih izpadov varno izključijo strežnike. V nasprotnem primeru bi prišlo zaradi prehodnega pojava izpada napetosti do nepredvidljivih napak na podatkih ali strežniški opremi (diskovnih enotah, napajalnikih ipd.). Nekatere organizacije se odločijo za nadomestno spletno mesto, kjer je vedno posodobljena natančna kopija njihovih kritičnih podatkov. Ko primarno spletno mesto odpade, se nadomestno spletno mesto nemudoma prikaže na spletu, tako da je izpadov malo ali nič. Ker so informacije postale strateška prednost, se je celotna industrija razvila okoli tehnologij, potrebnih za izvajanje ustrezne varnostne strategije. Podjetje lahko sklene pogodbo s ponudnikom storitev, da ustvari varnostno kopijo vseh njihovih podatkov ali pa kupi velike količine spletnega prostora za Slika 3. Načela kreiranja močnih gesel [7] shranjevanje in to stori sam. Tehnologije, kot so omrežja skladiščnih prostorov in arhivski sistemi, zdaj uporablja večina 2.5 Varnostne kopije velikih podjetij. Orodje, bistvenega pomena za varnost informacij, je celovit Grafikon na sliki 4 prikazuje najpomembnejše razloge za rezervni načrt varnostnega kopiranja podatkov za celotno izgubo podatkov, ki naj vsakega uporabnika motivirajo za to, da organizacijo. Ne samo, da je treba varnostno kopirati podatke na redno in preudarjeno varnostno kopiranje podatkov. 655 2.9 Fizična varnost Organizacija lahko izvaja najboljšo shemo za preverjanje pristnosti tako da, razvije najboljši nadzor dostopa in namesti požarne zidove in omogoča preprečevanje vdorov, vendar njena varnost ne more biti popolna brez izvajanja fizične varnosti. Fizična varnost je zaščita dejanskih strojnih in mrežnih komponent, ki shranjujejo in prenašajo informacijske vire. Za izvajanje fizične varnosti mora organizacija prepoznati vse ranljive vire in sprejeti ukrepe za zagotovitev, da teh virov ni mogoče fizično posegati ali ukrasti. Najpomembnejše ukrepe Slika 4. Razlogi za izgubo podatkov [8] navajamo v nadaljevanju. 2.6 Požarni zidovi Zaklenjena vrata Vsa varnost je neuporabna, če lahko vsiljivec preprosto vstopi v Metoda, ki jo mora organizacija uporabiti za povečanje varnosti računalnik in fizično odstrani varovanje računalniške naprave. v svojem omrežju, je tudi požarni zid. Požarni zid je kot strojna Podatke z informacijami visoke vrednosti bi bilo treba zavarovati ali programska oprema (ali oboje). Strojni požarni zid je naprava, na lokaciji z omejenim dostopom. ki je povezana z omrežjem in filtrira pakete na podlagi nabora pravil. Programski požarni zid deluje v operacijskem sistemu in Zaznavanje fizičnega vdora prestreže pakete, ko prispejo do računalnika. Požarni zid zaščiti Sredstva z informacijami z visoko vrednostjo je treba spremljati vse strežnike in računalnike podjetja tako, da ustavi pakete zunaj z uporabo varnostnih kamer in drugih sredstev za odkrivanje omrežja organizacije, ki ne ustrezajo strogim naborom kriterijev. nepooblaščenega dostopa do fizičnih lokacij, kjer obstajajo. Požarni zid je lahko konfiguriran tudi tako, da omeji pretok Zavarovana oprema paketov, ki zapustijo organizacijo. Naprave je treba zakleniti, da se prepreči, da bi jih ukradli. Trdi Nekatere organizacije se lahko odločijo za uporabo več disk enega zaposlenega lahko vsebuje vse podatke o stranki, zato požarnih zidov kot del svoje varnostne konfiguracije omrežja, je nujno, da je zavarovan. tako da ustvarijo en ali več odsekov svojega omrežja, ki so delno zavarovani. Ta segment omrežja se imenuje DMZ, na njem Spremljanje okolja organizacija razpolaga z viri, ki potrebujejo širši dostop, vendar Strežniki organizacije in druga oprema z visoko vrednostjo jih je še vedno treba zavarovati. morajo biti vedno shranjeni v prostoru, v katerem se spremlja temperatura, vlaga in pretok zraka. Tveganje za okvaro strežnika 2.7 Sistemi za zaznavanje vdorov se poveča, ko ti dejavniki presežejo določen obseg. Sistem, ki ga je mogoče zaradi varnosti postaviti v omrežje, je Izobraževanje zaposlenih sistem za zaznavanje vdorov ali IDS (Intrusion Detection Eden najpogostejših načinov tatov za pridobivanje podatkov o System). IDS ne dodaja dodatne varnosti; namesto tega ponuja podjetju je, da ukradejo prenosne računalnike zaposlenih, funkcijo za prepoznavanje, ali je omrežje napadeno. IDS je medtem ko zaposleni potujejo. Zaposleni morajo biti mogoče konfigurirati za spremljanje določenih vrst dejavnosti in usposobljeni za zavarovanje svoje opreme, kadar so zunaj nato opozoriti varnostno osebje, če se ta dejavnost pojavi. IDS pisarne. prav tako lahko pozneje zabeleži različne vrste prometa v omrežju za analizo. IDS je bistven del vsake dobre varnostne 2.10 Uporabnost nastavitve. Pri iskanju varnih informacijskih virov morajo organizacije 2.8 Navidezna zasebna omrežja uravnotežiti potrebo po varnosti z potrebami uporabnikov za učinkovit dostop do teh virov in njihovo uporabo. Če varnostni Z uporabo požarnih zidov in drugih varnostnih tehnologij lahko ukrepi sistema otežijo uporabo, potem uporabniki najdejo organizacije učinkovito zaščitijo številne svoje informacijske načine, kako varnost lahko postane bolj ranljiva, kot bi bila brez vire, tako da postanejo nevidne za zunanji svet. Če zaposleni, ki varnostnih ukrepov. Vzemimo za primer pravilnike o geslu. Če dela od doma, zahteva dostop do nekaterih teh virov ali če je najet organizacija zahteva izjemno dolgo geslo z več posebnimi znaki, svetovalec, ki mora delati v internem podjetniškem omrežju z se lahko zaposleni zateče k temu, da ga zapiše in da v predal, saj oddaljene lokacije, se uporablja navidezno zasebno omrežje ali si ga ne bo mogel zapomniti. Bolj varno je, da iznajdemo system, VPN (Virtual Private Network). po katerem si lahko geslo zapomnimo. Slika 5 prikazuje predlog, VPN je razširitev podjetniškega zasebnega intraneta prek kako ustvariti močno geslo. javnih omrežij, kot je splet, z gradnjo varnih zasebnih povezav in skozi zasebne tunele. VPN omogoča varno sporočanje informacij prek spleta s povezovanjem oddaljenih uporabnikov, poslovalnic in poslovnih partnerjev v razširjeno skupno privatno omrežje. S kombinacijo programske opreme in dodatnih varnostnih ukrepov omogoča organizaciji omejen dostop do svojih omrežij in hkrati zagotavlja splošno varnost. 656 Ko ima uslužbenec dovoljenje za dostop in shranjevanje podatkov podjetja na svoji napravi, se pojavi drugačna varnostna grožnja, saj ta naprava lahko postane tarča tatov. Kraja mobilnih naprav (prenosnih računalnikov) je ena od glavnih metod, ki jih uporabljajo tatovi podatkov. Za zaščito mobilnih naprav so nekateri mobilni proizvjalci uvedli različico nabora funkcij Tier Two. Te so na splošno združene pod naslovom MTD (Mobile Threat Defense). Čeprav je MTD učinkovit in pogosto zadostuje za zaščito mobilnih Vir: https:/ www.varninainternetu.si/ Slika 5. Predlog za kreiranje močnega gesla [9] končnih točk, je še vedno do neke mere omejen s stopnjo vključitve teh rešitev v celotni varnostni system [11]. 2.11 Varnostna politika Organizacije bi morale razmisliti o pravilniku o mobilnih napravah, ki obravnava naslednja vprašanja: uporaba kamere, Poleg zgoraj naštetega tehničnega nadzora morajo organizacije uporaba snemanja glasu, nakupih aplikacij, šifriranje v izvajati tudi varnostne politike kot obliko upravnega nadzora. mirovanju, nastavitve samodejnega povezovanja Wi-Fi, Varnostna politika je dokument, ki pisno potrdi, kako podjetje nastavitve bluetooth, uporaba VPN, nastavitve gesla, poročanje načrtuje zaščito organizacije in informacijske tehnologije [10]. o izgubljenih ali ukradenih napravah in varnostno kopijo. Dobra politika varovanja informacij določa smernice za Poleg politik obstaja več različnih orodij, ki jih lahko zaposlene glede uporabe informacijskih virov podjetja in organizacija uporabi za zmanjšanje nekaterih teh tveganj. Na omogoča podjetju možnosti ukrepanja, če zaposleni krši politiko. primer, če je naprava ukradena ali izgubljena, lahko Po mnenju inštituta SANS je dobra politika "uradna, kratka geolokacijska programska oprema pomaga, da jo organizacija in na visoki ravni izjava ali načrt, ki vključuje splošna prepričanja, najde. V nekaterih primerih je morda smiselno namestiti cilje organizacije in sprejemljive postopke za določeno programsko opremo za odstranjevanje oddaljenih podatkov, ki področje." Politike zahtevajo skladnost, saj bo neupoštevanje bo odstranila podatke iz naprave, če to postane varnostno politike privedlo do disciplinskih ukrepov. Politika ne določa tveganje. posebnih tehničnih podrobnosti, temveč se osredotoča na želene rezultate. Varnostna politika mora temeljiti na vodilnih načelih zaupnosti, celovitosti in razpoložljivosti. 4 VARNOST OSEBNIH PODATKOV Dober primer varnostne politike, s katero se bodo mnogi seznanili, je politika uporabe spletnih strani. Politika uporabe Vsak od nas lahko kot posameznik sprejme ukrepe za spletnih strani določa odgovornosti zaposlenih v podjetju, ko za zagotovitev varnosti svojih računalniških tehnologij. Ni dostop do spleta uporabljajo vire podjetja. možnosti, da bi imeli stoodstotno varnost, vendar obstaja nekaj preprostih korakov, ki jih lahko naredimo za svojo varnost. Posodobimo svojo programsko opremo. Kadar koli prodajalec 3 MOBILNA VARNOST programske opreme ugotovi, da je bila v njihovi programski opremi odkrita pomanjkljivost v varnosti, bo sprožil posodobitev Ker se uporaba mobilnih naprav, kot so pametni telefoni in programske opreme, ki jo lahko prenesemo, da odpravimo tablični računalniki, povečuje, morajo biti organizacije težavo. Za avtomatizacijo tega procesa vklopimo samodejno pripravljene na sprejemanje varnostnih ukrepov. Eno prvih posodabljanje v računalniku. vprašanj v razmislek vsake organizacije je, ali sploh dovoljuje Namestimo protivirusno programsko opremo in jo mobilne naprave na delovnem mestu. Večina zaposlenih že ima posodabljajmo. Na trgu je veliko dobrih paketov protivirusne te naprave, zato se postavlja vprašanje, ali naj organizacije programske opreme, tudi brezplačnih. omogočijo zaposlenim, da prinesejo svoje naprave in jih Bodimo previdni pri povezovanju v omrežjem Wi-Fi. uporabljajo kot del svojih zaposlitvenih dejavnosti ali pa naj Uporabniki bi se morali zavedati svoje okolice, ko se na javnem naprave svojim zaposlenim priskrbijo organizacije. Uporaba mestu povežejo z omrežjem Wi-Fi in morajo biti pozorni na lastnih mobilnih naprav omogoča zaposlenim, da se bolj ostale uporabnike, ki tudi delijo to omrežje. Priporočljivo je, da integrirajo v svoje delo ter lahko prinesejo večje zadovoljstvo in ne dostopajo do svojih finančnih ali osebnih podatkov. Prav tako produktivnost zaposlenih. V mnogih primerih je zaposlenim se morajo zavedati, da lahko tudi povezovanje USB bliskovnih praktično nemogoče preprečiti, da bi imeli na delovnem mestu pogonov z napravo ogrozi varnost. Na napravo ne priklopimo svoje pametne telefone ali tablice. Če organizacija zagotavlja neznanega bliskovnega pogona, razen če ga lahko najprej svoje naprave zaposlenim, pridobi večji nadzor nad uporabo pregledamo s svojo varnostno programsko opremo. naprav, hkrati pa se prepreči možnosti upravnega in varnostnega Varnostno kopirajmo svoje podatke. Tako kot morajo nereda [1]. organizacije varnostno kopirati svoje podatke, tako jih morajo Mobilne naprave lahko predstavljajo številne edinstvene tudi uporabniki. In veljajo enaka pravila: to moramo storite redno varnostne izzive za organizacijo in kmalu postane njena največja in kopijo shraniti na drugem mestu. Preprosta rešitev je, da skrb tatvina intelektualne lastnine. Za zaposlenega z nastavimo račun s spletno varnostno kopijo za avtomatizacijo zlonamernimi nameni je zelo preprost postopek, da mobilno varnostnih kopij. napravo poveže z računalnikom prek USB vrat ali brezžično v Zavarujmo svoje račune z dvofaktorno avtentikacijo. Večina poslovno omrežje in naloži zaupne podatke. Prav tako bi bilo ponudnikov e-pošte in družbenih medijev ima možnost enostavno na skrivaj fotografirati proizvod ali storitev v dvofaktorne avtentikacije. Uporaba tega načina je preprosta: ko organizaciji. se prvič v račun prijavimo z neznanega računalnika, nam strežnik 657 pošlje besedilno sporočilo s kodo, ki jo moramo vnesti, da Informacijski sistemi obdelujejo in shranjujejo informacije, potrdimo, da smo v resnici ta oseba. To pomeni, da se nihče več ki omogočajo opravljanje primarnih storitev podjetij. Prav tako ne more prijaviti v naše račune, ne da bi poznal geslo in imel svoj pa vsebujejo tudi osebne podatke in informacije posameznikov mobilni telefon. in o posameznikih. Uporabniki informacijskih sistemov zato Gesla naj bodo dolga, močna in edinstvena. Za svoja osebna pričakujejo, da bo sistem opravljal svojo funkcijo učinkovito in gesla upoštevajmo ista pravila, ki se jih priporoča organizacijam. zanesljivo ter bo nudil varen dostop do podatkov in ščitil zaupne Gesla morajo biti dolga (osem ali več znakov) in vsebovati vsaj informacije pred nedovoljenim dostopom, spreminjanjem in dve od naslednjih: velike črke, številke in posebni znaki. izgubo. Uporabljajmo tudi različna gesla za različne račune, tako da če nekdo ukrade naše geslo za en račun, še vedno ne more dostopati do naših drugih računov. VIRI IN LITERATURA Bodimo previdni pri uporabi sumljivih povezav in prilog. Ko [1] Bourgeois, D. 2019. Information Systems for Business and prejmemo e-pošto, tvit (čivk) ali Facebook objavo, bodimo Beyond. Chapter 6. Str. 123-124. DOI= pozorni na vse povezave ali priloge, ki so tam vključene. Ne https://opentextbook.site/exports/ISBB-2019.pdf. klikajmo neposredno na povezavo, če nam je povezava sumljiva. [2] Rouse, M. 2016. Confidentiality, integrity, and availability Če želimo dostopati do spletnega mesta, ga poiščimo sami v (CIA triad). DOI= brskalniku in ga obiščimo neposredno od tam. https://whatis.techtarget.com/definition/Confidentiality- integrity-and-availability-CIA. 5 ZAKLJUČEK [3] Nieles, M., Dempsey K., Pillitteri V. Y. 2017. An Introduction to Information Security NIST Special Varnost informacijskih sistemov, znana tudi pod imenom Publication 800-12. Revision 1. Str. 2-3. DOI= INFOSEC, je široka tema na področju informacijske tehnologije, https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST ki se osredotoča na zaščito računalnikov, omrežij in njihovih .SP.800-12r1.pdf. uporabnikov. Skoraj vsa sodobna podjetja, pa tudi številne [4] TokenGuard. 2020. RSA SecurID 700 Authenticator, The družine in posamezniki, so utemeljeno zaskrbljeni zaradi gold standard in two-factor authentication. DOI= digitalnih tveganj. Te grožnje prihajajo v različnih oblikah in http://www.tokenguard.com/RSA-SecurID-SID700.asp. velikostih, vključno s krajo zasebnih informacij, krajo baze [5] Ekdahl, H. 2017. How to Successfully Introduce Role podatkov, namestitvijo zlonamerne programske opreme na Based Access Control into a Group Environment. računalnik in namernimi motnjami v storitvah. DOI=https://www.idenhaus.com/how-integrate-role-based- Varnost informacij je praksa preprečevanja nepooblaščenega access-control-group-environment. dostopa, uporabe, razkritja, motenj, spreminjanja, pregledovanja, [6] Wagenseil, P. 2020. These are the latest world's worst beleženja ali uničenja informacij. Zagotoviti je treba, da passwords. DOI= informacije ne bodo ogrožene na kakršen koli način, ko se https://www.tomsguide.com/news/worst-passwords-2020. pojavijo kritične težave. Te težave vključujejo naravne nesreče, [7] Hall, M. 2018. 11 Tips for a Stronger Password | okvaro računalnika/strežnika in fizične kraje, vendar niso DriveSavers Data Recovery. DOI= omejene nanje. https:/ www.pinterest.ch/pin/9007267991349304. Področje informacijske varnosti se je v zadnjih letih močno [8] FinancePro. 2017. Podjetniki, to so najpogostejši razlogi povečalo in razvijalo. Ponuja številna področja za specializacijo, za izgubo podatkov! Kako se zavarovati. DOI= vključno z varovanjem omrežij in sorodne infrastrukture, zaščito https:/ pro.finance.si/TELEKOM/8855297/Podjetniki-to- aplikacij in baz podatkov, varnostnim testiranjem, revizijo so-najpogostejsi-razlogi-za-izgubo-podatkov-Kako-se- informacijskih sistemov, načrtovanjem neprekinjenega zavarovati. poslovanja, odkrivanjem elektronskih zapisov in digitalno [9] Varni na internetu. 2011. Kako ustvarite močno geslo. forenziko. DOI=https://www.varninainternetu.si/article/zavarujte- Varnost informacijskih sistemov je mogoče zagotavljati samo geslo. s celovitim metodičnim pristopom, ki ne vključuje samo ključne [10] Rouse, M. 2016. Security policy. DOI= vstopne točke v omrežje, temveč celotno omrežje. Ključ do https://searchsecurity.techtarget.com/definition/security- celovitega pristopa je varnostna politika, s katero definiramo vse policy. varnostne procese in mehanizme za zaščito. Te varnostne procese, [11] Reed, J. 2019. The Evolution of Mobile SecurityBreaking mehanizme in druge elemente varnosti pa je potrebno uporabiti Down Barriers for a Holistic Security Ecosystem. str. 8. na mrežnem sistemskem in aplikativnem nivoju informacijske DOI= https://ww2.frost.com/wp- infrastrukture. content/uploads/2019/05/FS_WP_MobileSecurity-min.pdf. 658 Izzivi poučevanja slovenskega jezika in književnosti na daljavo Challenges of distance learning by Slovene teachers Maruša Robida Osnovna šola Šenčur Pipanova cesta 43 4208 Šenčur, Slovenija marusa.robida@os-sencur.si POVZETEK izzivom spoprijemal po svoje. Nihče izmed nas pa ni mogel obiti tehnologije, brez katere sam pouk na daljavo ne bi bil mogoč. Pouk od doma je od učencev zahteval veliko mero samostojnosti Izvedba pouka, podprtega s tehnologijo, zahteva temeljit in samoiniciativnosti. Tudi učitelji smo se znašli v situaciji, v premislek. Katero aplikacijo uporabiti? Katero orodje bi bilo kateri še nismo bili. V svojem prispevku sem opisala, kako sem najustreznejše? Tovrstne odločitve pa so bile v času šole na se lotila poučevanja slovenščine na daljavo in katera orodja, daljavo še toliko težje. Kaj bo učencem v tem nenavadnem času aplikacije so mi bile v pomoč. Predstavila sem tudi nekatere ustrezalo? Jim bo to orodje pomagalo doseči učne cilje? Bom s vidike šolanja na daljavo, ki bi lahko bile tudi del klasičnega to aplikacijo kot učiteljica dobila ustrezno povratno informacijo? pouka že v osnovni šoli. Šola na daljavo je namreč prinesla tudi Spraševala sem se tudi, ali aplikacija omogoča sodelovanje na določene segmente, ki bi jih bilo vredno obdržati. Še posebno to daljavo. velja za uvajanje sodobne tehnologije, brez katere si poučevanja v 21. stoletju ne moremo več zamišljati. 2 IZZIVI ŠOLE NA DALJAVO V ŠOLSKEM KLJUČNE BESEDE LETU 2019/2020 Poučevanje na daljavo, slovenščina, IKT V marcu 2020 smo se učitelji znašli v čisto novi vlogi. Večinoma ABSTRACT smo se najprej osredotočili na aplikacijo, s katero so bili učenci seznanjeni. Sama sem se tako osredotočila na MS Teams in MS Pupils were supposed to be independent and self-directed in the OneNote. time when school were closed. Teachers were also in totally new situation. This paper describes the pedagogic methods and tools 2.1 Predstavitev dela z MS Teams for distance learning which I used during lockdown. I’ve tried to demonstrate some aspects of distance learning that could be Teams je integrirano orodje, ki omogoča hkratno urejanje included in all lessons in primary school, not just during dokumentov v oblaku in komuniciranje. Namenjeno je emergency circumstances of lockdown. More and more teachers sodelovalnemu učenju znotraj enega okolja. [4] realize the importance of computer usage in the learning process, Sama sem že pred šolo na daljavo v okolju MS Teams especially in the 21st century. oblikovala ekipe in način dela s Teamsi predstavila v razredu. Vsak razred oz. skupina v 8. in 9. r. je imela v Teamsih svojo KEYWORDS ekipo. Sprva sem na ta način komunicirala z učenci, a večina tega načina še ni bila vajena. Pravzaprav sem v celotnem obdobju šole Distance learning, Slovene, ICT na daljavo nagovarjala učence prek eAsistenta in prek klepeta znotraj Teamsov. Veliko učencev si je že v marcu naložilo 1 UVOD aplikacijo Teams na telefon, tako da je naša komunikacija lepo potekala. S preostalimi pa smo klepetali prek eAsistenta. Naloga Kljub številnim projektom, izobraževanjem, vezanim na IKT, je učitelja je bila in je, da je prilagodljiv. učitelje šola na daljavo v marcu 2020 ujela nepripravljene. Ta Prek Teamsa smo imeli tudi video konference. Sprva smo se način dela se je namreč popolnoma razlikoval od metod tako dobivali v času razredne ure, kasneje sem prek video poučevanja, ki smo jih bili vajeni. Vsak učitelj se je z novim konference razložila težje dele snovi, izvedla pa sem tudi utrjevanje. Prek video konference sem tudi ocenjevala govorne nastope. Teams omogoča deljenje zaslona in aplikacij, ena od funkcij je tudi tabla, na katero se lahko riše. Predavanje se lahko Permission to make digital or hard copies of part or all of this work for personal or tudi snema, saj se prenese znotraj Office 365 v MS Stream. To je classroom use is granted without fee provided that copies are not made or distributed dobrodošlo, da si lahko učenci, ki se niso mogli udeležiti video for profit or commercial advantage and that copies bear this notice and the full konference, kasneje vse skupaj še enkrat ogledajo. citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). V maju 2020 so se učenci začeli pritoževati, da je video Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia srečanj preveč in da jim le-te zmedejo ustaljen urnik dela, kot so © 2020 Copyright held by the owner/author(s). 659 ga načrtovali od marca 2020. Vsekakor so bile video konference vrste – basen; vsebina je izvirna, prav tak je naslov; besedilo je potrebne, saj so ustrezna nadgradnja vnaprej posnetih razlag. ustrezno členjeno (razdeljeno je na odstavke; vsaj 3); pravopisna Prek video konferenc so se učenci lahko pogovarjali, obenem pa pravilnost. Vse basni sem pregledala še sama in ocenila delo so učenci razvijali komunikacijske veščine, ki so sicer učenca, ki je popravljal basen, in učenca, ki je napisal basen. pomemben del pouka slovenščine. Učencem sem v OneNotu, kjer sem podajala navodila za delo, Orodje Teams omogoča tudi, da z učenci delim vsebino in jim naročila, naj najprej poskušajo najti pohvalo: dosežke drug dodelim naloge. Tvorbne naloge je bilo prek Teamsa lažje drugega presojajo tako, da najprej iščejo pozitivne stvari. Nato vrednotiti, saj mi besedila ni bilo potrebno shranjevati, ampak dodajo predloge za izboljšanje (npr. svetujem ti, da pišeš sem popravljala Wordove dokumente direktno v brskalniku. odstavke; predlagam ti, da preden oddaš besedilo, še enkrat Kvalitetna gradiva, poustvarjalne naloge, ki jih učitelj prejme prebereš in popraviš pravopisne napake; menim, da bi bilo bolje, od učencev, je smiselno urediti tako, da jih vsi lahko vidijo. V ta da bi dopolnil del, ko zajec ukrade med; mislim, da bi lahko namen sem v spletnih učilnicah Teams pripravila neko skupno medvedov odnos do lisice natančneje opisal). mesto, kamor dajem gradiva vsem na ogled. Podobno bi se dalo MS Teams in MS OneNote sta orodji, ki sta učitelju v veliko narediti tudi v Padletu. pomoč. V Teamsu lahko oblikujemo spletne učilnice, prek Formsa pripravljamo preverjanja in jih delimo preko Teamsa. 2.2 Predstavitev dela z MS OneNote Teamsi omogočajo dajanje povratne informacije (slika 2), preko Znotraj Teamsov se lahko oblikuje tudi Zvezek za predavanja, v koledarja zlahka skličemo video konferenco. ozadju le-tega pa je aplikacija OneNote (slika 1). To je v bistvu digitalni zvezek, v katerem je več odsekov. Za vsak razred sem oblikovala svoj zvezek, zato so učenci delali samostojno, a vendar so prav zaradi medvrstniškega vrednotenja, ki bo razloženo v nadaljevanju, imeli priložnost, da sodelujejo med seboj. Učenci so kljub oddaljenosti skupaj oblikovali namene učenja in kriterije uspešnosti v OneNotu (odsek prostor za sodelovanje). Učencem lahko delim zadolžitve pod odsek domača naloga. Kasneje lahko zelo enostavno pregledujem vse naloge naenkrat. Zelo uporaben je tudi odsek prostor za sodelovanje, saj omogoča, da učenci skupaj oblikujejo dokument. Ta funkcija je podobna aplikaciji Padlet. Slika 60. Dajanje povratne informacije učencu OneNote mi je v času šole na daljavo pomagal, da sem lahko po datumih uredila učno snov, tako da učenci niso imeli težav. Do zvezka zlahka dostopajo in določene strani lahko tudi spreminjajo, sooblikujejo. Zdi pa se, da ti dve orodji nista ravno enostavni za učence. Kljub navodilom, ki so jih dobili, se nekateri učenci niso znašli v Oblaku 365. Posneti bi morala video posnetek, kako uporabljati OneNote in Teams ali pa imeti vsaj videokonferenco na to temo. Le-to sem imela, a prepozno, saj je kar nekaj učencev potožilo, da se jim zdi delo zahtevno. V letošnjem šolskem letu bom večkrat znotraj klasičnega pouka pokazala, kako se Teamsi in OneNote uporabljajo. S pomočjo Slika 59. Delo v OneNotu tabličnih računalnikov bodo vse tudi sami preizkusili. Tako bomo bolje pripravljeni na morebitno karanteno in posledično Pogosto sem v času šole na daljavo v odsek domača naloga šolo na daljavo. postavila vprašanje, vezano na snov, da sem dobila hitro povratno informacijo, ali lahko sledijo učni snovi. Pogosto so tudi odgovarjali na vprašanja, vezana na posnetek, film, ki so si 3 SLABE PLATI ŠOLANJA NA DALJAVO ga morali ogledati. Zdi se, da je bilo najbolj problematično to, da učitelj ni mogel Uporabnost digitalnega zvezka pa se je izkazala predvsem, ko zaznati odziva učencev. Ni bilo prave povratne informacije, sem ugotovila, da lahko preko OneNota izpeljem medvrstniško učitelj je lahko samo ugibal o učenčevem predznanju. Kljub vrednotenje. To je ena izmed zelo uporabnih sodobnih video konferencam pa je bil učitelj še vedno negotov, saj spletno pedagoških metod, ki je vezana na formativno spremljanje. [1] okolje ne more nadomestiti pristnega stika z učenci. Najprej so učenci sami tvorili neko besedilo (npr. pri pouku Učitelj pa je naletel še na problem, ko je uvajal novo književnosti so v 7. razredu tvorili basen). Basen so oddali v aplikacijo, orodje. Ko učenci samostojno uporabljajo npr. odsek domača naloga. Vsakemu učencu sem v odsek domača tablične računalnike, lahko hitro opaziš, da je aplikacija za naloga v OneNotu naložila basen sošolca, ki jo je kritično učence prezahtevna, da ne vedo, kako jo uporabljati. Normalno ovrednotil po naprej postavljenih kriterijih: značilnosti besedilne je, da so na začetku težave. A sčasoma bi morala postati 660 aplikacija učencem tako pisana na kožo, da se z njo ne bi posebej daljavo je nastalo veliko zanimivih izdelkov, npr. učenci so ubadali, ampak bi s pomočjo aplikacije dosegali učne cilje. Na posneli svoje vloge o prebranih knjigah, vsebino prebranega so daljavo je bilo pa še posebej težavno ugotoviti, kako učencem preoblikovali v strip s pomočjo aplikacija Storyboard That aplikacija ustreza. (slika 3). 4 PRILOŽNOSTI ZA IZBOLJŠAVO Ena izmed slabosti šolanja na daljavo je bila tudi to, da je bilo delo zgolj individualno. Iz dokumenta, ki ga je izdalo Ministrstvo za izobraževanje, znanost in šport avgusta 2020, naj bi bilo delo vezano tudi na delo dvojicah. [5] Potrebno je izbrati spletno okolje, ki omogoča tovrstno delo. Sama sem izbrala delo z OneNote, s katerim sem izvedla medvrstniško vrednotenje, ko so Slika 61. Strip na temo pesmi Zabušant – avtor pesmi učenci drug drugemu popravljali besedila. Tako so med seboj J. Prevert (avtorica stripa: sedmošolka) sodelovali, si izmenjavali svoje ideje, misli. S tem so tudi vzdrževali socialne stike med seboj, kar je bilo za njihovo počutje Pozitivna plat te aplikacije je, da je brezplačna in da za učence takrat zelo pomembno. ni zelo zahtevna. Bolj pomembno je, da se učenci osredotočijo Potrebno je bilo dobro premisliti, katere vsebine so primerne na samo poustvarjanje kot pa na to, kako ravnati z orodjem. Če za delo na daljavo. Na študijskih skupinah v avgustu 2020 nam je vsega preveč, postane učencem delo mukotrpno. je bilo predlagano, katere vsebine iz učnega načrta so primerne Je pa kar nekaj možnosti, kar se dokazov tiče. Lahko bi na za delo na daljavo. Učni načrt bo tudi digitaliziran, kar nam bo v določeno temo posneli multimedijsko predstavitev (film, zvočno pomoč v primeru, če bi moralo delo ponovno potekati od doma. oddajo, fotografijo, projekcijo), lahko bi oblikovali publicistično [5] besedilo, kviz za sošolce, lahko bi govorno predstavili neko Kar se obravnave književnosti tiče, bi bilo smotrno brati vsebino, lahko bi likovno poustvarjali, naredili izdelek itd. daljše besedilo po delih. Vmes naj bi učitelj pripravil vprašanja, Možnosti je veliko in prav je, da učitelj spodbuja svoje učence k morda organiziral video srečanje, da bi preveril, ali je besedilo izvirnosti. učencem razumljivo, razjasnil bi morebitne neznane besede. V Po raziskavi Zavoda za šolstvo je kar slaba polovica (48,9 %) času šole na daljavo so imeli učenci nalogo, da preberejo knjigo, učiteljic in učiteljev v času šole na daljavo največkrat uporabljala ki so jo imeli doma. Lahko so si jo seveda tudi izposodili preko elektronsko pošto za stik z učenci. Sledita uporaba Biblosa. Brali so po delih in po prebranih začetnih poglavjih so videokonferenc (19,1 %) in spletno učno okolje (17,4 %). [6] v odseku domača naloga (v OneNotu) odgovarjali na naslednja Elektronska pošta ne omogoča stika med učenci, kot to vprašanja: kaj vam je zaenkrat pri knjigi najbolj všeč, kateri je omogočajo videokonference in določena spletna okolja. Učenci tvoj najljubši junak, kako mislite, da se bo knjiga končala. S tem morajo imeti kljub oddaljenosti občutek, da so povezani, da sem spodbudila zanimanje za nadaljnje branje knjige. imajo možnost izmenjave svojih misli, idej. V času šole na Zdi se, da smo učitelji v času dela na daljavo premalo daljavo so večino učencev prevevali občutki osamljenosti. pozornosti namenili sprotnemu preverjanju. To bi bilo najbolj Zagotovo bi uporaba aplikacij, ki omogočajo medsebojno smotrno narediti kar v spletni učilnici, saj so jo učenci redno sodelovanje, stisko učencev omilila. pregledovali. Preverjanje bi moralo biti po sklopih, in to večkrat mesečno. Le tako bi učitelj lahko sledil napredku učencev oz. 5 ZAKLJUČEK opazil pomanjkljivosti v znanju. Odločila sem se, da bodo sprotna preverjanja v spletni učilnici v letošnjem šolskem letu Šolanje na daljavo je nas, učitelje, prisililo, da smo se lotili metod učenci reševali tudi med klasičnim poukom, da bi se tega načina poučevanja, ki so nam bile doslej neznanka. Posnetki razlag, dela navadili, če bi razred morebiti moral ostati v karanteni. videokonference, delo v spletnih učilnicah so postali temelj Zelo pomemben segment šole na daljavo je posnetek razlage. učnega procesa. Čeprav smo si vsi učitelji želeli klasičnega Obvezno morajo biti na posnetku tudi dodana navodila za delo, pouka, smo zaznali, da so določeni segmenti šolanja na daljavo saj se znanje pridobiva le z aktivnim delom in ne le poslušanjem. taki, ki bi jih bilo vredno ohraniti. Delo v spletnih učilnicah bi Posnetek naj ne bo daljši od nekaj minut. [3] Pri slovenščini so moralo biti pomemben segment pouka tudi takrat, ko poteka se izkazale video razlage dobre predvsem za obravnavo pouk v šoli. Če bodo učenci vajeni dela v spletnih učilnicah, bo slovničnih vsebin in za zgodovinski pregled literarnih obdobij. šolski proces čim manj moten, če učenci ostanejo doma. Tudi Sama sem za pripravo razlag uporabila program ActivePresenter. raziskovalec dr. Saša Prešern [2] meni, da naj del pouka (npr. dve Video konference lahko pripomoreju k temu, da učenci uri na teden) učitelji še naprej izvajamo prek spleta zato, ker je ostanejo med seboj povezani in da jih lahko učitelj nagovori. to dobro za učence in ker smo tako pripravljeni na podobne Navsezadnje lahko urijo svoje konverzacijske spretnosti, saj brez izzive, kot je covid-19. video konferenc te veščine ne bi mogli razvijati. Strokovnjaki Učitelj je dolžan organizirati delo tako, da se vzdržujejo menijo, da je video konferenca primerna takrat, ko učence socialni stiki in da imajo učenci možnost med seboj sodelovati. spodbudimo k sodelovanju, k razpravi, dajanju mnenj, Izbirajo naj se učna okolja in aplikacije, ki ta način dela razčiščevanju dilem, koristna pa je tudi za pridobivanje povratnih spodbujajo. Uporaba IKT pri poučevanju pa zahteva nekoliko informacij. [3] drugačne pristope pri poučevanju, zato se je učitelj dolžan Potrebno se je zavedati, da moramo učitelji učence spodbujati, izobraževati in krepiti svoje digitalne kompetence. da so učenčevi izdelki kot dokazi čim izvirnejši. V času šole na 661 LITERATURA IN VIRI [3] https://video.arnes.si/portal/asset.zul?id=c2hZEVWUrSCa FQQxgKSyZ4PY (pridobljeno 20. 8. 2020). [1] Holcar Brunauer, A., Bizjak C., Borstner M., Cotič Pajntar, J. idr. 2017. Formativno spremljanje v podporo [4] https://podpora.sio.si/izobrazevanje-na-daljavo-spletno- učenju. Zavod RS za šolstvo, Ljubljana. komuniciranje-in-sodelovanje/ (pridobljeno 20. 8. 2020). [2] Prešern, S. 2020. Virus razkriva, kaj je zares pomembno v [5] https://www.zrss.si/digitalnaknjiznica/Covid_19/52/ življenju. Delo (8. 8. 2020), 10. (pridobljeno 20. 8. 2020). [6] https://www.zrss.si/digitalnaknjiznica/IzobrazevanjeNaDal javo/36/ (pridobljeno 15. 8. 2020). 662 Medpredmetno povezovanje in uporaba informacijsko- komunikacijske tehnologije pri poučevanju na daljavo v osnovni šoli Cross-curricular integration and use of information communication technologies in distance learning in primary school Simona Samida Cerk Osnovna šola Franceta Bevka Ljubljana Ulica Pohorskega bataljona 1 1000 Ljubljana, Slovenija simonasamida@gmail.com POVZETEK centre. Students who are brought to independent with innovative approaches thinking and research in accordance with modern Prispevek predstavlja možnosti medpredmetnega povezovanja in guidelines didactics. Teaching in a modern school is supposed to uporabo informacijsko-komunikacijske tehnologije pri be based on those teaching approaches that enable holistic poučevanju na daljavo v osnovni šoli. Osredotočamo se na learning. They create a rich learning environment which is based sodobno šolo, ki v središče postavlja inovativne in aktivne on active methods and team works. Cross-curricular integration učence. Učence, ki jih z inovativnimi pristopi pripeljemo k supported by application information and communication samostojnemu razmišljanju in raziskovanju v skladu s sodobnimi technology is important part of learning and teaching, as this is smernicami didaktike. Pouk v sodobni šoli naj bi bil zasnovan na an integrated approach where pupils are combining knowledge, tistih pristopih poučevanja, ki omogočajo celostno učenje, content and learning skills. Students develop interest and ustvarjajo bogato učno okolje ter temeljijo na aktivnih metodah motivation to learn while using information communication tools. in oblikah dela. Medpredmetno povezovanje podprto z uporabo Establishment and selection of an appropriate digital learning informacijsko-komunikacijske tehnologije predstavlja environment at distance learning and the thoughtful use of pomemben del učenja in poučevanja, saj je to celosten pristop, modern didactic approaches represent the basic foundation of kjer se povezujejo znanja, vsebine in učne spretnosti. Učenci pri quality conducting distance learning. The paper shows the medpredmetnem povezovanju preko različnih informacijsko- derivation options interdisciplinary lessons in the fifth grade komunikacijskih orodij razvijajo interes in motivacijo za učenje. using information communication technologies in distance Vzpostavitev in izbira ustreznega digitalnega učnega okolja pri learning and learning. poučevanju na daljavo ter premišljena uporaba sodobnih didaktičnih pristopov predstavljata osnovni temelj kakovostne KEYWORDS izvedbe pouka na daljavo. Prispevek prikazuje možnosti izpeljave medpredmetnega pouka v petem razredu z uporabo Cross-curricular integration, information and communication informacijsko-komunikacijske tehnologije pri poučevanju in technology, distance education, integrated learning učenju na daljavo. KLJUČNE BESEDE 1 UVOD Medpredmetno povezovanje, informacijsko-komunikacijska Sodobna šola v središče postavlja inovativnega in aktivnega tehnologija, izobraževanje na daljavo, celostno učenje učenca, ki preko inovativnih pristopov poučevanja samostojno razmišlja in raziskuje. Pouk v sodobni šoli naj bi temeljil na ABSTRACT celostnem učenju z uporabo aktivnih učnih oblik in metod dela. The paper presents the possibilities of interdisciplinary Medpredmetno povezovanje predstavlja pomemben del učenja in integration and use of information and communication poučevanja, saj stremi k povezovanju znanj in s tem ciljev znotraj technology in distance learning in primary school. We focus on enega predmeta in med različnimi predmeti. Učenci pri a modern school that puts innovative and active students at the medpredmetnem povezovanju razvijajo interes in motivacijo za učenje. Pri tem dosegajo visok učni uspeh in kažejo večjo radovednost za usvajanje interdisciplinarnih znanj. Še posebej je medpredmetno povezovanje smiselno pri izobraževanju na daljavo, saj delo po učnih in tematskih sklopih v okviru več Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed predmetov omogoča lažje sledenje in spremljanje napredka, for profit or commercial advantage and that copies bear this notice and the full osmišlja znanje, pri učencih dviga učno motivacijo in interes za citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). učenje. Če je uporaba informacijsko-komunikacijske tehnologije Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia pri klasičnem pouku predstavljala zgolj dopolnitev in popestritev © 2020 Copyright held by the owner/author(s). 663 izobraževanja, je postala pri izobraževanju na daljavo nujno in omogoča povezovanje in združevanje različnih učnih ciljev v neobhodno potrebna. Vzpostavitev ustreznega digitalno smiselno celoto. Tako celostno učenje zagotavlja povezavo in podprtega učnega okolja je postala ključna za kakovostno poenotenje znanja, učence globoko motivira k drugačnemu izvedbo pouka na daljavo. Ustrezno e-kompetenten učitelj, ki v zaznavanju ustvarjalnemu povezovanju vsebin in oblikovanju takšnem digitalno podprtem učnem okolju pri svojem delu novih in drugačnih miselnih modelov, struktur in sistemov [6]. premišljeno uporablja sodobne in inovativne didaktične pristope, Temeljni cilji, ki obsegajo zahtevo po usklajenem načrtovanju lahko učence pripelje do višjih oblik učenja in znanja. učiteljev različnih predmetov in področij, so doseganje večje S prispevkom želimo prikazati možnosti izpeljave stopnje povezanosti med disciplinarnimi znanji, preprečitev izobraževanja na daljavo usmerjeno v medpredmetni koncept preobremenjenosti učencev, priprava na vseživljenjsko izobraževanja podprt z informacijsko-komunikacijsko izobraževanje in kakovostno življenje, povečanje kakovosti in tehnologijo. trajnosti pridobljenega znanja ter razvijanje sposobnosti samostojnega, ustvarjalnega in kritičnega mišljenja ter presojanja [1]. 2 MEDPREDMETNO POVEZOVANJE Medpredmetno povezovanje je celosten didaktični pristop s 2.2 Kdaj in kako povezovati vsebine? katerim horizontalno in vertikalno povezujemo znanja, vsebine Medpredmetnega pristopa poučevanja se poslužujemo takrat, ko in učne spretnosti. Medpredmetno povezovanje spodbuja je to smiselno, ko je učna snov primerna in imamo zadovoljive samostojno in aktivno pridobivanje učnih izkušenj, in poteka v možnosti za izvedbo. Možnosti medpredmetnih povezav celoviti dejavnosti učenca, vključuje njegove spoznavne, zasledimo v učnih načrtih posameznih predmetov. Iz njih lahko čustvene in telesne funkcije [8]. Medpredmetno povezovanje je razberemo, kateri predmeti se najbolje vežejo med seboj in katere nastalo zaradi težnje po doseganju večje kakovosti pouka in vsebine lahko povežemo, da uresničimo cilje iz učnih načrtov prilagajanja načinov poučevanja sodobnim spoznanjem o naravi posameznih predmetov [10]. učenja, pri katerem se upošteva celostno spoznavanje učne Poznamo več načinov udejanjanja medpredmetnih povezav. stvarnosti [13]. Takšno načrtovanje pouka prinaša vsebinsko Nekatere lahko uresničimo vsako učno uro, nekatere pa preko racionalnost, ekonomičnost, boljšo učno uspešnost [9]. različnih organizacijskih oblik, kot so šole v naravi, projektni Medpredmetno povezovanje temelji na idejah konstruktivizma dnevi, dnevi dejavnosti, le-te zahtevajo več časa, bolj Piageta, Deweya, Brunerja in drugih, ki so učenje z poglobljeno obravnavo vsebin posameznih predmetov in bolj razumevanjem ali smiselno učenje povezovali z razumevanjem prilagodljiv urnik [10]. Medpredmetne povezave morajo biti pojmov in njihovim povezovanjem v strukture znanja. Tako je prilagojene predznanju učencev in učenčevi razvojni stopnji. učenje z medpredmetnim povezovanjem nasprotje učenju na Povezujemo le tiste vsebine, ki so smiselne in ne delamo povezav pamet posameznih izoliranih vsebin. Ta posnema resnične tam, kjer ni smiselno, da bi jih medpredmetno povezovali [4]. življenjske situacije, kar je za učence dober zgled in močan motiv za učenje. Medpredmetno povezovanje podpirajo tudi različne 2.3 Medpredmetno povezovanje pri pouku na raziskave z drugih področij, na primer raziskave o delovanju daljavo v osnovni šoli možganov in obdelavi informacij. Novo znanje se organizira po vzorcu prejšnjih izkušenj in pomenu, ki iz njih izhaja. Učenje Pri pouku na daljavo je potrebno racionalizirati učne vsebine in novih vsebin je torej uspešnejše, če izhaja iz otrokovih izkušenj se osredotočiti na temeljne cilje posameznih učnih predmetov, in poteka v zanj znanih in razumljivih okoliščinah [6]. saj naj bi učenci pri tovrstni obliki pouka za usvajanje in Medpredmetno povezovanje upošteva učenčevo predznanje, razumevanje znanja porabili tudi do trikrat več časa. Če se stališča, pričakovanja, čustva in socialno komponento. poslužujemo medpredmetnega povezovanja kot didaktičnega Uresničuje načelo celovitosti učnega procesa, povezuje učenje z pristopa, lahko vsebine posameznih učnih predmetov življenjem ob spodbujanju izkušenjskega učenja pri učencih, obravnavamo ekonomično, celostno, poglobljeno in z večjim priznava otrokovo individualnost z upoštevanjem njegovih motivacijskim učinkom. Še posebej je medpredmetno potreb, interesov, zmogljivosti. Je odprt učni model, ki omogoča povezovanje enostavno izpeljati v prvem in drugem triletju učitelju in učencem fleksibilno prilagajanje sprotnim potrebam osnovne šole, saj večino predmetov poučuje razredni učitelj, ki in situacijam. Od učitelja takšen pristop dela zahteva prožnost, ima poglobljen vpogled v učno vsebino in cilje učnih predmetov, širino v znanju, empatijo in posluh za potrebe, interese in ki jih poučuje. Učitelji se pri medpredmetnem pristopu sposobnosti učencev [7]. osredotočajo na doseganje ciljev ter na krepitev znanj skozi povezovanje vsebin. Učencem je pri tovrstnem pristopu učna 2.1 Zakaj medpredmetno povezovati učne snov bolj približana, celostno obravnavana, lažje razumljiva, vsebine? hkrati pa dviga učno motivacijo in interes za učenje. Primeri medpredmetnih učnih tem v petem razredu: Medpredmetno povezovanje je nastalo zaradi težnje po • prazgodovina, koliščarji, Karantanija, Rimljani, doseganju boljše kakovosti pouka in prilagajanja načinov srednjeveški gradovi – družba, likovna umetnost, poučevanja sodobnim spoznavanjem učenčeve učne stvarnosti glasbena umetnost, slovenščina; [13]. Medpredmetni pristop za učence prinaša mnoge prednosti, • opis rastline, naravna barvila – slovenščina, kot so celostno dojemanje sveta, izkušenjsko učenje, prenašanje gospodinjstvo; usvojenega znanja in procesov na druga področja, individualizacija in diferenciacija pouka. Tovrstno poučevanje in • naravno-geografske enote Slovenije, kulinarika, šege in navade – družba, glasbena umetnost, likovna učenje presega okvirje posameznega učnega predmeta, saj umetnost, gospodinjstvo; 664 • geometrija – matematika, šport; Omogoča rabo raznih oblik in metod dela, učence večinoma • zdrava prehrana – naravoslovje in tehnika, motivira za pouk in omogoča hitrejše in kakovostnejše doseganje gospodinjstvo, matematika; ciljev pouka [12]. • soda in liha števila, števila do milijona – matematika šport. 4 IZOBRAŽEVANJE NA DALJAVO Možnosti medpredmetnih povezav je v prvem in drugem Če je uporaba informacijsko-komunikacijske tehnologije pri triletju zelo veliko, pri tem je pomembno, da povezave učnih klasičnem pouku predstavljala zgolj dopolnitev in popestritev vsebin ne nastajajo na silo. Potrebno je upoštevati tudi posebnosti izobraževanja, je postala pri izobraževanju na daljavo nujno in specialno didaktičnega načrtovanja posameznih predmetov, saj neobhodno potrebna. Vzpostavitev ustreznega digitalno lahko v nasprotnem primeru siromašimo proces učenja. podprtega učnega okolja je postala ključna za kakovostno Medpredmetno povezovanje bo kakovostno takrat, ko bo izvedbo pouka na daljavo. smiselno vključevalo vsebine, procese, znanja, spretnosti itd., ki spodbujajo učenje iz različnih zornih kotov posameznih 4.1 Orodja za učenje in poučevanje na daljavo predmetnih področij. Na podlagi tega nastane učni transfer znanj in spretnosti, ki omogočajo razvijanje sistemskega mišljenja in Za poučevanje na daljavo se uporabljajo različna orodja, ki mrežo znanja za ustvarjalno reševanje učnih in življenjskih prenašajo informacije, ali pa služijo kot pomoč pri usvajanju in okoliščin [8].. razumevanju učnih vsebin. Elektronska pošta je eden izmed najpogostejših načinov komuniciranja med učiteljem in učenci, saj poleg osnovne pisne 3 INFORMACIJSKO-KOMUNIKACIJSKA komunikacije omogoča tudi pošiljanje različnih dokumentov. TEHNOLOGIJA Zelo pogosto uporabljeno orodje je spletna učilnica. Spletna učilnica Moodle je eden izmed programskih paketov za izvajanje Raba informacijsko-komunikacijske tehnologije postaja e-izobraževanja. Učitelj lahko v spletni učilnici objavlja gradiva, integralni del pouka. Uporaba le-te je v veliki meri odvisna od daje domače naloge, pripenja videoposnetke z razlagami, učitelja, od njegovega individualnega znanja in njegovih objavlja fotografije izdelkov, s svojimi učenci klepeta v pristopov poučevanja. Sodoben in kvaliteten pouk sovpada z klepetalnici. Učenci v spletni učilnici odpirajo dokumente, ki jih ustrezno izbiro učne tehnologije [11]. je pripel učitelj, oddajajo domače naloge, klepetajo v klepetalnici, Informacijsko-komunikacijska tehnologija je vključena v vse rešujejo kvize. Učitelj lahko v spletni učilnici spremlja in procese, ki se dogajajo v šolskem okolju. Tehnologija pripomore pregleduje aktivnost učencev, pregleduje domače naloge in daje k učenju s širitvijo dostopa kot tudi z vpeljevanjem raznovrstnih povratne informacije učencem, spremlja uspešnost reševanja poti učenja. Učni proces in vsebine so z uporabo informacijsko- kvizov itd. komunikacijske tehnologije atraktivnejše. Uporaba Videokonferenčne storitve so namenjene organizaciji informacijsko-komunikacijske tehnologije pri pouku poveča sestankov, predavanj, pa tudi za vzpostavljanje stikov z učenci produktivnost učiteljev in prihrani čas predvsem pri pripravi in ali za komunikacijo in sodelovanje med samimi učenci. posodabljanju dnevnih priprav, prilagajanju individualnim Orodje Kahoot! je namenjeno izdelavi kvizov, razprav, potrebam učencev in predstavljanju učne snovi [2]. vprašalnikov in je ena izmed atraktivnejših aplikacij za Kompetenten učitelj je z uporabo informacijsko- ponavljanje in utrjevanje znanja. Kahoot! omogoča sestavljanje komunikacijske tehnologije uspešnejši, ustvarjalnejši in lastnih kvizov ali uporabo že obstoječih, ki jih ustvarjalci delijo inovativnejši, saj uporablja veljavne in zanesljive podatke ter se z drugimi uporabniki portala. Kviz je mogoče reševati zaveda pravnih in etičnih načel varne in odgovorne uporabe individualno, ali pa v obliki razrednega tekmovanja. Časovna tehnologije [3]. Različne študije uporabe informacijsko omejitev reševanja posameznega vprašanja, točkovanje in komunikacijske tehnologije v izobraževanju kažejo, da privlačna glasba pripomorejo k napetosti med reševanjem kviza informacijsko-komunikacijska tehnologija olajša učenje in dvigajo učno motivacijo. otrokom z drugačnimi sposobnostmi in načini učenja, omogoča učinkovitejše učenje in poučevanje z vključevanjem več čutov ter daje možnost boljšega prilagajanja in sledenje pouku [2]. 5 ZAKLJUČEK V zadnjem času se namesto računalniške pismenosti uporablja pojem digitalna zmožnost oziroma digitalna Medpredmetno povezovanje in uporaba informacijsko- kompetenca. »Digitalna zmožnost oz. kompetenca je zavedanje, komunikacijske tehnologije sta nepogrešljivi komponenti odnos in sposobnost vsakega posameznika, da smiselno sodobnega in inovativnega izobraževanja na daljavo. uporablja digitalna orodja in storitve za razločevanje, dostopanje, Izpostavljamo celosten pristop, kjer se povezujejo znanja, upravljanje, vključevanje, vrednotenje, analiziranje in vsebine in učne spretnosti. Učenci preko sodobnih in inovativnih sintetiziranje digitalnih virov, da ustvarja nova znanja, nove metod ter uporabe različnih informacijsko-komunikacijskih medijske izraze in se sporazumeva z drugimi v specifičnih orodij usvajajo učno snov, dosegajo višje oblike učenja ter življenjskih okoliščinah, da bi tako omogočil konstruktivna povezujejo znanja. Pri učenju so motivirani, osredotočeni in družbena dejanja in da bi lahko razmišljal o teh procesih«. [5] radovedni, saj je pot do usvajanja znanja podprta z digitalnimi Učni načrt za slovenščino razvijanje digitalnih zmožnosti učnimi okolji, ki so v današnjem času nujna in neobhodno povezuje z razvijanjem sporazumevalne zmožnosti v slovenskem potrebna. Z medpredmetnimi povezavami lahko vsebine jeziku. Ta vključuje zavestno in kritično rabo informacijske posameznih učnih predmetov obravnavamo bolj ekonomično, tehnologije pri opravljanju šolskih obveznosti in dejavnosti. 665 celostno in poglobljeno, kar se še posebej obrestuje pri [6] Krnel, D., Hodnik Čadež, T., Potočnik, N., Medved- izobraževanju na daljavo. Udovič, V. (2008). Medpredmetno povezovanje v 1. razredu – večpredmetni delovni učbenik. Naravoslovna solnica letnik 12, št. 3, str. 6-9. LITERATURA IN VIRI [7] Kuščer, K. (2000). Integriran pouk: priročnik za [1] Bevc, V. (2005). Medpredmetno načrtovanje in obravnavo tematskega sklopa Sadovnjak. Ljubljana: Zavod povezovanje vzgojno-izobraževalnega dela. V Spodbujanje Republike Slovenije za šolstvo. aktivne vloge učenca v razredu.: zbornik prispevkov, ur. [8] Sicherl-Kafol, B. (2008). Medpredmetno povezovanje v Tanja Rupnik Vec, str. 50-59. Ljubljana: Zavod Republike osnovni šoli. Didakta: letnik 17, št. 19, str. 7-9. Slovenije za šolstvo. [9] Strmičnik, F. (2001). Didaktika: osrednje teoretične teme. [2] Brečko, B. N., Vehovar, V. (2008). Informacijsko- Ljubljana: Znanstveni inštitut Filozofske fakultete. komunikacijska tehnologija pri poučevanju in učenju v slovenskih šolah. Ljubljana: pedagoški inštitut. [10] Štemberger, V. (2008). Načrtovanje in izvajanje medpredmetnih povezav. V Učitelj v vlogi raziskovalca: [3] Gerlič, I- (2000). Sodobna informacijsko-komunikacijska akcijsko raziskovanje na področjih medpredmetnega tehnologija v izobraževanju. Ljubljana: DZS. povezovanja in vzgojne zasnove v javni šoli, ur. Janez Krek [4] Hodnik-Čadež, T. (2008). Učitelj kot raziskovalec , str. 112-130. Ljubljana: Pedagoška fakulteta. medpredmetnega povezovanja. V Učitelj v vlogi [11] Tišler, T. (2006 ). Spodbujanje uporabe informacijsko- raziskovalca: akcijsko raziskovanje na področjih komunikacijske tehnologije na osnovni šoli. Članek povzet medpredmetnega povezovanja in vzgojne zasnove v javni dne, 22.8.2019, na https://solazaravnatelje.si/ISBN/961- šoli, ur. Janez Krek , str. 131-149. Ljubljana: Pedagoška 6637-04-5.pdf fakulteta. [12] Učni načrt za slovenščino (2019). Ljubljana: Zavod [5] Kerndl, M. (2013). Diferenciacija in individualizacija pri republike Slovenije za šolstvo. pouku književnosti v tretjem triletju osnovne šole. Doktorska disertacija: Maribor: Univerza v Mariboru, [13] Žibert, S. (2007). Medpredmetna povezanost vzgojnih Filozofska fakulteta. predmetov v prvih treh razredih. Razredni pouk: letnik 9, št. 3, str. 27. 666 Preverjanje in ocenjevanje znanja z aplikacijo Liveworksheet Assessment of knowledge with Liveworksheet App Saša Silovšek OŠ Griže Griže 1a 3302 Griže, Slovenija sasa.silovsek@gmail.com POVZETEK Učenje s pomočjo sodobne tehnologije ni več le popestritev 1 UVOD vsakodnevnega učnega procesa, ampak je postala že stalna V učnem procesu je neizbežno potrebno stalno prizadevanje praksa v večinoma vseh razredih in pri večini predmetov. Učenci učiteljev za iskanje različnih načinov, da uspemo pri učencih živijo s sodobno tehnologijo na vsakem koraku, prav tako pa se sprožiti željo po znanju. Vse več učiteljev ugotavlja, da s pomočjo sodobnih spletnih aplikacij lahko veliko naučijo. Te tradicionalni pristopi pri vzgojno-izobraževalnem delu niso več niso le način njihovega komuniciranja, ampak tudi močno ustrezni, ker ne vodijo k zadovoljivim dosežkom učencev. Za motivacijsko orodje za učenje, utrjevanje znanja in, kot smo se učinkovito učenje je namreč ključno, da učence pouk pritegne, lahko prepričali v času karantene in izobraževanja na daljavo, da lahko učni izkušnji pripišejo pomen oziroma povezanost z tudi učinkovito orodje za preverjanje in ocenjevanje znanja na življenjem [4]. Bolj so učenci motivirani za delo, boljši je uspeh. daljavo. Eno izmed takšnih uporabnih spletnih orodij je Če uspemo učence motivirati in v njih vzbuditi pozitivna čustva, LiveWorksheet, ki nam omogoča preprosto sestavo smo na dobri poti [5]. Če bi bile dejavnosti vedno zanimive in interaktivnega učnega lista za sprotno utrjevanje, preverjanje ali zabavne, bi učence že same po sebi pritegnile, zato moramo ocenjevanje znanja. učitelji prilagajati poučevanje tako, da pripravljamo za učence zanimive didaktične dejavnosti, ki ustrezajo namenu in ki jih KLJUČNE BESEDE učenci z veseljem opravljajo. Za eno izmed uspešnih načinov se Sodobna tehnologija, preverjanje in ocenjevanje znanja, učenje je pokazala aplikacija Liveworksheet. Z njo lahko popestrimo na daljavo, Liveworksheet vsakodnevno rutino v razredu, pokazala pa se je tudi kot uspešno orodje za učenje na daljavo. Namenjena je spreminjanju različnih ABSTRACT tradicionalnih učnih listov, pisnih preverjanj ali ocenjevanj Learning with the help of modern technology is no longer just a znanja npr. v wordu, pdf-ju, power pointu, v interaktivne učne diversification of the everyday learning process, but it has liste. Liveworksheet je orodje, do katerega lahko dostopamo zelo already become everyday routine in almost all classes and almost hitro in preprosto ter brezplačno, potebujemo le računalnik ali all subjects. Students live with modern technology all the time tablico in spletno povezavo. Gre za eno bolj priljubljenih and they can also learn a lot with the help of modern web aplikacij s katero lahko spremljamo učenčevo razumevanje in applications. These are not only a way of communicating, but napredek (formativno spremljanje), hkrati pa ga lahko also a powerful motivational tool for learning and, as we were uporabimo tudi za ocenjevanje znanja, lahko pa tudi kot uvod v able to see during quarantine, also an effective tool for checking novo snov za ugotavljanje predznanja. V času ocenjevanja lahko and assessing knowledge at a distance learning. One such useful učitelj nadzoruje učenca na daljavo preko videa, audio ali online tool is LiveWorksheet which allows us to easily compile »screen share« načina. [2] an interactive worksheet to test knowledge. KEYWORDS 2 OPIS Modern technology, assessment of knowledge, distance learning, Orodje Liveworksheets nam omogoča, da svoje tradicionalne Liveworksheet delovne liste za tiskanje (doc, pdf, ppt, jpg. .) spremenimo v interaktivne spletne vaje, ki se samodejno ovrednotijo [1]. Učenci lahko delovne liste rešujejo preko spleta in odgovore pošljejo učitelju. Prednost tega je večplastna: predstavlja večjo motivacijo za učence, omogoči njim in učitelju takojšnjo Permission to make digital or hard copies of part or all of this work for personal or povratno informacijo, učitelju prihrani čas in je prijazen okolju classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full glede na prihranek papirja. Poleg tega interaktivni delovni listi v citation on the first page. Copyrights for third-party components of this work must celoti izkoristijo nove tehnologije, ki se uporabljajo pri be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia izobraževanju: lahko vključujejo zvok, videoposnetke, različne © 2020 Copyright held by the owner/author(s). tipe nalog kot so naloge izbirnega tipa, naloge dopolnjevanja in 667 kratkih odgovorov, naloge povezovanja in urejanja in celo slušne željene velikosti. Nato v besedilna polja zapišete pravilne in govorne vaje, ki jih morajo učenci izvajati z mikrofonom. odgovore. Če obstaja več možnih odgovorov, vnesete vse, ločene Delo v aplikaciji zahteva registracijo, ki jo opravite, preden s poševnicami. (Slika 2) lahko začnete z delom. Osnovna stran ponuja prijavo za učitelja ali prijavo za učenca. Ključne povezave so tri in sicer: iskanje ter uporaba že narejenih interaktivnih učnih listov, izdelava svojih lastnih interaktivnih učnih listov in povezovanje interaktivnih učnih listov v delovne zvezke. Meni Community je namenjen urejanju dela za prijavljenega uporabnika in urejanje gradiva za deljenje z učenci. Učenci dostopajo do gradiva tako, da jim učitelj preprosto pošlje povezavo ali pa učence vpiše v aplikacijo in jim dodeli Slika 2: Vstavimo besedilna polja in vanje vpišemo ustrezne ustrezne naloge za reševanje. Po reševanju izbranih ali odgovore (vir: dodeljenih nalog se jim avtomatično izpiše povratna informacija https://www.liveworksheets.com/lwsmaker/gettingstarted.asp) o uspešnosti. Le-ta upošteva samo odgovore, za katera so bila ustvarjena polja, ki jih sistem lahko točkuje, ne zna pa točkovati 3.2.2 Naloga spustnega tipa t. i. prostih odgovorov. Učencem lahko ponudite spustni seznam možnosti, med katerimi lahko izbirajo ustrezno rešitev. V tem primeru narišete besedilno polje in vnesete "choose:", ki mu sledijo možnosti, ločene s 3 IZDELAVA INTERAKTIVNIGA UČNEGA poševnicami, pravilni odgovor pa označite z zvezdico. (Slika 3) LISTA S pomočjo orodja lahko zelo enostavno izdelamo svoje lastne interaktivne učne liste, tako da naložimo svoj dokument v aplikacijo Liveworksheet (doc, pdf, jpg . .), ki bo nato pretvorjen v sliko. Nato na učni list samo vnesemo polja s pravimi odgovori. Obstaja tudi nekaj ukazov, ki se jih moramo naučiti za različne tipe nalog, kot so povleci - spusti, povezovanje, slušne vaje, govorne vaje itd.. Vendar je zelo enostavno obvladljivo, v pomoč pa so nam v orodju priloženi tutorial-i ali video priročniki. Seveda pa je potebno omeniti, da lahko v zbirki uporabimo tudi že izdelane interaktivne učne liste, ki zajemajo veliko različnih Slika 3: Izdelava vaje spustnega tipa (vir: jezikov in predmetnih področij in so jih bili učitelji pripravljeni https://www.liveworksheets.com/lwsmaker/gettingstarted.asp) dati v skupno rabo in deliti z ostalimi. [1] 3.2.3 Naloga izbirnega tipa 3.1 Naložite svoj učni list Pri nalogah tega tipa na pravilen odgovor vnesete »select: yes«, na napačen odgovor pa »select: no«. (Slika 4) Če gre za Kliknite na make interactive worksheets - izdelaj interaktivni vprašanje z več možnimi odgovori (na primer: "Izberite svojo učni list na vrhu strani (glavni meni) in kliknite get started - najljubšo barvo"), vnesete samo "select:". začni. Nato kliknite Select file - Izberi datoteko, choose the document - izberi dokument v računalniku in nato kliknite upload - naloži.(Slika 1) Datoteka mora biti v formatu doc, docx, pdf, jpg ali png. Omejitev velikosti je 5 MB. Ko se naloži, se bo dokument pojavil na zaslonu in takoj lahko pričnemo urejati in vstavljati besedilna polja v dokument. Slika 4: Izdelava vaje izbirnega tipa (vir: https://www.liveworksheets.com/lwsmaker/gettingstarted.asp) Slika 1: V prvem koraku naložimo svoj učni list (vir: https://www.liveworksheets.com/lwsmaker/index.asp) 3.2.4 Naloga povezovanja V besedilna polja vnesete "join:1", "join:2", "join:3" itd, ki jim 3.2 Izdelava različnih tipov nalog sledi isto število odgovorov. (Slika 5) Številke se ne smejo ponavljati. 3.2.1 Vstavljanje pravilnih odgovorov Na delovnem listu narišete besedilna polja za vstavljanje pravilnih odgovorov tako, da kliknite, pridržite in povlečete do 668 Slika 8: Izdelava govorne vaje (vir: Slika 5: Izdelava vaje povezovanja (vir: https://www.liveworksheets.com/lwsmaker/gettingstarted.asp) https://www.liveworksheets.com/lwsmaker/gettingstarted.asp) 3.3 Predogled 3.2.5 Naloga tipa povleci – spusti Kliknite gumb “preview” za predogled, da si ogledate svoj V besedilna polja vnesete "drag - povleci", ki ji sledi številka interaktivni delovni list in ga preverite. elementa, ki ga je treba povleči, in "drop - spusti", za njim pa številko ustreznega para. (Slika 6) Številke se ne smejo 3.4 Shranite učni list ponavljati. Če ste po predogledu zadovoljni z rezultatom, kliknite gumb za shranjevanje. Nato vnesete naslov učnega lista, uporabniško ime in geslo. Povezava do novega interaktivnega delovnega lista, ki jo lahko pošljete svojim učencem, vam bo takoj na razpolago. 3.5 Skupna raba učnega lista Če želite, lahko svoj interaktivni delovni list delite z drugimi uporabniki. Vnesti boste morali naslov, jezik, stopnjo, zadevo, starost, opis in vsebino delovnega lista. Te informacije bodo Slika 6: Izdelava vaje povleci – spusti (vir: drugim pomagale pri iskanju vašega delovnega lista. https://www.liveworksheets.com/lwsmaker/gettingstarted.asp) 3.2.6 Naloga slušnega tipa 3.6 Posredovanje učnih listov učencem Da, tako je: interaktivni učni list lahko pripravimo tudi do Obstajata dva načina za pošiljanje učnih listov učencem: Prva, govorjenja! V besedilna polja vnesete "listen - poslušaj:", ki mu enostavna, je kopiranje povezave učnega lista in pošiljanje le-te sledi beseda ali poved, ki jo bodo učenci slišali. (Slika 7) S po e-pošti, spletni učilnici, socialnih medijih itd. Ko učenci rešijo pomočjo sintetizatorja govora boste le še izbrali jezik in slušna učni list, svoje odgovore pošljejo učitelju (samodejno se bodo naloga za vajo, preverjanje ali ocenjevanje je pripravljena. preverili in točkovali, pravilni in nepravilni odgovori bodo nemudoma vidni in obarvani z zeleno in rdečo). (Slika 9) Za to možnost se učencem ni treba registrirati. Slika 7: Izdelava slušne vaje (vir: https://www.liveworksheets.com/lwsmaker/gettingstarted.asp) 3.2.7 Naloga govornega tipa V besedilna polja vnesete »speak:«, ki mu sledi odgovor. (Slika 8) Nato izberete jezik. Če je možnih več odgovorov, vnesite vse, vendar jih obvezno ločite s poševnicami. Trenutno so govorne vaje delovale le v brskalniku Google Chrome. Slika 9: Takojšnja povratna informacije o uspešnosti (vir: https://www.liveworksheets.com/worksheets/en/English_as_a_ Second_Language_(ESL)/Telling_the_time/The_hours_ub184z s) 669 Druga možnost zahteva več časa za pripravo, vendar je večkrat, preden so bili zadovoljni s svojimi rezultati in končni najboljša rešitev v primeru, če nameravate to spletno mesto s izdelek poslali učitelju. Prav to mi je bil neizpodbiten dokaz za svojimi učenci redno uporabljati. Lahko registrirate svoje učence tako željeno angažiranost, samoiniciativnost in motiviranost pri (ali jih povabite, da se prijavijo), sestavite interaktivne delovne učencih. Seveda se v primeru ocenjevanja med ponujenimi zvezke z najljubšimi delovnimi listi in jim dodelite delovne opcijami čas reševanja časovno omeji in tako prepreči večkratno zvezke. S pomočjo te možnosti lahko učenci dostopajo do t.i. reševanje. students' zone z uporabniškim imenom in geslom ter rešujejo Čeprav sama priprava interaktivnega učnega lista od učitelja vaje v svojih delovnih zvezkih. Vso njihovo delo bo shranjeno, zahteva bistveno več vloženega časa, se trud izplača, saj so tako da lahko kadar koli preverite njihovo delo in napredek. učenci za tako delo bistveno bolj motivirani in skoncentrirani. Temu primerno je tudi njihovo znanje večje. Menim, da bi bila 3.7 Kam učitelji prejmejo ovrednotene učne škoda, da ne bi izmenjevali dobrih praks in tudi v prihodnosti liste učencev uporabili tehnologije in novih načinov poučevanja in preverjanja Najpreprostejši način je, da učenci, potem ko rešijo učni list, znanja, bodisi pri poučevanju na daljavo kot tudi v samem kliknejo ponujeno možnost »Finish - Končaj«, nato izberejo razredu, saj postaja informacijsko-komunikacijska tehnologija v "Pošlji moje odgovore učitelju" in vnesejo vaš e-poštni naslov. današnjem času vedno bolj nepogrešljiv učni pripomoček, ki Nato boste v svojem e-poštnem sporočilu dobili obvestilo, vse predstavlja prednost vsem udeležencem v učnem procesu [3]. odgovore učencev pa lahko preverite tudi v sami aplikaciji v svojem poštnem predalu. VIRI IN LITERATURA Bolj zapletena, a še boljša možnost je, da izdelate svoj interaktivni delovni zvezek in vanj dodate svoje najljubše učne [1] Liveworksheet: https://www.liveworksheets.com/ liste (svoje ali pa učne liste drugih učiteljev, ki so jih delili v skupno rabo). Nato registrirate svoje učence in jim dodelite [2] The Benefits of Online Assessment: delovne zvezke. Kadarkoli lahko preverite njihovo delo, dodelite https://www.testreach.com/benefits-of-online-assessment- testreach.html domačo nalogo ali dodajate komentarje in opombe. [3] Advantages of using online assessment tools to evaluate students: https://www.creatrixcampus.com/blog/5- 4 ZAKLJUČEK advantages-using-online-assessment-tools-evaluate- students V času, ko so bile šolske učilnice prazne, smo bili učitelji primorani s pomočjo digitalne tehnologije iskati nove načine za [4] Rutar Ilc, Z., 2003: Pristopi k poučevanju, preverjanju in podajanje učne snovi na daljavo, ob tem pa je potrebno poudariti, ocenjevanju. Ljubljana: Zavod republike Slovenije za da je prav poseben izziv predstavljalo preverjanje in ocenjevanje šolstvo. znanja. Liveworksheet je samo ena izmed mnogih možnosti, ki [5] Boekaerts, M. 2013. Motivacija in čustva imajo ključno se je izkazala za učinkovito. Glavno prednost vidim v tem, da so vlogo pri učenju. V Dumont, H. et all. 2013. O naravi se po izjavah učencev in staršev celo zabavali ob reševanju učenja: Uporaba raziskav za navdih prakse, 2. izd., tovrstnih vaj, predvsem pa jim je bilo všeč, da so takoj dobili Ljubljana, Zavod RS za šolstvo, dostopno na: povratno informacijo o pravilnosti rešenega in svoji uspešnosti. http://ww.zrss.si/pdf/o-naraviucenja.pdf (24. 8. 2019). Nemalokrat so ob sprotnem preverjanju učni list reševali 670 Formativno spremljanje v času izobraževanja na daljavo Formative assessment in time of distance learning Nuša Skumavc Osnovna šola Predoslje Kranj Predoslje 17a 4000 Kranj, Slovenija nusa.skumavc@guest.arnes.si POVZETEK Formativno spremljanje je eno od učinkovitih načinov pouka, ki 1 UVOD učencem omogoča, da so soodgovorni za lastno znanje. V Marca 2020 smo vsi izobraževalci v Sloveniji vključno z učenci, preteklem šolskem letu smo zaradi epidemije koronavirusa dijaki in študenti, ostali doma in se šolali drugače, kot smo bili izobraževanje učencev nadaljevali na daljavo. V prispevku je do sedaj navajeni. Epidemija koronavirusa nas je prisilila, da smo predstavljena uporaba elementov formativnega spremljanja v spremenili način poučevanja, učenci pa načine učenja. Prejšnje obdobju izobraževanja na daljavo na primeru dveh učnih sklopov šolsko leto je naša šola vstopila v razvojno nalogo Uvajanje pri predmetu družba v četrtem razredu ob pomoči različnih formativnega spremljanja in inkluzivne paradigme. Gre za računalniških orodij in aplikacij. Rezultat dela po načelih projekt, ki traja dve leti. Tako smo tudi v času izobraževanja na formativnega spremljanja je dober, učenci so dosegli cilje, ki smo daljavo izvajali formativno spremljanje. Prilagoditi smo morali si jih zastavili. Poleg dobrih učnih rezultatov pa so učenci dosegli načine vključevanja elementov formativnega spremljanja v še mnoge cilje, ki krepijo kompetence s področja praktične pouk, ki je potekal na daljavo. uporabe IKT. KLJUČNE BESEDE 2 FORMATIVNO SPREMLJANJE Šolanje na daljavo, informacijska tehnologija, Google obrazci, Formativno spremljanje je način pouka, ki sta ga razvila Britanca Socrative, Xooltime Paul Black in Dylan William. Pri formativnem spremljanju je ABSTRACT učenec tisti, ki izgrajuje svoje znanje, učitelj pa ga pri tem podpira tako, da ves čas ugotavlja, kako napreduje ter pouk Formative assessment is one of the effective ways of teaching prilagaja povratnim informacijam, ki jih od njega pridobi [1]. that allows students to be co-responsible for their own knowledge. Formativno spremljanje vključuje pet elementov [1]: In the past school year, due to the coronavirus epidemic, we • oblikovanje namenov učenja in kriterijev continued to educate students at a distance learning. The paper uspešnosti, presents two cases of formative assessment during distance • pridobivanje dokazov o učenju, learning in the subject society in the fourth grade with the help • zagotavljanje povratnih informacij (tako od učenca of various computer tools and applications. The result of working k učitelju kot tudi od učitelja k učencu), according to the principles of formative assessment is good, the • oblikovanje vprašanj v podporo učenju, students have achieved the goals we set for ourselves. In addition • samovrednotenje ter vrstniško vrednotenje. to good learning outcomes, students have achieved many goals that strengthen competencies in the field of practical use of ICT. 2.1 Nameni učenja in kriteriji uspešnosti KEYWORDS Nameni učenja so na takšen način preoblikovani učni cilji iz učnega načrta, da so razumljivi učencu. V učnih načrtih so Distance learning, information technology, Google Forms, namreč cilji pogosto zapisani tako, da so razumljivi učiteljem, Socrative, Xooltime torej strokovnim delavcem. Oblikovani nameni učenja učencu pomagajo, da razume, kaj se bo učil, mu pomaga osredotočiti se na učno dejavnost in prevzeti odgovornost do lastnega učenja [1]. Kriteriji uspešnosti pa so konkretne trditve, ki so povezane z nameni učenja ter učnimi cilji, ki učencu pomagajo razumeti, v katerem primeru bodo uspešni. Z njihovo pomočjo vedo, ali so dosegli namene učenja. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed 2.2 Dokazi o učenju for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must Dokazi so zbirka podatkov, ki jih v procesu učenja dobiva učitelj be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia (ter tudi učenec). V grobem jih delimo v tri skupine: dokazi, ki © 2020 Copyright held by the owner/author(s). izhajajo iz pogovorov med poukom, dokazi, ki izhajajo iz 671 opazovanj ter izdelki kot dokazi [1]. Učenec lahko dokaze zbira Današnje tehnologije za izobraževanje na daljavo omogočajo tudi v portfoliu, ki omogoča vpogled v njegovo delo. Dokazi se dve vrsti komunikacije: sinhrono oz. sočasno ter asinhrono oz. zbirajo v vseh fazah učenja, saj je s tem viden tudi učenčev časovno neusklajeno komunikacijo učitelja in učenca [1]. V napredek. zadnjem času se uporablja pretežno kombinacija obojega, saj nam to omogočajo raznolika spletna okolja, kot so npr. spletne 2.3 Povratna informacija učilnice. Povratna informacija učencu pove, kako dobro je dosegel cilje ter kaj mora še izboljšati. Učenca spodbuja k razmisleku o tem, na kateri stopnji na poti do svojega cilja je ter kaj vse mora še 4 FORMATIVNO SPREMLJANJE V ČASU napraviti, da bo ta cilj dosegel. Povratna informacija mora biti IZOBRAŽEVANJA NA DALJAVO jasna in razumljiva, pravočasna in primerno pogosta, povezana z Izobraževanje na daljavo je v naši šoli po dogovoru potekalo nameni učenja ter kriteriji uspešnosti, konkretna, specifična in tako, da smo učitelji vsakodnevno pošiljali staršem dokumente, uporabna [1]. Dobro je, da vsebuje tudi predlog, kako izboljšati v katerih so bila navodila za šolsko delo tistega dne. Razrednik izdelek. Povratno informacijo lahko učencu podaja učitelj ali pa je tako zbral skupaj vsa navodila ter morebitne priloge, ki jih je drug učenec. Prav tako pa so pomembne tudi informacije, ki jih v eni elektronski pošti poslal staršem preko modula podaja učenec učitelju, saj mu s tem pomaga razumeti učenčeve komunikacija v aplikaciji eAsistent [1]. Učenci so sčasoma misli ter potrebe. postajali vse bolj suvereni pri uporabi IKT, zato so nekateri starši predlagali, da bi se elektronska pošta z navodili pošiljala tudi 2.4 Vprašanja v podporo učenju učencem. Tako so nekateri učitelji vsebine pošiljali še učencem Vprašanja učencu pomagajo pri učenju. Vendarle pa moramo preko eAsistenta za učence. Starši so pohvalili to, da so paziti, kakšna vprašanja postavljamo, saj morajo biti načrtovana elektronsko pošto z navodili prejemali tudi sami, saj so tako premišljeno ter spodbujati razmišljanje na vseh taksonomskih lahko nadzorovali delo svojega otroka. ravneh. Boljša so odprta vprašanja, saj omogočajo iskanje Tudi v času izobraževanja na daljavo smo nekateri učitelji pri različnih odgovorov. Pri postavljanju vprašanj pred več učenci se pouku uporabljali elemente formativnega spremljanja. je dobro izogniti dvigovanju rok, saj tak način k razmišljanju Predstavljen je primer uporabe formativnega spremljanja pri spodbudi tudi ostale učence. Prav tako je potrebno učencem pouku družbe v 4. razredu pri učnih sklopih domača pokrajina in zagotoviti dovolj časa za razmislek o odgovoru. Učence je dejavnosti. Nekaj učne snovi je bilo predelane že v času pred potrebno spodbujati tudi k medvrstniškemu postavljanju karanteno. Tako smo se že pri pouku v učilnici pogovarjali o vprašanj. namenih učenja. 2.5 Samovrednotenje in vrstniško vrednotenje 4.1 Kriteriji uspešnosti Samovrednotenje je zmožnost realne presoje lastne uspešnosti Učencem smo poslali kriterije uspešnosti (slika 1 in slika 2), ki [1]. Učenec s pomočjo pregleda dokazov o doseganju namenov so jim pomagali pri presojanju, kako dobro znajo vsebine učenja presoja, v kolikšni meri jih je dosegel ter o nadaljnjih obravnavanih sklopov, ki smo jih kasneje tudi ocenili. korakih in morebitnih spremembah načina učenja. Samovrednotenje poteka v vseh fazah učenja. Pri vrstniškem vrednotenju učenci drug drugemu podajajo analizo dosežkov. V tem primeru mora učitelj v razredu zagotoviti zaupanja vredno okolje, v katerem se učenci počutijo varno. 3 IZOBRAŽEVANJE NA DALJAVO Izobraževanje na daljavo (distance education) je oblika izobraževanja, ko sta učitelj in učenec med poučevanjem prostorsko ločena, komunikacijo med njima in komunikacijo med učenci samimi pa omogočajo različne vrste tehnologij [1]. M. Burns [1] loči 5 modelov izobraževanja na daljavo glede na prevladujočo tehnologijo: • korespondenčni model (natisnjena besedila), • avdiomodel (avdiotehnologija, radio), • televizualni model (videokonferenčni sistemi, televizija), • na računalniški tehnologiji temelječi multimedijski model (interaktivni videi, CD-ROM-i, interaktivna multimedija), • na spletu temelječi modeli (online tečaji, online Slika 62: Kriteriji uspešnosti za učni sklop domača konference, virtualni razredi oz. šole in univerze), pokrajina. • modeli, temelječi na mobilni tehnologiji (pametni telefoni, tablice, e-bralniki) 672 Slika 63: Kriteriji uspešnosti za učni sklop dejavnosti. 4.2 Dokazi o učenju Slika 65: Eden izmed dokazov o učenju je bil tudi plakat, ki Učenci so bili občasno naprošeni, da so pošiljali dokaze (slika 3 ga je učenec izdelal s pomočjo znanja, ki ga je pridobil na in slika 4) o svojem učenju preko elektronske pošte, kasneje pa primeru svojega domačega kraja. Plakat je nato učenec preko spletne učilnice Xooltime, ki jo je v času izrednih razmer fotografiral in ga naložil v ustrezno objavo v spletno razvilo podjetje eŠola d. o. o., pod okriljem aplikacije eAsistent učilnico Xooltime, ki je del eAsistenta [1]. [1]. 4.3 Povratna informacija Učenci so v procesu učenja in tudi ob koncu reševali različne naloge (slika 5) preko spletnih aplikacij, preko katerih je posameznik prejel povratno informacijo o svojem učenju (slika 6). Kot zelo uporabna se je izkazala aplikacija Google obrazci oz. Google Forms [1], ki omogoča izdelavo neke vrste kviza. Če v obrazec vnesemo tudi zahtevek za vpis elektronskega naslova, lahko obrazec po pregledu učitelja samodejno pošlje povratno informacijo o pravilnosti rešitev. Slika 64: Dokazi o učenju, ki so jih preko aplikacije eAsistent [1] podali učenci na nalogo, naj zapišejo tri izvirne ideje, na kakšen način bi v njihovi družini ali šoli trajnostno ravnali. Slika 66: Aplikacija Google obrazci oz. Google Forms [1] omogoča tudi vprašanja odprtega tipa, ki jih kasneje pregledamo in ovrednotimo. 673 4.4 Vprašanja v podporo učenju Vprašanja v podporo učenju smo učencem postavljali predvsem preko rednih srečanj preko aplikacije Zoom [1]. Tako so učenci ostali v stiku s sošolci, učiteljem ter učno snovjo. Poleg tega je tak način dela »pomagal« vsem tistim, ki so imeli več težav s tem, da so v času izobraževanja na daljavo poprijeli za šolsko delo. Videokonferenčna srečanja so tako omogočala tudi učencem, da so postavljali vprašanja drug drugemu. 4.5 Samovrednotenje in vrstniško vrednotenje Samovrednotenje ter vrstniško vrednotenje tega dela učne snovi smo izvedli v tednih v juniju, ko smo se zopet vrnili v šolske klopi. Učenci so na podlagi kriterijev uspešnosti presojali doseganje učnih ciljev. Pri svojem delu so bili več kot uspešni, kar se je pokazalo tudi pri ocenah iz te učne snovi. Učenci so Slika 67: Učencu lahko poleg točk pri posameznem morali povezati teoretično znanje z lastnostmi svojega domačega odgovoru napišemo tudi povratno informacijo. kraja oz. pokrajine. Google obrazci oz. Google Forms [1] daje učitelju podrobno sliko o znanju posameznika ter celotnega razreda s pomočjo 5 POVRATNA INFORMACIJA UČENCEV IN statističnih podatkov (slika 7). STARŠEV Učenci so bili že vajeni dela po načelih formativnega spremljanja. Poročali so, da jim je všeč, da pri svojem delu uporabljajo različne spletne aplikacije, vendar pa jim uporaba teh (zaenkrat) vzame več časa, kot če bi delali na klasičen način. Starši so bili veseli, da so njihovi četrtošolci veliko nalog lahko opravili sami. Včasih so imeli le na začetku nekaj dela z njimi, da so jim razložili osnove uporabe določene aplikacije. Všeč jim je bilo tudi, da smo se pogosto slišali in videli preko video klica. Slika 68: Google obrazci omogočajo tudi odlično statistiko za učitelja. 6 ZAKLJUČEK Dokaze o učenju smo zbirali tudi preko nekaterih drugih aplikacij (slika 8), npr. preko aplikacije Socrative [1]. Kljub temu, Glede na to, da bo v prihodnje izobraževanje na daljavo kot kaže da ni prevedena v slovenščino, so jo četrtošolci hitro znali ostalo vsaj delno prisotno v našem šolskem vsakdanu, je dobro uporabljati brez težav. Prednost te aplikacije je, da ne zahteva poznati možnosti, ki nam jih taka oblika izobraževanja ponuja. registracije učenca, pač pa učenec na začetku le vpiše kodo Formativno spremljanje je zagotovo ena od prioritet, ki bi jo rade naloge ter svoje ime. šole vpeljale v svoj vsakdan. Na tak način bodo učenci postali in ostali aktivni v izgradnji svojega znanja, prevzeli bodo odgovornost za svoje učenje ter znanje. Elemente formativnega spremljanja je v izobraževanje na daljavo smiselno vpeljevati, vendar premišljeno ter v ustrezni količini. Pogosto se namreč zgodi, da se učenci v »poplavi« vsega izgubijo ter tako hitro izgubijo motivacijo. Na to bomo morali biti učitelji še posebej pozorni. VIRI [1] Burns, M. 2011. Distance Education for Teacher Training: Modes, Models, and Methods. Education Development Center. DOI: http://idd.edc.org/sites/idd.edc.org/files/Distance%20Educ ation%20for%20Teacher%20Training%20by%20Mary%2 0Burns%20EDC.pdf (pridobljeno 10. 8. 2020) [2] eAsistent https://www.easistent.com/ [3] Google obrazci oz. Google Forms https://www.google.com/intl/sl/forms/about/ Slika 69: Povratne informacije od učenca k učitelju smo pridobivali tudi preko aplikacije Socrative [1]. 674 [4] Holcar Brunauer, A. idr. 2019. Formativno spremljanje v poročilo. Zavod Republike Slovenije za šolstvo. DOI: podporo učenju. Priročnik za učitelje in strokovne delavce https://www.zrss.si/digitalnaknjiznica/IzobrazevanjeNaDal (7 zvezkov). Zavod Republike Slovenije za šolstvo. javo/2/#zoom=z (pridobljeno 9. 8. 2020) [5] Rupnik Vec, T. idr. 2020. Analiza izobraževanja na [6] Socrative https://www.socrative.com/ daljavo v času epidemije Covid-19 v Sloveniji. Delno [7] Zoom https://zoom.us/ 675 Varna mobilnost tudi na daljavo Safe mobility in time of distance learning Nuša Skumavc Osnovna šola Predoslje Kranj Predoslje 17a 4000 Kranj, Slovenija nusa.skumavc@guest.arnes.si POVZETEK consisting of individual recordings, which we played to other students at the end of the school year. The fourth-graders who V preteklem šolskem letu smo zaradi pojava novega took part in the production were proud of their products, and they koronavirusa in z njim povezane bolezni COVID-19 praktično also learned about the use of information technology in a useful čez noč bili primorani spremeniti svoj način poučevanja in se way and interactive security. navaditi na šolanje na daljavo. Drugačen način pouka nam je vsem udeleženim, tako učencem, učiteljem kot tudi staršem, KEYWORDS obrnil življenje na glavo. Ker pa je šolski kurikulum sestavljen iz obveznega in razširjenega programa, so mnogi učenci v Distance learning, extended program, information technology, pomanjkanju časa ter težavam pri prilagajanju na drugačen način OpenShot Video Editor dela, razumljivo prednost dali obveznemu delu kurikuluma. Učitelji smo tako iskali različne načine za motiviranje učencev. 1 UVOD V prispevku je predstavljen primer dobre prakse, kako smo uresničevali cilje razširjenega programa v času šolanja na daljavo. Letošnje šolsko leto je bilo posebno v vseh pomenih te besede. Rezultat skupnega dela je bil video, sestavljen iz posameznih Meseca marca so se učenci namreč namesto v šolskih klopeh posnetkov, ki smo ga ob koncu šolskega leta predvajali ostalim začeli izobraževati na daljavo. Izkušnja je bila nova tako za učencem. Četrtošolci, ki so sodelovali pri izdelavi, so bili na učence kot tudi učitelje. Predvsem od učiteljev je zahtevala svoje izdelke ponosni, poleg tega pa so se spoznavali z uporabo popolno reorganizacijo pouka za iskanje najracionalnejše poti za informacijske tehnologije na koristen način ter interaktivno doseganje zastavljenih učnih ciljev. Na daljavo pa se ni izvajal le varnostjo. obvezni program, pač pa tudi razširjeni program osnovne šole, kamor spada tudi poskus »Uvajanje tujega jezika v obveznem KLJUČNE BESEDE programu in preizkušanje koncepta razširjenega programa v Šolanje na daljavo, razširjeni program, informacijska osnovni šoli« , znotraj tega pa vsebinski sklop Gibanje in zdravje tehnologija, OpenShot Video Editor za dobro psihično in fizično počutje oz. na kratko GZDP, kar zajema tudi teme varne mobilnosti. V prvi polovici šolskega leta ABSTRACT smo skupaj z učenci izdelali kar nekaj izdelkov, ki smo jih In the past school year, due to the emergence of the new predstavili ožji in širši okolici, npr. maketo okolice šole s coronavirus and the associated disease COVID-19, we were fotografijami nevarnih prometnih točk, letake, s katerimi smo ob forced to change our teaching methods almost overnight and get pomoči policista voznike v okolici šole opozarjali na problem used to distance learning. A different way of teaching turned the alkoholiziranosti za volanom … Ko pa smo zaradi pojava novega lives upside down for all participants, students, teachers and koronavirusa ostali doma, smo morali plane nekoliko spremeniti. parents. However, because the school curriculum consists of a Ni preostalo drugega, kot da smo naše delo prilagodili razmeram compulsory and extended curriculum, many students, in the lack in s skupnimi močmi ustvarili video, s pomočjo katerega smo of time and difficulty in adapting to a different way of working, učencem naše šole pokazali, kaj vse smo v letošnjem šolskem gave understandable priority to the compulsory part of the letu počeli v okviru varne mobilnosti. curriculum. Teachers were thus looking for different ways to motivate students. The article presents an example of good 2 RAZŠIRJENI PROGRAM – GIBANJE IN practice in how we achieved the goals of the extended program ZDRAVJE ZA DOBRO PSIHIČNO IN during distance learning. The result of the joint work was a video FIZIČNO POČUTJE Program osnovne šole sestavljata obvezni in razširjeni program Error! Reference source not found. Obvezni program obsega Permission to make digital or hard copies of part or all of this work for personal or obvezne in izbirne predmete, ure oddelčne skupnosti, dneve classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full dejavnosti in šolo v naravi. Razširjeni program obsega citation on the first page. Copyrights for third-party components of this work must neobvezne izbirne predmete, individualno in skupinsko pomoč be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia učencem, dopolnilni in dodatni pouk, interesne dejavnosti, © 2020 Copyright held by the owner/author(s). podaljšano bivanje in jutranje varstvo. Šole so dolžne ponuditi 676 vse organizacijske oblike razširjenega programa, učenci pa se »ustavljal« na točno določenih mestih (postajališčih Pešbusa) ter vanje prostovoljno vključujejo Error! Reference source not sprejemal svoje potnike, učence. Učenci so prejeli tudi found. »vozovnico« ter vanjo zbirali žige. Aktivnost smo izpeljali že Razširjeni program osnovne šole se bo iz oblike, kot jo lansko šolsko leto (v jeseni in spomladi), letos pa smo nabor prog poznamo danes, sčasoma preoblikoval v tri glavna področja razširili, tako da smo postavili kar tri proge, katerih zadnja Error! Reference source not found. : postaja je bila naša šola. V dejavnosti je skupno sodelovalo 54 • Gibanje in zdravje za dobro psihično in fizično učencev in 9 odraslih spremljevalcev (večinoma učiteljev). počutje (področje A), V mesecu oktobru smo sodelovali na likovnem natečaju in pri • Kultura in tradicija (področje B), izvedbi akcije »Otroci za varnost v prometu«, ki ga je organiziral • Vsebine iz življenja in dela osnovne šole NIJZ OE Kranj. Učenci so narisali risbe, ki se navezujejo na temo (področje C). »promet in alkohol«, ter jih nato v spremstvu policista delili Telesna aktivnost, zdrava prehrana, varno okolje in voznikom, ki so v času ulične akcije pripeljali mimo naše šole. preventivni programi so pomembni dejavniki, ki mladim Oktobra in novembra pa smo se posvetili izdelavi makete zagotavljajo optimalen razvoj v času odraščanja. Veliko mladih naše šole z okolico (slika 1), na kateri smo prikazali prometni se namesto za žogo na igriščih podi za žogo na raznih igralnih režim in nevarne točke. Sprehodili smo se skozi vas ter si konzolah, poleg tega se pogosto neredno prehranjujejo s pretežno ogledali okolico naše šole, fotografirali nevarnejše prometne predelano hrano, premalo pijejo ter zaradi pomanjkanja znanja o točke, merilec hitrosti, prehode za pešce … Te fotografije smo tem po nepotrebnem na dolgi rok uničujejo svoje zdravje. V potem nalepili na maketo. okviru prenovljenega razširjenega programa naj bi učenci spoznali različne vsebine in načine udejanjanja zdravega življenjskega sloga, jih preizkusili, občutili in doživeli Error! Reference source not found. 3 VARNA MOBILNOST Znotraj področja A (Gibanje in zdravje za dobro psihično in fizično počutje) so naslednji sklopi Error! Reference source not found. : gibanje, hrana in prehranjevanje ter zdravje in varnost. V sklop »zdravje in varnost« spada tudi varna mobilnost. V delovnem gradivu Razširjeni program osnovne šole Error! Reference source not found. je varna mobilnost definirana kot »sodoben način življenja in dela, katerega sestavni del so prometna kultura, zdrav način življenja, ustrezen odnos do okolja ter ekonomično ravnanje udeležencev v prometu«. Ker se učenci Slika 70: Maketa, ki so jo izdelali učenci v okviru varne mobilnosti. v prometu znajdejo v različnih vlogah (pešci, kolesarji, sopotniki v avtomobilu ali avtobusu …), so vsebine varne mobilnosti 4.2 Varna mobilnost v času šolanja na daljavo namenjene usvajanju znanja in razvijanju različnih kompetenc, ki jih morajo v naštetih vlogah obvladati, da se lahko varno Z aktivnostmi smo nadaljevali v mesecu marcu. Pod šolo smo vključujejo v družbo. spremljali promet in šteli posamezna prevozna sredstva, ki so v določenem času pripeljala mimo. Zaradi pojava novega koronavirusa in s tem povezanega šolanja na daljavo, smo z 4 PRIMER DOBRE PRAKSE aktivnostmi za nekaj časa prekinili. Nato smo na daljavo izvedli še nekaj aktivnosti: ogled raznih videov, ki so povezana z 4.1 Varna mobilnost na naši šoli upadom prometa v času karantene po evropskih in svetovnih Vsebinam varne mobilnosti je bilo letno namenjenih 38 ur, torej mestih, seznanjanje s tem, kako hodijo v šolo otroci drugod po ena šolska ura tedensko. Ker gre za razširjeni program, je bila ura svetu … V zadnjem delu šolskega leta pa smo se preko aplikacije varne mobilnosti zastavljena tako, da se ni izvajala Zoom dogovorili, da bo vsak učenec posnel video, ki je povezan vsakotedensko po eno uro, pač pa večinoma v t.i. blok urah, torej z varnostjo v prometu ali pa s trajnostno mobilnostjo. po dve šolski uri skupaj v nekajtedenskih sklopih, nato pa se 4.3 Navodila za izdelavo nekaj časa ni izvajala. Tako smo izkoristili jesenske in spomladanske mesece, ko smo veliko časa preživeli zunaj in Učencem je bilo potrebno podati nekaj navodil za izdelavo videa. opravljali aktivnosti kar tam. V zimskem času tako vsebin varne To smo storili preko aplikacije Zoom Error! Reference source mobilnosti nismo izvajali. V okviru teh ur smo jeseni izvedli kar not found. , ki omogoča videokonferenčne klice. Ker so učenci nekaj aktivnosti. V tretjem tednu septembra, torej v Evropskem že dobro vedeli, na kaj vse morajo biti udeleženci pozorni, nam tednu mobilnosti, smo v sodelovanju z Mestno občino Kranj in tem ni bilo težko najti. Dogovorili smo se, da bomo posneli videe društvom Rekreatur za učence od 2. do 5. razreda izpeljali z naslednjo poučno vsebino: trajnostni način prevoza – vlak ali dejavnost Pešbus. Dejavnost poteka v okviru programa Aktivno avtobus, vožnja s kolesom po ustreznih prometnih površinah, v šolo. Učitelji smo en teden vsako jutro učence razredne stopnje, skupni prevozi, pripenjanje z varnostnim pasom, prečkanje ceste ki so to želeli, po predvideni poti peš spremljali v šolo. Pešbus je čez prehod za pešce ter vožnja po omejitvah. Ker so v tistem času poudarjali, naj ostanemo doma, smo se dogovorili, da bodo videe 677 snemali s pomočjo pripomočkov in ne v resničnih situacijah. Situacijo smo izkoristili tudi za pogovor o varnosti na internetu, posnetkih, na katerih so oni sami ter dejstvu, da posnetki, ki jih objavijo v svetovnem spletu, tam tudi za vedno ostanejo. Slika 73: Ozadje ob začetku skupnega videa smo naredili s pomočjo predloge v programu Microsoft Powerpoint Error! Reference source not found. . Slika 71: Učenci so svoje videe posneli s pomočjo igrač, ki 4.6 Montiranje videa v celoto jih imajo doma. Za montiranje videov učencev v celoto smo uporabili Učenci so se o tem, kateri video bodo posneli, odločali glede računalniški program OpenShot Video Editor Error! Reference na igrače, ki so jih imeli doma, npr. skiro, avtomobil, avtobus … source not found. Gre za brezplačen program, ki uporabniku (slika 2). Prometno podlago so zgradili s pomočjo lego kock, omogoča enostavno montažo videov, slik, glasbenega ozadja ter nekateri so uporabili igralno podlogo, na kateri je cesta ali pa so različnih prehodov (slika 5). si pomagali s podlago (slika 3), ki so jo izdelali v eni od nalog, ki so jo imeli v okviru pouka (izdelava družabne igre na temo trajnostne mobilnosti). Snemali so večinoma z mobiteli. Učenci so prejeli še naslednje usmeritve: video naj bo posnet ležeče, izogibajo naj se hitrim premikom, kadar govorijo naj bodo blizu telefona, da se jih bo dobro slišalo ipd. Slika 74: Za montiranje videa smo uporabili računalniški program OpenShot Video Editor Error! Reference source not found. . V končni video so bili vključeni tudi glasba ter prehodi med slikami in posameznimi krajšimi videi. Slika 72: Učenci so uporabili pripomočke, ki so jih imeli doma (podlaga, ki so jo izdelali za družabno igro na temo trajnostne mobilnosti ter igrače, kot npr. avtomobilčki ter 5 POVRATNA INFORMACIJA UČENCEV osebe). Učenci so po končani nalogi poročali, da jim samo snemanje ni 4.4 Snemanje in pošiljanje videov, ki so jih povzročalo težav, prav tako niso imeli težav s pošiljanjem ustvarili učenci videov. Po njihovem mnenju jim je največ časa vzela priprava scenarija, kako bodo posneli posamezno situacijo. Povedali so, Učenci so svoje videe večinoma posneli v MP4 formatu. Zaradi da se sedaj bolj zavedajo, kako pomembno je, kaj snemajo in kje velike velikosti so svoje videe večinoma poslali preko orodja objavljajo svoje video posnetke ter fotografije. Pri snemanju so WeTransfer Error! Reference source not found. , ki je zelo bili kreativni, znajti so se morali s pripomočki, ki jih imajo doma. enostaven za uporabo, omogoča pa pošiljanje večjih datotek Čisto vsi vključeni učenci so bili s svojim izdelkom zelo (velikost do 2 GB). zadovoljni, želeli bi si več takega načina dela. Predvsem pa so bili ponosni nase, ko so si končni izdelek ogledali še ostali 4.5 Vmesni kadri učenci. Posamezne videe učencev smo želeli zmontirati v celoto. Za slikovno podlago, v katero smo vključili slike na začetku videa, smo vzeli predlogo iz PowerPointa (slika 4), ki je del paketa 6 ZAKLJUČEK Microsoft Office Error! Reference source not found. Zaradi trenutne situacije z virusom in boleznijo COVID-19, v kateri se je znašel cel svet, smo se morali vsi prilagoditi. Veliko učiteljev in učencev je bilo na situacijo slabo pripravljenih. Tisti, ki jim je IKT blizu, so imeli s prilagajanjem na situacijo bistveno manj težav. Vendar pa je šlo v tem primeru večinoma za uporabo 678 tudi takih aplikacij, ki jih sicer v »običajnem« šolanju ne e/content/1/Kurikularni%20dokument%2011_6.pdf uporabljamo (npr. snemanje videov). V prihodnje se bo zato (pridobljeno 4. 8. 2020) potrebno izobraziti tudi na teh področjih. Tisti, ki smo se [2] OpenShot Video Editor https:/ www.openshot.org/ samoiniciativno lotili raziskovanja možnosti, ki nam jih IKT [3] Powerpoint (Microsoft Office) ponuja, smo se v tem času veliko naučili. Glede na to, da kaže, https://www.microsoft.com/sl-si/ da se situacija z novim koronavirusom še nekaj časa ne bo umirila, se bo potrebno na tak način dela privaditi. Tisti, ki so se [4] Predmetnik osnovne šole. DOI: vse življenje pripravljeni učiti, s tem ne bodo imeli težav. https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/O snovna-sola/Ucni-nacrti/Predmetnik-OS/Predmetnik-za- osnovno-solo.pdf (pridobljeno 9. 8. 2020) VIRI [5] WeTranfer https://wetransfer.com/ [1] Logaj, V. idr. 2018. Razširjeni program osnovne šole. [6] Zakon o osnovni šoli. DOI: Delovno gradivo. Zavod Republike Slovenije za šolstvo. http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO44 DOI: 8# (pridobljeno 9. 8. 2020) https:/ skupnost.sio.si/pluginfile.php/693888/mod_resourc [7] Zoom https://zoom.us/ 679 Razvoj obiskov na Institutu »Jožef Stefan« skozi čas - od odprtih vrat do virtualnega obiska Development of Jožef Stefan Institute visits through time – from open days to virtual visits Špela Stres, Levin Pal CTT JSI Jamova cesta 39 1000 Ljubljana, Slovenija spela.stres@ijs.si, levin.pal@ijs.si POVZETEK Na Institutu »Jožef Stefan« od marca 2008 naprej sistematično 1 UVOD organiziramo različne izobraževalne dogodke: dan, teden, večer Na Institutu »Jožef Stefan« že vrsto desetletij, od leta 2008 pa v odprtih vrat ter redne obiske Instituta. Tako se Institut »Jožef sistematični in poenoteni obliki k organiziramo tradicionalne Stefan« aktivno vključuje v proces vzpostavljanja učeče se dneve Jožefa Stefana, ko praznujemo obletnico rojstva velikega družbe in sodeluje pri razmahu zanimanja otrok, učencev, slovenskega znanstvenika, po katerem naš Institut nosi ime. dijakov, študentov ter odraslih za naravoslovje. S sprejetjem širše Jožef Stefan se je rodil 24. marca 1835. Dnevi Jožefa Stefana se rabe virtualnih komunikacijskih orodij v šolah in v podjetjih se v vsako leto zaključijo v soboto z Dnem odprtih vrat Instituta, ki zadnjem času odpirajo tudi nove možnosti za tesnejše jih organizira Center za prenos tehnologij in inovacij v sodelovanje s pomočjo virtualnih orodij. Članek obravnava sodelovanju z raziskovalnimi odseki na Institutu. Takrat si vzpostavitev, rast, razvoj in prenovo omenjenih izobraževalnih zainteresirani posamezniki lahko ogledajo zanimivosti, ki jih dogodkov, skozi dogodke in številke. Institut skriva za svojimi vrati. Marca leta 2020 je bil omenjeni dogodek prestavljen zaradi epidemije Covid19 in se ni izvedel. KLJUČNE BESEDE Dodatno je konzorcij partnerjev Ustanova Hiša Dan odprtih vrat, izobraževalni dogodki, znanost, izobraževanje, eksperimentov, Institut »Jožef Stefan«, Kemijski inštitut in STEM, šolski sistem, sodelovanje Tehniški muzej Slovenije sooblikoval projekt » Noč ima svojo ABSTRACT moč«. V okviru projekta je Center za prenos tehnologij in inovacij na Institutu »Jožef Stefan« organiziral in sodeloval pri At the Jožef Stefan Institute, we have been systematically aktivnostih v okviru vseevropske akcije Evropska noč organizing various educational events since March 2008: a day, raziskovalcev v petek, 28. septembra 2018 in 27.septembra 2019, a week, an open house and regular visits to the Institute. Thus, ko je bil izveden tudi Večer odprtih vrat. Na noč raziskovalcev the Jožef Stefan Institute is actively involved in the process of se širom Evrope široko odprejo vrata organizacij, ki se ukvarjajo establishing a learning society and the spread of interest of z znanostjo in raziskovanjem, da bi predstavile poklic in življenje children, pupils, students and adults in science. With the adoption znanstvenikov širši javnosti. of the wider use of virtual communication tools in schools and Z Dnevom odprtih vrat ter izvedbo Večera odprtih vrat (v companies, the Institute is opening up new possibilities for closer Noči raziskovalcev) se Institut »Jožef Stefan« že desetletja cooperation. The article deals with the establishment, growth, aktivno vključuje v proces vzpostavljanja učeče se družbe in development and renovation of the mentioned educational events, razmahu zanimanja otrok, učencev, dijakov, študentov ter through events and numbers. odraslih za naravoslovje. V nadaljevanju prikazujemo začetek in razvoj skozi številke, ter prehod v novo, informatizirano dobo KEYWORDS izobraževalnih dogodkov. Open day, educational events, science, education, STEM, school system, cooperation 2 DAN ODPRTIH VRAT 2.1 Nov začetek 2008 Dan odprtih vrat na Institutu poteka “od nekdaj” – tako dolgo, da ni mogoče z gotovostjo ugotoviti, kdaj se je ta aktivnost prvič uvedla. Glede na [1] pa je razvidno, da je bil leta 2008 dan Permission to make digital or hard copies of part or all of this work for personal or odprtih vrat oz. DOV, kot ga imenujemo s kratico, po dolgih letih classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full spet organiziran na soboto in da je bil odziv daleč nad citation on the first page. Copyrights for third-party components of this work must pričakovanji. Tega leta si je prostore instituta ogledalo več kot be honored. For all other uses, contact the owner/author(s). 700 ljudi, reaktor pa še dodatno več kot 400 ljudi. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 680 Leta 2008 smo obiskovalce prvič povabili, da se ob vsaki skupin je bilo manj kot preteklo leto, ker ni bil šolski delovni dan. polni uri, med 10. in 14. uro zberejo pri vratarju Instituta »Jožef Kljub temu je prišlo nekaj avtobusov in kombijev. Stefan« na Jamovi cesti 39 na Viču v Ljubljani in si izberejo Podjetja so bila obveščena preko okrožnic TIA in JAPTI ter enouren ogled laboratorijev Instituta. Na voljo je bilo devet letakov mreže Enterprise Europe Network. Takoj po objavi so se različnih predstavitvenih ogledov znotraj treh programov – 1. pričeli vrstiti klici in elektronska sporočila posameznikov iz vse Program: Snov, robotika; 2. Program: Biotehnologija-kemija- Slovenije. fizika ter 3.program: Znanje, sistemi, materiali in okolje. Dodatno k obveščanju je bilo razdeljenih še 1600 letakov Obenem je bil ob 11h in 12h z Jamove organiziran prevoz na okoliškim prebivalcem na območju Jamove in Reaktorja, enoto Instituta v Podgorici - zaradi velikega zanimanja obvestili smo tudi medije. Tako smo zajeli precej heterogeno obiskovalcev sta od 11h naprej avtobus in minibus vozila združbo obiskovalcev IJS, od starejših prebivalcev iz soseščine, nepretrgoma. Na lokaciji v Podgorici so si obiskovalci lahko ki so pogosto poudarjali, da jih je že celo življenje zanimalo, kdaj ogledali laboratorije v predstavitvah štirih programov: 1. bo “pri sosedu kaj eksplodiralo”, do staršev z otroki, Program: Okolje: Hg laboratorij – geokemija – pospeševalnik; 2. osnovnošolcev, srednješolcev, študentov iz bližnje in daljne Program Jedrska tehnologija – reaktor TRIGA; 3. Program: okolice Instituta. Obiska se je udeležilo vsaj 11 podjetij iz vse Okolje: radiološki del – vroča celica in 4. Program; Jedrski Slovenije, ki jih je zanimalo sodelovanje z IJS, veliko jih je bilo odpadki (ARAO). Zavedali smo se omejitev pri številu predvsem iz Primorske regije. obiskovalcev. Zaradi velikosti laboratorijev je bil predviden Avtobus, ki je na lokacijo »Reaktor« vozil z Jamove ceste ogled Instituta v skupinah po največ 15 obiskovalcev. Naenkrat vsako polno uro, je bil vseskozi poln, ker pa smo del bi tako brez težav lahko v devetih različnih enournih programih obiskovalcev zaradi pomankanja prostora na Reaktor poslali s sprejeli 135 obiskovalcev, kar se je zdela glede na obisk s šolskimi avtobusi, so sodelavci z Reaktorja na koncu prijazno prejšnjih let smiselna ocena. Toda obisk je leta 2008 presegel ponudili prevoz tudi s svojim kombijem, kar je še en primer pričakovanja - ob 10h se je na Institutu naenkrat znašlo več kot povezanosti ekipe na Institutu. Na Reaktor smo prepeljali 3 250 obiskovalcev in obisk skoraj do konca dneva ni upadel. velike avtobuse obiskovalcev, ki so bili nad možnostjo ogleda Ključnega pomena za izvedbo obiska v tolikšnem obsegu je Reaktorskega centra navdušeni. igral in še vedno igra mrežno razvejan sistem koordinatorjev po Institut si je na Jamovi ogledalo več kot 600, na Reaktorju pa raziskovalnih odsekih Instituta. Koordinatorji so tisti, ki s več kot 250 obiskovalcev (Slika 2). Zahvaljujoč tablam, ki so jih soglasjem vodij svojih enot Instituta obiskovalce toplo sprejmejo prijazno priredili v delavnicah Instituta, smo z odhodnih mest na v laboratorije, jim jih razkažejo in jih popeljejo v svet znanosti parkirišču vsako polno uro pregledno lahko usmerili vsako od na način, da jim jo čimbolj približajo. Brez njih obiski Instituta devetih skupin ogledov, ki so bili po programu na voljo. ne samo, da bi bili popolnoma drugačni, temveč sploh ne bi bili Da bi bili obiskovalci o možnostih ogleda bolje informirani, mogoči. Že desetletje je skupnost koordinatorjev obiskov na smo pripravili poseben letak s programi obiska. Kot Institutu osnova izvedbe obiskov, vseskozi in še vedno deluje na organizacijsko pomanjkljivost smo identificirali potrebo po prostovoljni osnovi, saj gre za neplačano delo navdušencev - bila velikem plakatu s seznamom odsekov po programih ter pa je v letih 2008-2010 tako povezana, da so se v šali celo oklicali prepoznavno znamenje (nalepka, priponka, . .), s čimer bi za ločen odsek Instituta (Slika 1). obiskovalci koordinatorje lažje ločili od množice. Slika 1. Koordinatorji na enem od letnih piknikov, srečanj, na katerih so se med seboj družili in se po napornih prostovoljno izvedenih obiskih Instituta tudi skupaj Slika 2: Izvedba obiskov na Institutu je vedno vsebovala poveselili. mešanico strokovnega pogovora, znanstvenih informacij, ogleda laboratorijev in neobveznega klepeta. 2.2 Razvoj 2009 Naslednji Dan odprtih vrat je 28. 3. 2009 že minil brez 3 IZBOLJŠAVE presenečenj in glede na odzive obiskovalcev tudi več kot uspešno. O dnevu odprtih vrat smo šole in gimnazije večkrat V naslednjih letih smo uvedli nekaj izboljšav [2, 3, 4, 5], ki pa obvestili preko Ministrstva za šolstvo, učitelje in njihove aktive niso bistveno spremenile začetne ideje izvedbe. Koordinatorji pa še posebej preko Zavoda za šolstvo. Naročil večjih šolskih obiska so dobili svoje značilne puloverje v svetlo modri barvi, da so bili v množici res prepoznavni. Zagotovili smo prazno 681 parkirišče in na njem znake, izpred katerih so se začenjali ogledi posamičnih skupin in programov. Ponudbo smo kasneje (2013) dopolnili tudi s postavitvijo informacijskega pulta, ki je v prvi vrsti namenjen prestrezanju obiskovalcev ob vstopu ter primernemu preusmerjanju na oglede programov glede na njihov interes. Obenem na informacijskem pultu delimo letake in gradiva o Institutu, projektih instituta ipd., da informacije o aktivnostih IJS lažje dosežejo zainteresirano javnost. Zaradi množičnih obiskov v naslednjih letih smo uvedli tudi t.i. “padalske” obiske, s čimer smo omogočili obisk tudi mnogim, ki Slika 3. Število obiskov ter odstopanje od povprečja po so se na oglede Instituta odpravili med polnimi urami, ko so bile enotah Instituta v letu 2008 (30.9.2007-30.10.2008) skupine načeloma že na obhodih – posebna skupina sodelavcev je poskrbela za to, da se je lahko vsaka večja skupina Število obiskov je nato raslo v dveh zaporednih skokih (Slika obiskovalcev pridružila ogledom tudi v vmesnem času. Dodatno 4), vsakemu izmed njih je sledila uvedba neke vrste omejitve smo zagotovili, da so potekali ogledi vseh 27 laboratorijev oz. števila obiskovalcev, z namenom, da se izvede kot je le mogoče enot hkrati, s čimer smo precej povečali kapaciteto ogledov ob veliko obiskov, vendar v obsegu in obliki, da le ti ne ovirajo upoštevanju omejitev 15 oseb na skupino. tekočega raziskovalno razvojnega dela na Institutu. Vsako leto novembra smo izvedli pregled odgovornih V letu 2010 smo zaradi velikega interesa šol za obisk Instituta koordinatorjev po 27 sodelujočih enotah Instituta, zbrali oz. uvedli teden, namesto dneva odprtih vrat, kar je pomenilo, da nas posodobili smo njihove kontaktne podatke ter izvedli lahko šole obiščejo v tednu pred Dnevom odprtih vrat vsak dan. informativni sestanek z njimi, kjer smo skupaj pregledali Po porastu števila šol, ki so nas obiskale v letu 2011 (65 šol), smo dosežene rezultate preteklega leta ter morebitne težave, ki so ob teden odprtih vrat okrnili in omejili število šol, ki so nas lahko izvajanju nastajale in način izvedbe obiskov v prihajajočem letu. obiskale v tem obdobju. Prav tako je bil izveden dodaten sestanek približno mesec dni pred Dnevom odprtih vrat, na katerem smo še posebej pozorno pregledali način organizacije, mesta prevzema, način ukrepanja v posameznih varnostnih in organizacijskih situacijah, do katerih prihaja v primeru dogodkov z več 1000 udeleženci. Skozi leta se je največji interes kazal za Šolo eksperimentalne kemije in Robotiko, ki smo ju oblikovali v ločena programa, da se ju je lahko udeležilo čim več obiskovalcev, predvsem nadobudnih mladih znanstvenikov iz prve triade ali vrtca. Čeprav so se in se še vedno koordinatorji obiskov na odsekih trudijo predstaviti problematiko svojih laboratorijev po najboljših močeh, pa je vsa leta ostala nerešena in nenaslovljena tematika kvaliteta predstavitev oz. njihovo poenotenje. Slika 4. Število obiskovalcev na Institutu v posameznem letu, ločeno za obiskovalce med letom (modra črta) in obiskovalce na Dnevu odprtih vrat (rdeča črta) [6, 7, 8, 9, 4 DAN ODPRTIH VRAT IN OBISKI SKOZI 10, 11, 12, 13, 14, 15, 16] ŠTEVILKE Leta 2015 in 2016 je število šol (Slika 5), ki so obiskale 4.1 Obdobje 2008-2019 Institut ponovno močno naraslo (79 in 83 šol), zato smo v letu 2017 omejili število obiskov na teden, v letu 2019 pa smo Že kmalu se je pokazalo, da so nekatere tematike za širšo skupino preizkušali možnost, da število omejimo na en obisk šole na obiskovalcev vsaj na prvi pogled bolj zanimive kot druge. teden, vendar nam to zaradi velikega povpraševanja ni uspelo. Seveda ob podrobnem pregledu to ni nujno ali sploh ni res, Glede števila obiskovalcev nimamo podatkov za vsa leta, vendar je interes za oglede po posameznih enotah nihal že od število obiskovalcev za leta 2009, 2017, 2018 in 2019 so ocene. samega začetka. Na Sliki 3 vidimo prikaz števila obiskov po Vsi ostali podatki so pridobljeni iz letnih poročil Instituta [6, 7, posameznih enotah ter odstopanje od povprečnega števila 12 8, 9, 10, 11, 12, 13, 14, 15, 16]. obiskov v obdobju od 30.9.2007 do 30.10.2008 za 331 izvedenih Tudi iz števila obiskovalcev je mogoče zaznati enake trende obiskov po enotah v tem obdobju. kot pri številu šol, ki so nas obiskale. Vrhovi v letih 2011 ter 2015 in 2016 so bili že obrazloženi, opozoriti pa je potrebno še, da se število obiskovalcev med letom ni zmanjšalo niti z omejitvijo števila šol, zaradi česar smo postali pri oblikovanju skupin za posamezne obiske laboratorijev bolj dosledni pri upoštevanju omejitve velikosti skupine do 15 oseb. 682 Slika 5. Število šol, ki so obiskale Institut v posameznem letu [6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16] 4.2 Večer odprtih vrat Slika 6: Noč ima svojo moč. Na Večeru odprtih vrat se nam Na noč raziskovalcev se širom Evrope široko odprejo vrata je v soju bakel pridružilo več kot 500 obiskovalcev. organizacij, ki se ukvarjajo z znanostjo in raziskovanjem, da bi predstavile poklic in življenje znanstvenika širši javnosti. V V večernih urah smo v sodelovanju z raziskovalnimi odseki okviru projekta je Center za prenos tehnologij in inovacij na na Institutu organizirali Večer odprtih vrat na Institutu »Jožef Institutu »Jožef Stefan« organiziral in sodeloval pri aktivnostih v Stefan« (Slika 6). Na pobudo promocije znanosti in raziskovanja okviru vseevropske akcije Evropska noč raziskovalcev v petek, smo odprli vrata naše največje raziskovalne ustanove in 28. septembra 2018. zainteresirani javnosti predstavili različne vidike raziskovalnega Sodelavci Instituta »Jožef Stefan«, Centra za prenos dela. Tako so si v petek zvečer obiskovalci v soju bakel in sveč tehnologij in inovacij smo se že dopoldan podali na pot po lahko ogledali dosežke in laboratorije številnih raziskovalnih Sloveniji z namenom osveščanja o raziskovanju in inovacijah ter odsekov, dokumentarne filme o raziskovalnem delu, atraktivne družbenih in gospodarskih koristih in kariernih možnostih, ki jih in poučne predstave eksperimentov ter se pogovarjali z slednja lahko nudita prav vsakomur od nas. Organizirali smo domačimi in tujimi raziskovalci. raziskovalne dneve v osnovnih in srednjih šolah ter predavanja V večeru odprtih vrat se nam je v tej posebni izdaji obiskov in delavnice v domovih za upokojence. S tem smo predstavili na Institutu pridružilo kar 500 obiskovalcev [17]. možnost uporabe znanosti in raziskovanja v vseh življenjskih obdobjih in pod motom »Znanje je čudovito« prikazali, kako je 4.3 Posebno leto 2020 lahko vsak od nas raziskovalec. V letu 2020 nas je obiskalo zgolj 5 šol [16], štiri od teh so prišle Obiskali smo eno osnovno in dve srednji šoli [17]. v mesecih januar in do sredine februarja, ko je Institut že omejil Osnovnošolcem in dijakom smo, tudi z njihovo pomočjo, gibanje znotraj organizacije zaradi izbruha Covid-19. predstavili osnove znanstveno - raziskovalnega dela skozi Zaradi uvedbe karantene je bil letos Dan odprtih vrat sprva kemijski test vitamina C in pojasnili osnove podjetništva s prestavljen, nato pa odpovedan Upamo, da ga bomo lahko poudarkom na pomenu trženja znanja in idej. Predavali smo o ponovno izvedli že v letu 2021. intelektualni lastnini ter razpravljali o sodobnem podjetništvu in Kot prilagoditev na izbruh nalezljive bolezni se na Institutu stanju na trgu. S tem smo spodbujali zanimanje mladih za uvajajo obiski na daljavo. naravoslovne poklice in zanimanje za raziskave in njihovo uporabo v vsakodnevnem življenju. Obiskali smo še tri domove za ostarele [17]. Sporočilo 5 OBISKI NA DALJAVO obiskov domov za starejše je bilo, da se učimo, izobražujemo in V letu 2020 smo izvedli 9 obiskov in gostili 430 obiskovalcev, raziskujemo skozi celo življenje in da starejši s svojo modrostjo nato morali dne 27. 2. 2020 prekiniti serijo dodatnih 36 do konca in življenjskimi izkušnjami doprinesejo dodano vrednost k junija načrtovanih obiskov šol [18]. Odpovedati smo morali tudi razvoju naše družbe. Tako pravijo, da moramo vedoželjnost “Dan odprtih vrat” in »Teden odprtih vrat« med “Štefanovimi ohraniti skozi celo življenje, da nadgrajujemo naše poznavanje dnevi”, ki se tradicionalno odvijajo konec marca. V mesecih in ozavestimo svet okoli nas in da ne zamremo. marec, april in maj tako ni bilo mogoče izvesti nobenega obiska, smo se pa v tem času reorganizirali in začeli izvajati obiske na daljavo. Ideja o virtualnih obiskih se je rodila iz potrebe, da še naprej oblikujemo zavedanje o vrhunski znanosti kot zanimivi in neobhodni sestavini vsake uspešne družbe ter možnosti in nuje, da vsi skupaj hitro osvojimo komunikacijo na daljavo. Preverili smo interes ter zmožnosti raziskovalcev Instituta za izvedbo obiskov na daljavo. Izvedli smo virtualni sestanek z vsemi koordinatorji, jim pojasnili ter se z njimi pogovorili o novo nastali situaciji ter prosili za mnenja v zvezi z idejo glede virtualne izvedbe obiskov Instituta. Prevladujoče mnenje koordinatorjev je bilo pozitivno, prav tako so se na idejo večinoma pozitivno odzvali vodje enot Instituta. Glavni 683 pomislek glede smiselnosti prehoda na virtualne obiske se je 6 ZAKLJUČEK nanašal na pomanjkanje osebnega stika med raziskovalci Z obiski šol, Tednom in Dnevom odprtih vrat se Institut »Jožef Instituta in obiskovalci, kar je dejansko ena izmed pomembnejših Stefan« že zadnjih 12 let sistematično in izredno proaktivno komponent obiska. Zato smo se osredotočili na ohranjanje vključuje v proces vzpostavljanja učeče se družbe in razmahu osebnega stika - četudi ta poteka virtualno – in v prihodnje bomo zanimanja otrok, učencev, dijakov, študentov ter odraslih za to komponento vzpodbujali in ohranjali kot ključno komponento naravoslovje. To potrjujejo vtisi obiskovalcev. Posameznike na izvedbe virtualnih obiskov. Institut privabi njihova lastna radovednost o tem, kaj se skriva za Že junija smo izvedli 2 virtualna obiska, nato pa še enega v vrati Instituta in kako se raziskovalno delo odraža v vsakdanjem mesecu avgustu (Slika 7) [19]. življenju. Družine prihajajo na Institut predvsem z namenom ciljno usmerjenega in dolgoročnega načrtovanja poklicne poti otrok ter spodbujanja zanimanja za naravoslovje. Hkrati pa so obiski, Teden in Dan odprtih vrat Instituta ' Jožef Stefan'' odlična priložnost za podjetja, da si ogledajo laboratorije Instituta in tako dobijo prvi vtis o možnostih vzpostavitve sodelovanja med gospodarstvom in raziskovalci IJS. Kaže tudi, da se s sprejetjem širše rabe virtualnih komunikacijskih orodij v šolah in v podjetjih odpirajo vedno nove možnosti za tesnejše sodelovanje. Te možnosti z navdušenjem sprejemamo. Z velikim veseljem bomo obiske, dneve, tedne in večere odprtih vrat organizirali še naprej, v prihodnje pa se velja še bolj Slika 7: V letu 2020 smo se po izbruhu bolezni COVID 19 in posvetiti vsebini prikazanih predstavitev in širjenju zavedanja, , z njo povezanih ukrepov preusmerili v izvedbo obiskov na da je znanost ena in edina, da je ključ do prihodnosti in da z njo daljavo. skupaj in enotno dihamo vsi državljani Republike Slovenije. Obiski na daljavo so izvedeni preko prenosa slike in žive ZAHVALE besede koordinatorjev obiskov preko virtualnih orodij. Med obiski je vzpostavljen direkten dialog s šolajočo se mladino, saj Velika zahvala gre Kristini Žagar Soderžnik – brez njene tako učitelje kot učence spodbujamo, da postavljajo vprašanja o pomoči, entuziazma in dobre volje obiski na Institutu ne bi vsem, kar vidijo in slišijo. zaživeli v taki meri, kot so. Prav tako se izvajajo vnaprej pripravljeni virtualni sprehodi Hvala vsem koordinatorjem obiskov, s katerimi smo po laboratorijih. Nekateri sprehodi so omogočeni tudi izven časa sodelovali skozi leta. Mnogi so odšli v tujino ali v industrijo, odprtih vrat, vendar v takem primeru manjka živa beseda mnogi so ostali zvesti Institutu. Kjerkoli ste, upam, da še naprej gostitelja na Institutu. Menimo, da je prav živ človek na drugi širite ljubezen do znanosti tudi med mladimi. strani virtualne povezave ključnega pomena za uspešnost obiskov, pa tudi za doseganje cilja – čim večje razširjenosti LITERATURA IN VIRI zanimanja mladih za znanost. Predstavitve laboratorijev so tako sicer vnaprej pripravljene, vendar pa kljub fizični oddaljenosti [1] Š. Stres, Zadnja sobota v marcu – “Dan odprtih vrat”, IJS potekajo spontano in se prilagajajo trenutni situaciji, potrebam in Novice (Maj 2008). interesu udeležencev in njihovim aktivnostim v času obiska. [2] Š. Stres, Dan odprtih vrat 2009, IJS Novice (Junij 2009). V novem šolskem letu 2020/21 smo začeli zbirati prijave na [3] Š. Stres, K.Žagar, Pregled nad izvedbo obiskov na IJS, IJS obiske s 1.septembrom, prejeli smo že 4 interese in zaključili z Novice (November 2010). načrtovanjem 3 obiskov. Veselimo se nadaljnjih povpraševanj [4] U.Mrgole, Dan odprtih vrat 2018 privabil predvsem šol in posameznikov, z veseljem bomo ponudili ogled čimveč družine, IJS Novice (Maj 2018). interesentom, skladno z možnostmi. V povojih je tudi načrtovanje virtualnega dneva odprtih vrat. [5] U.Mrgole, R.Premk, Za uvod v praznovanje sedemdesete obletnice Instituta »Jožef Stefan« - Dan odprtih vrat IJS, IJS V tem trenutku razvijamo različne ideje. Ena izmed njih je Novice, (Junij 2019). možnost vstopa v virtualne sobe, za omejeno količino časa, npr. za 10 minut, pri čemer bi se osredotočali na izvedbo obiskov [6] Letno poročilo IJS, (2008). predvsem za družine in za skupine šol, pa tudi interesentov v [7] Letno poročilo IJSl, (2009). domovih za ostarele ali druge skupine, ki bi se nam na ta način [8] Letno poročilo IJS, (2010). lahko pridružile. [9] Letno poročilo IJS, (2011). Sodeč po pozitivnih odzivih obiskovalcev, jim bo tudi na tak način predstavljeno delo sodelavcev in opreme Instituta še dolgo [10] Letno poročilo IJS, (2012). ostalo v lepem spominu. [11] Letno poročilo IJS, (2013). Pri tem še naprej ostajamo osredotočeni na organizacijo [12] Letno poročilo IJS, (2014). klasičnih obiskov, ki so se po odzivu šol in šolarjev izkazali za [13] Letno poročilo IJS, (2015). nepogrešljivo doživetje. Obiske na daljavo bi v prihodnje ponujali kot dodatno možnost za premagovanje časovnih, [14] Letno poročilo IJS, (2016). logističnih in drugih ovir za obiske šol. [15] Letno poročilo IJS, (2017). 684 [16] Letno poročilo IJS, (2018). [18] Interno Letno poročilo CTT (2019). [17] M.Ivanišin, T.Lutman, Za Evropsko noč raziskovalcev na [19] M.Pitako, Obiski otrok tudi na daljavo?, IJS Novice, (Julij Institutu »Jožef Stefan« predstavili raziskovalno delo v soju 2020). bakel in sveč, IJS Novice (Oktober 2018). 685 Uporaba aplikacije Padlet za učence s posebnimi potrebami pri pouku na daljavo Using Padlet for pupils with special needs in distance learning Maja Šebjanič Oražem Osnovna šola Puconci Puconci 178 9201 Puconci, Slovenija maja.sebjanic@gmail.com POVZETEK komunikacijsko tehnologijo (v nadaljevanju IKT) in veščost njene uporabe v največjo korist. V prispevku je prikazan primer uporabe aplikacije Padlet za namene izvajanja dodatne strokovne pomoči učencem s posebnimi potrebami pri pouku na daljavo v času zaprtja 2 POUK NA DALJAVO vzgojno-izobraževalnih ustanov zaradi razglašene epidemije. Delo z učenci s posebnimi potrebami je že v običajnem šolskem Pouk na daljavo se v veliki meri razlikuje od “klasičnega” pouka, okolju specifično, pri prenosu pouka v virtualna okolja pa je bilo to je pouka v živo, v učilnicah. Razlike so tako na potrebno pri načrtovanju in izvajanju pomoči v digitalno organizacijskem kot tudi na pedagoško-didaktičnem področju. podprtem okolju svoje delo oblikovati še bolj premišljeno. “Učno okolje v tem primeru dobiva popolnoma nove razsežnosti in predstavlja enega izmed temeljev uspešne izvedbe poučevanja KLJUČNE BESEDE in učenja.” [3] Zaradi razglašene epidemije so se vrata vzgojno- Pouk na daljavo, dodatna strokovna pomoč, Padlet izobraževalnih ustanov s 16. 3. 2020 zaprla. V kratkem času so ABSTRACT morale šole vzpostaviti ustrezno digitalno podprto učno okolje za izvajanje pouk na daljavo. Vsaka šola je glede na svoje The article presents an example of Padlet use for providing specifike in možnosti pripravila svoj način dela. additional professional help for pupils with special needs at a Vloga učitelja (in tudi učenca) se pri pouku na daljavo distance learning during epidemic. Working with pupils with spremeni, saj se več ne osredotoča na razlago snovi, temveč na special needs is already specific in the usual school environment, tako imenovane podporne pogovore, katerih namen je nudenje and when the lessons move to virtual environment, it was individualne in dodatne pomoči učencem, motiviranje za necessary to design teachers work even more thoughtfully. izvajanje aktivnosti in tudi nudenje dodatnih učnih izzivov učencem, ki učno vsebino že obvladajo. Zaradi tega je izrednega KEYWORDS pomena, da je učitelj ustrezno usposobljen in da v digitalno Distance learning, additional professional help, Padlet podprtem učnem okolju pri svojem delu premišljeno uporablja sodobne didaktične pristope. Le na ta način lahko pouk na daljavo izvaja kakovostno [3]. 1 UVOD Glavne značilnosti pouka na daljavo najbolj nazorno Z razglasitvijo izrednih razmer zaradi epidemije covid-19, prikazuje shema (slika 1). zaprtjem vzgojno-izobraževalnih ustanov in “preslitvijo” pouka v virtualna okolja se je marsikateri učitelj znašel pred vprašanjem “Kako pripraviti in izvajati pouk na daljavo?” Pred (morda še večjo) zagato smo se znašli tudi učitelji dodatne strokovne pomoči za učence s posebnimi potrebami, saj je narava našega dela specifična – individualno delo “ena na ena”. Zato je bilo potrebno v kratkem času dobro pretehtati in ubrati pot, ki bo učencem glede na njim razpoložljivo informacijsko- Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must Slika 75: Poučevanje na daljavo [3] be honored. For all other uses, contact the owner/author(s). Učitelj mora imeti do obsega dela učencev pri pouku na Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). daljavo realne zahteve, dajati jim miora jasna navodila, primeren 686 obseg dela in jim posredovati sprotno povratno informacijo. Ob ohranjali stike na način in preko orodij ter komunikacijskih tem pa je potrebno poskrbeti tudi za to, da dosežemo vse oziroma naprav, ki so jih vajeni oziroma katerih so vešči. čim več učencev [3]. Ravno slednje je pri učencih s posebnimi Učencem s posebnimi potrebami je učitelj dodatne strokovne potrebami v veliki meri zagotovljeno s strani učiteljev za dodatno pomoči pomembna oseba na šoli, na katero se lahko obrne, zato strokovno pomoč. je zanje pomembno, da ohranijo stik z osebami, ki jim zaupa. Težave, ki se jim pojavljale v teh razmerah, smo jim pomagali premagovati preko različnih tehnik in strategij ob uporabi IKT. 3 DODATNA STROKOVNA POMOČ Učencem smo tako pomagali s svetovanjem, razlago (tako Učencem, ki so zaradi določenih primenjkljajev, motenj oziroma učiteljevih navodil, učne snovi kot tudi postopkov uporabe IKT) ovir usmerjeni kot učenci s posebnimi potrebami, pripada za preko različnih komunikacijskih kanalov in hkrati ohranjali stik premočjanje težav po [8] dodatna strokovna pomoč. z njimi. Navodila za učenje in organizacijo za učenje smo jim učitelji pogosto podprli tudi z različnimi IKT orodji [7], 3.1 Metode in pristopi aplikacijami in podobno. Učenci s posebnimi potrebami potrebujejo za optimalen napredek in rezultate prilagojene metode in pristope poučevanja. 4 APLIKACIJA PADLET Pri tem običajno kombiniramo direktno poučevanje (jasno določeni cilji, pravila, specifični koraki, ki se natančno razložijo, Padlet (nekdanji Wallwisher) je aplikacija oziroma e-storitev, ki demonstracija korakov in povezav med pojmi) s strateškim omogoča “skupno rabo”. Ima obliko table oziroma zida, na poučevanjem (učenje strategij reševanja naloge in uporabe znanj katerega lahko pišemo in objavljamo sporočila, pripenjamo pri reševanju problemov) [2]. “Obe metodi terjata modeliranje, različna gradiva, delimo slike ali posnetke [5, 6]. Učenci (in demonstracije, povratne informacije, vodeno in samostojno drugi) lahko dostopajo do table preko posredovane povezave ali izvajanje vaj ter transfer znanja in naučenih strategij.” [4] QR kode. Učencem s posebnimi potrebami v ta namen s pomočjo Padlet podpira vse vrste datotek in je preprost za uporabo, drugačnih didaktičnih in metodičnih pristopov, tehnik, potrebnega je le nekaj osnovnega znanja angleščine. Do pripomočkov in podobno prilagajamo vsebino in organizacijo, pa aplikacije lahko dostopamo preko spleta na računalniku ali tudi hitrost napredovanja, cilje in organizacijo vzgojno- pametnem telefonu. V slednjem primeru si je potrebno prenesti izobraževalnega okolja [1]. in namestiti aplikacijo na telefon. Osnovna različica, ki je brezplačna, omogoča omejeno 3.2 Individualizirani program kreiranje različnih tabel, pri čemer so nam na voljo predloge Za vsakega učenca s posebnimi potrebami strokovna skupina, ki (slika 2). Če želimo različico izboljšati oziroma razširiti, jo lahko jo za posameznega učenca pred pričetkom šolskega leta imenuje glede na svoje želje in potrebe proti doplačilu poljubno ravnatelj, glede na učenčeve težave, motnje oziroma ovire nadgradimo. pripravi individualizirani program. Z individualiziranim programom se po [8] (36. člen) določijo: (a) cilji in oblike dela na posameznih vzgojno-izobraževalnih področjih; (b) strategije vključevanja učenca s posebnimi potrebami v skupino; (c) potrebne prilagoditve pri preverjanju in ocenjevanju znanja, doseganju standardov in napredovanju; (č) uporaba prilagojene in pomožne izobraževalne tehnologije; (d) izvajanje fizične pomoči; (e) izvajanje tolmačenja v slovenskem znakovnem jeziku; (f) prehajanje med programi in potrebne prilagoditve pri organizaciji; (g) časovna razporeditev pouka; (h) veščine za čim večjo samostojnost v življenju (prilagoditvene spretnosti) in (i) načrt vključitve v zaposlitev. Za čas pouk na daljavo je zavod za šolstvo izdal priporočila za potek nudenja dodatne strokovne pomoči ter za preverjanje in Slika 76: Predloge za kreiranje table ocenjevanje znanja v osnovni šoli. Za učence s posebnimi potrebami so tako priporočali, da je pri preverjanju in 4.1 Uporaba aplikacije pri nudenju dodatne ocenjevanju znanja v primerih, ko se prilagoditev, zapisanih v strokovne pomoči na daljavo individualiziranem programu, pri delu na daljavo ne da v celoti izvesti, priporočljivo dodati spremembe prilagoditev, ki se Za namene nudenja dodatne strokovne pomoči učencem s upoštevajo v času izobraževanja na daljavo. posebnimi potrebami na daljavo smo se poslužili aplikacije Padlet, saj se nam je zdela pregledna, preprosta za razumevanje 3.3 Izvajanje dodatne strokovne pomoči na in uporabo in privlačna za učence. daljavo Po uvodnih postopkih za registracijo smo se lotili raziskovanja možnosti, ki jih aplikacija nudi. Kot najbolj Razmere, v katerih smo se marca 2020 zaradi epidemije znašli, pregledno in uporabno, kar je zlasti za učence s posebnimi so od učiteljev dodatne strokovne pomoči zahtevale veliko mero potrebami zelo pomembno, saj imajo pogosto težave z inovativnosti in iznajdljivosti. V tem času je bilo potrebno nuditi usmerjanjem pozornosti, orientacijo in organizacijo, se nam je oporo tako staršem kot učencem. S starši smo vzpostavljali in zdelo oblikovanje table s tematskimi sklopi. Te smo poimenovali 687 glede na predmet oziroma področje, ki so ga posamezne objave/gradiva pokrivala (slika 3). Slika 79: Miselni vzorec Občasno smo učencem pripenjali sprostitvene aktivnosti in miselne premore, ki smo jih pripredili po spletnih virih in oblikovali v slikarju (primer: slika 6), ali pripeli povezave do Slika 77: Oblikovana table z gradivi različnih posnetkov na spletu. Za mlajše učence so se kot Za uporabo aplikacije Padlet in oblikovanje table z gradivi pozitivne obnesle zvočne pravljice, ki so jih lahko poslušali. smo se odločili, saj smo želeli na enem mestu ponuditi učencem vseh razredov, s katerimi delamo, različne vrste gradiv, ki so jim pri pouku na daljavo in pri izpolnjevanju šolskih obveznosti lahko v pomoč. Na ta način so zlahka in hitro lahko dostopali do nabora gradiv oziroma pripomočkov, kakor jih imenujemo pri našem delu. 4.2 Gradiva za nudenje dodatne strokovne pomoči na daljavo Pri pripravi gradiv za nudenje dodatne strokovne pomoči smo upoštevali naslednje zahteve: (a) individualizirani program posameznega učenca, vključujoč njegova močna in šibka področja ter učne značilnosti; (b) navodila učečih učiteljev za posamezen teden; (c) diferenciacijo in individualizacijo dela za Slika 80: Predlog miselnega premora Učencem (in tudi njihovim staršem) smo povezavo do naše posameznega učenca (glede na naravo njegovih težav, zmožnosti table posredovali na začetku pouka na daljavo in jih pozvali, da in podobno); (č) IKT, ki jo ima učenec doma na voljo; (d) naj sproti spremljajo vsebino in gradiva, ki smo jih ves čas sproti dostopnost orodij in aplikacij za pripravo gradiva; (e) uporabnost posodabljali. gradiva za učenca pri izpolnjevanju nalog/obveznosti. Upoštevaje navedene zahteve smo se najpogosteje poslužili priprave povzetkov učne snovi, s poudarkom na temeljnih 5 ZAKLJUČEK pojmih obravnavane učne teme, ki smo jih pripravili v Wordu, shranili v format PDF in objavili na naši tabli Padlet (primer: Čas epidemije je učitelje postavil pred številne nove izzive, slika 4). vezane zlasti na IKT. Sodobni učitelj mora biti prožen in se na digitalno-tehnološke spremembe odzivati hitro. Imeti mora določena znanja, razvite spretnosti in veščine, tako imenovane digitalne kompetence, da lahko sodobno IKT uporablja preudarno in kompetentno. Na spletu je dostopno mnogo različnih orodij, aplikacij in storitev, ki so lahko zelo uporabni v izobraževalne namene. Zlasti kot uporabni so se izkazali v času pouk ana daljavo. Tudi sami smo skušali dodatno strokovno pomoč na daljavo izvesti čim učinkoviteje in uporabno za učence. Aplikacija Padlet, ki smo se je pri tem poslužili, nam je omogočala, da smo v kratkem času lahko pripravili za učence pregledno in na videz privlačno tablo, Slika 78: Povzetek učne snovi na kateri so zlahka našli gradivo za pomoč pri delu na daljavo. Povzetke učne snovi, zlasti pri pouku književnosti, občasno Učenci so bili nad takšnim načinom dela navdušeni, kar je ne tudi jezika, smo pripravljali tudi v obliki miselnih vzorcev, ki nazadje tudi najpomembnejše. smo jih oblikovali s pomočjo spletne aplikacije Mindomo (primer: slika 5). VIRI IN LITERATURA [1] Galeša, M. 1995. Specialna metodika individualizacije. Radovljica, Didakta. [2] Košir, S. idr. (2008). Navodila za prilagojeno izvajanje programa osnovne šole z dodatno strokovno pomočjo. 688 Primanjkljaji na posameznih področjih učenja. Ljubljana, [5] Padlet – Apps on Google Play. 2020. Zavod Republike Slovenije za šolstvo. DOI= DOI=https://play.google.com/store/apps/details?id=com.w http://www.ucne- allwisher.Padlet&hl=en_US. tezave.si/files/2016/10/Navodila_primanjkljaji_podrocja_u [6] Padlet – SIO podpora. 25. 3. 2014. cenja.pdf. DOI=https://podpora.sio.si/padlet/. [3] Kustec, S. idr. 2020. Vzgoja in izobraževanje v Republiki [7] Za učitelje, izvajalce dodatne strokovne pomoči. 26. 3. Sloveniji v razmerah, povezanih s covid-19- Modeli in 2020. Ljubljana, Zavod Republike Slovenije za šolstvo. priporočila. Ljubljana: Ministrstvo za izobraževanje, DOI=https://www.zrss.si/objava/za-ucitelje-izvajalce- znanost in šport ter Zavod Republike Slovenije za šolstvo. dodatne-strokovne-pomoci. DOI=https://www.zrss.si/pdf/modeli_in_priporocila.pdf. [8] Zakon o usmerjanju otrok s posebnimi potrebami [4] Navodila za izobraževalne programe s prilagojenim (ZUOPP-1). Uradni list RS, št. 58/2011. izvajanjem in dodatno strokovno pomočjo za devetletno DOI=http://www.uradni- osnovno šolo. 2003. Ljubljana, Ministrstvo za list.si/1/objava.jsp?urlid=201158&stevilka=2714. izobraževanje, znanost in šport. DOI=www.zrss.si/doc/050911101018__pp_prilagojeno_iz vajanje_programa_os_maj.doc. 689 Oblikovanje učencu prilagojenih e-gradiv Designing student-friendly e-materials Urška Šuštaršič OŠ Danile Kumar Gogalova 15 1000 Ljubljana, Slovenija sustarsicu@os-danilekumar.si POVZETEK considered in the preparation of e-materials and their adaptation. We presented ways to detect and recognize emotions in e- Ustrezna tehnologija in želja po učenju je pripeljala do fenomena learning and focused on the possibilities of adapting learning učenja preko IKT tehnologij. Sedaj se lahko učenci učijo materials to students based on them. We looked for ways to kitajščine na na prestižni pekinški šoli iz naslonjača svoje dnevne improve the e-learning experience for students in a way that sobe, lahko prisostvujejo pri kemijskih poskusih v nemških would increase the transparency of the students progress and laboratorijih ali pa se učijo igranja kitare. Kako bodo pri tem increase the positive e-learning experience in a way that would uspešni, pa je odvisno tudi od primerne priprave in prilagajanja also include their well-being in the learning process. Based on a učnih gradiv. Čustva pomembno vplivajo na učenje, ne glede na survey conducted with students from 6th to 9th grade of primary metodo po kateri se učimo. V prispevku smo ob pregledu school, we designed a model for adapting e-learning materials. literature raziskovali v kakšni meri se čustva, počutje in Guidelines for adjustment were better organization, higher vpletenost učencev upoštevajo pri pripravi e-gradiv in njihovemu motivation and reduction of work overload feeling. prilagajanju. Predstavili smo načine za zaznavanje in prepoznavanje čustev pri e-učenju in se osredotočili na možnosti KEYWORDS za prilagajanje učnih gradiv učencem na podlagi le-teh. Iskali smo načine, kako izboljšati izkušnjo e-učenja za učence na način, E-learning, emotions, student-friendly materials, primary school da bi povečali preglednost napredka učenca in povečali pozitivno izkušnjo e-učenja na način, da bi v učni proces vključili tudi 1 UVOD njihovo počutje. Učenje je kompleksen proces, pri katerem imajo čustva Na podlagi ankete, ki smo jo izvedli z učenci od 6. do 9. razreda pomembno vlogo. Čustva vplivajo na motivacijo, pozornost, osnovne šole, smo zasnovali model za prilagoditev gradiv za e- koncentracijo, zaznavanje, predelavo in pomnjenje informacij, učenje. Smernice za prilagajanje so bile boljša organizacija, višja samoregulacijo in številne druge aspekte učenja [1]. Psihologinja motivacija za delo in zmanjševanje občutka preobremenjenosti Woolfolk ugotavlja, da ja za optimalno učenje potrebno ohraniti za delo. ravno pravo raven vzburjenja glede na nalogo, kar pomeni stalno opazovanje učencev in prilagajanje dejavnosti glede na njihove KLJUČNE BESEDE povratne informacije [2]. Raziskava med slovenskimi učitelji E-učenje, čustva, učencu prilagojena gradiva, osnovna šola ugotavlja, da se le-ti zelo dobro zavedajo pomena čustev pri učenju. Med poučevanjem so tako pozorni na čustva, ki jih ABSTRACT učenci izražajo med poukom in jih, preko različnih pristopov, Appropriate technology and a desire to learn has led to the poskušajo tudi uravnavati [3]. Kako pa je s čustvi pri učenju na phenomenon of learning through ICT technologies. Now, from daljavo? Osredotočili smo se na osnovnošolce in raziskovali, the armchair of their living room, students can learn Chinese at a kakšna čustva so doživljali pri učenju na tak način, kako jih sploh prestigious Beijing school, attend chemical experiments in a prepoznati in kakšne so možnosti za naše upoštevanje le-teh pri German laboratory, or learn to play the guitar. How successful pripravi učencu bolj prilagojenih gradiv. they will be also depends on the appropriate preparation and adaptation of teaching materials. Emotions have a significant impact on learning, regardless of the learning method. In this 2 UČENJE NA DALJAVO paper, while reviewing the literature, we explored the extent to Učenje na daljavo poznamo že zelo dolgo. Začelo naj bi se že which students' emotions, feelings and involvement are pred sto leti z učenjem preko dopisovanja, in sicer v redko poseljenih državah Avstralije, Nove Zelandije in ZDA [4]. Termin e-učenje navadno uporabljamo za učenje preko spleta, Permission to make digital or hard copies of part or all of this work for personal or kar ni napačno, toda pomeni še veliko več kot to. Elektronsko classroom use is granted without fee provided that copies are not made or distributed oziroma e-učenje je v osnovi definirano kot učenje s pomočjo for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must informacijsko-komunikacijskih tehnologij (IKT) [5]. Nanaša se be honored. For all other uses, contact the owner/author(s). na uporabo elektronskih medijev v različne izobraževalne Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). namene, od uporabe IKT v klasični učilnici do komunikacije na 690 daljavo. Pojavlja se v različnih oblikah, kot so: spletno učenje • možnost večperspektivnega prikaza snovi (interaktivni (web based learning), virtualna učilnica, e-komunikacija, način učenja), računalniško podprta interaktivna komunikacija in podobno. • poljubnosti prostora (posameznik se lahko uči na katerikoli lokaciji želi), 2.1 E-učenje in klasično učenje • poljubnost hitrosti (posameznik izbira kako hitro oziroma počasi jemlje snov), Zaradi določenih specifičnih prednosti, je e-učenje vse bolj • poljubnost časa (posameznik izbere čas učenja). prisotno na vseh ravneh izobraževanja, še posebej na Prav tako zmanjša stroške izobraževanja. Zmanjšanje visokošolski ravni. Zaradi različnih razlogov, kot so stroškov je posledica različnih dejavnikov: ni izgubljenega časa digitalizacija šolstva kot tudi nepredvidljive izredne razmere, se na poti do izobraževalnega središča, ni potnih stroškov, ni e-učenje vse bolj vpeljuje tudi na osnovnošolsko raven. Oba stroškov povezanih z učilnicami, omogoča pridobivanje znanja načina poučevanja imata svoje značilnosti (Tabela 1). Naš fokus po potrebi. Podatki so stalno posodobljeni. Zaradi hitrega je usmerjen predvsem na poudarek v učnem procesu, motivacijo tehnološkega razvoja znanje prej zastara. Strokovne knjige in vlogo učitelja pri poučevanju. postanejo zastarele že kmalu po izdaji. Spletna gradiva imajo v primerjavi s knjigami veliko prednost, saj jih je mogoče sproti Tabela 5. Primerjava e-učenja in klasičnega učenja [6] posodabljati [12]. 2.4 Izzivi e-učenja Kot slabost e-učenja šteje to, da je e-učenje v večini primerov formalno naravnano in z manj priložnostmi za neformalno izobraževanje. E-izobraževanje je pogosto učenje v zamudi, posameznik navadno ne dobi takojšnje povratne informacije, ko jo potrebuje, ampak šele kasneje v časovnem presledku. Če je veliko posredovanja preko spleta, iz strani učitelja in učenca ni vključenih veliko čustev, zato je tudi motivacija za učenje lahko slabša. E-učenci morajo biti zato veliko bolj samostojni, motivirani in zanesljivi kot tradicionalni učenci [8]. V klasični učilnici ima učitelj direkten vpogled v počutje učencev, saj lahko jasno prepoznava, kdaj so učenci aktivni/manj aktivni, doživljajo pozitivna oz. negativna čustva in na podlagi tega prilagaja pouk. Pri e-učenju pa se ta vidik pogosto zanemarja, saj je težko dosegljiv in merljiv. Raziskovalci zato opozarjajo, da so čustva zelo pomembna, če ne še bolj, tudi pri e-učenju in jih je potrebno Raziskave na področju primerjave klasičnega učenja in e- upoštevati, kako in na kakšen način, pa bo potrebno podrobneje učenja kažejo različne rezultate. Nekatere ugotavljajo, da med raziskati [13], [14]. danima načinoma učenja ni pomembnih razlik [7]. Ameriška Raziskovanja aspekta vključevanja učencev pri e-učenju smo primerjava med študenti glede motivacije/zanimanja za delo in se lotili tudi mi. ocen pri prvem preizkusu znanja navaja več prednosti pri klasični metodi učenja. Študentje, ki so se izobraževali po identičnem 2.5 Sistemi, ki prilagajajo gradiva programu preko e-učenja, so sicer kazali več zanimanja za delo Obstaja že veliko sistemov, ki na podlagi različnih dejavnikov in posledično imeli več motivacije za delo, a so se izkazali s prilagajajo gradiva svojim uporabnikom. Na podlagi predznanja, slabšimi ocenami prvega izpita kot študenti, ki so se izobraževali časovnega okvirja in starosti se prilagaja zahtevnost, obširnost in preko klasičnih predavanj [8]. Nekatere študije pa poročajo o več količina gradiv. prednostih učenja na daljavo [9]. Raziskovalci so oblikovali tudi gradiva na podlagi učnih stilov posameznika [7] in pričeli s študijami, kako prilagajati 2.2 Čustva pri klasičnem in e-učenju učna gradiva glede na počutje učencev [15]. Raziskave kažejo, da ni pomembnih razlik pri izražanju akademskih čustev med klasičnim učenjem in e-učenjem. Na 3 ČUSTVA IN UČENJE splošno so rezultati raziskav v e-okoljih vzporedni z rezultati v tradicionalnih učilnicah, kar kaže na to, da so čustva v spletnih 3.1 Akademska čustva učnih okoljih v primerjavi s klasičnimi učilnicami podobna [10]. Zato lahko čustva v e-okoljih raziskujemo po identičnih Akademska čustva so povezana s čustvi, ki jih učenci doživljajo paradigmah. med učenjem. Feldman Barrett in Russell delita akademska čustva na pozitivna/negativna ter na čustva, ki aktivirajo in de- 2.3 Prednosti e-učenja aktivirajo posameznika med učenjem (Tabela 2) [15]. Pozitivna čustva so tista, ki jih učenci doživljajo kot prijetna Prednosti e-učenja, v ospredju učenja preko spleta [11]: in pri njih vzbujajo veselje do učenja, spodbujajo motivacijo, aktivnost in zbranost, večajo kritičnost in fleksibilnost mišljenja. Negativna čustva so tista, ki jih učenci doživljajo kot neprijetna 691 in praviloma zavirajo proces učenja, demotivirajo, zmanjšujejo • vedenjski (opazovanje ali zajem motorično-vedenjskih stopnjo pozornosti in motivacije za učenje. aktivnosti, kot so obrazni izrazi, intonacija glasu, telesna drža, analiza vnosa besedila …). Tabela 2. Akademska čustva po Feldman Barrett, 2. stopnja: vrednotenje čustev Russell in Pekrun A – pred nalogo (subjektivno poročilo učenca). Če je učenec žalosten oz. utrujen, se sistem praviloma izogne novi snovi. B – med nalogo (subjektivno poročilo učenca). Učenci določajo vrsto in intenzivnost čustev, ki jih doživljajo. C – analiza počutja po nalogi (analiza preko vnesenega teksta učenca ali preko subjektivnega poročila učenca). D – evalvacija počutja učenca (na podlagi dobljenih podatkov se učencu določi njegovo počutje: žalost, dolgočasje, utrujenost, zmedenost …). Povratna informacija Pomemben del sistema je, na podlagi pridobljenih informacij in Pekrun [15] deli čustva na štiri področja. Čustva, ki jih učenci podanih algoritmov, avtomatsko oblikovanje primerne povratne doživljajo ob dosežkih, uspehih oz. neuspehih (veselje, upanje, informacije učencu, da pri učenju spodbudi čim večjo čustveno ponos/sram, anksioznost). Epistemološka čustva so tista, ki jih varnost in vztrajnost pri delu. Sistem se lahko odzove bodisi s sprožajo kognitivni problemi ob učenju, predvsem pri novih in paralelno-empatičnim (npr. »to je bilo pa stresno, poskusimo neznanih nalogah (radovednost, zmedenost, frustracije ob ovirah, nekaj drugega«) ali reaktivno-empatičnim odgovorom (»Izberi si presenečenje…). Temeljna čustva so tista, ki se vežejo na teme naslednji izziv…«) ali pa predlaga spremembo nalog (npr. in snovi, ki so predstavljene med poukom, povezane z interesi sprememba zaporedja nalog). učencev (zanimanje, nezanimanje). Socialna čustva so vezana na odnose z učitelji in sošolci (sočutje, ljubezen, zavist, jeza…). Pri poučevanju je pomembno, da jih učitelj pozna in upošteva tako 5 IDEJNA ZASNOVA UČENCU pri učenju, kot tudi pri pripravi in oblikovanju gradiv. PRILAGOJENEGA E-GRADIVA Zaradi izrednih razmer smo osnovne šole v šolskem letu 2019/20 4 PRILAGAJANJE E-GRADIV GLEDE NA od marca do maja izvajale celoten pouk na daljavo. Ker je pouk POČUTJE večinoma potekal preko spleta, lahko govorimo o e-učenju ali celo spletnemu učenju. V zelo kratkem časovnem obdobju je bilo 4.1 Raziskave potrebno prilagoditi gradiva spletnemu načinu dela, kar vsekakor ni bilo enostavno. Pri tem smo se srečevali s številnimi izzivi. Več raziskav na tem področju se je pričelo v letu 2011 z uvedbo Eden izmed teh je bil, kako vzdrževati motivacijo učencev za t.i. projekta ALICE (Adaptive Learning via Intuitive/Interactive, delo in njihovo vztrajnost, prav tako pa tudi kako pomagati Collaborative and Emotional systems). Cilj programa je bil učitelju, da bi lažje spremljal učence pri delu. oblikovati inovativno prilagojeno okolje za e-učenje, ki je Učencem smo želeli učna gradiva čim bolj približati, tako z interaktivno in se prilagaja učenčevim čustvom, spodbuja vidika dejavnosti in načina dela, kot tudi preveriti njihovo njegovo opolnomočenje, gradi socialno identiteto in zagotavlja doživljanje ob delu in gradiva prilagajati še iz tega vidika. Po pristno učno izkušnjo [16]. enem mesecu e-učenja smo izvedli spletno anketo o delu na daljavo, na podlagi katere smo zbrali prevladujoča čustva 4.2 Emotivni sistem e-učenja učencev, ki so bila temelj za oblikovanje poskusnega sistema Velik izziv e-učenja je, kako čim bolje zaznavati in prepoznavati gradiv po metodi Feidakis in Daradoumis [17]. počutje učencev, da bi na podlagi teh spoznanj lahko prilagajali učenje, kot to počnejo učitelji v klasični učilnici. Feidakis in Daradoumis [17] sta oblikovala t. i. inteligentni 6 PRILAGAJANJE E-GRADIV emotivni sistem za e-učenje, ki izboljšuje učno izkušnjo učencem Oblikovanje gradiv je potekalo v treh stopnjah in sicer: analiza in spodbuja tudi razvoj učenčevih socialnih in čustvenih stanja učenja na daljavo in prepoznavanje prevladujočih počutij kompetenc. Navajata tri stopnje sistema, ki so bolj podrobno učencev ob tem, posodobitev interaktivnih gradiv na podlagi opisani v nadaljevanju. prepoznanih prevladujočih občutij ter oblikovanje smernic za 1. stopnja: zaznavanje in prepoznavanje čustev konstruktivne povratne informacije. Opredelitev treh načinov za merjenje čustev: 6.1 Analiza e-učenja • psihološki (subjektivno poročilo učenca z uporabo Za namen naše raziskave smo uporabili psihološki način verbalnih ali slikovnih lestvic oz. vprašalniki itd.), merjenja čustev, čustva učencev smo ugotavljali preko • fiziološka (uporaba senzorjev za zajemanje biometričnih subjektivnega poročila z uporabo lestvic v obliki spletne ankete. signalov: EMG, EKG…), 692 S spletno anketo o e-učenju smo želeli izvedeti mnenje izpolnjevali po lastni organizacijski shemi in ob tem pisali učencev o zahtevnosti dela, izvedeti kako uspešni se počutijo pri dnevnik opravljenih nalog. Po končani nalogi so dodali svojo delu in njihovo počutje ob učenju na tak način. V anketi je samooceno v obliki trostopenjske slikovne lestvice (Slika 3). sodelovalo 222 učencev od 6. do 9. razreda. Analiza ankete Ugotovili smo, da je 94 % učencev za dostop do gradiv uporabljalo splet, pri čemer lahko govorimo o spletnem učenju. 70 % učencev je ocenilo, da delo z e-napravami obvladajo, samo 5 % učencev je ocenilo, da pri tem potrebujejo pomoč. Večina (90 %) učencev je naloge opravljala sama, brez pomoči staršev Slika 3: Primer naloge za matematiko ali drugih. Velika večina učencev pravi, da so, po njihovem Ta sistem dela je odlično deloval za 80 % učencev, ki so mnenju, uspeli opraviti vse naloge (81 %). Kot glavne razloge za naloge redno opravljali (Slika 81), za ostalih 20 % učencev pa nedokončanje vseh nalog so učenci navajali predvsem smo iskali druge rešitve, tudi v prilagoditvi gradiv. pomanjkanje organizacije, motivacije in preobremenjenost (Slika 81). Prenos gradiv v Google Slides Za prilagoditev gradiv smo uporabili Googlovo orodje Google Slides. Orodj je brezplačno in podprto v vseh operacijskih sistemih. Omogoča spletno ustvarjanje in urejanje predstavitev, deljenje preko povezav in urejanje z drugimi udeleženci [18]. Gradivo smo prilagodili na podlagi treh najpogostejših težav, ki so jih učenci navajali v anketi kot glavne razloge, da niso dokončali vseh nalog. Organizacija Slika 81: Ali si uspel/a narediti vse do sedaj zahtevane Oblikovali smo tedenski urnik, v katerega smo preko povezav naloge? (n = 207) umestili vse naloge, ki so bile razdeljene na 45 minutne sklope po predmetih (Slika 4). Prepoznavanje prevladujočih počutij učencev Učenci so večinoma poročali o pozitivnih čustvih (Slika 82). Pod drugo pa so navajali brezvoljnost, strah, tesnobo, osamljenost, nevtralnost in podobno. Slika 82: Večino časa se počutim (n = 209) Na podlagi pridobljenih podatkov smo zbrali prevladujoča, kontrastna čustva in jih razdelili v tri sklope glede na vrednost in Slika 4: Tedenski urnik s povezavo aktivacijo, in sicer: - pozitivna – visoka aktivnost (zadovoljstvo, veselje, Motivacija radovednost), Motivacijo lahko povečamo preko višje participacije - pozitivna/negativna - nizka aktivnost (sproščenost, posameznika, spodbujanja radovednosti in preko dajanja večje dolgočasje), možnosti odločanja/izbire. Aktivnost lahko učenem povečamo tudi z raznolikostjo, presenetljivimi dejavnostmi in kratkimi - negativna – visoka aktivnost (strah, tesnoba). fizičnimi aktivnostmi [2]. Zato smo ob zaključku vsakega sklopa 6.2 Prilagajanje gradiv nalog določenega predmeta ohranili 3-stopenjsko samooceno opravljenih nalog in dodali možnost za opombe. Na koncu smo Začetno stanje dodali še 4 možnosti, ki jih učenec izbere glede na vrednost Osnovna oblika gradiv, ki smo jih pripravljali za učence, je bila (pozitivna/negativna) in aktivacijsko pozicijo trenutnega počutja pripravljena v obliki PDF. Naloge s cilji so bile pripravljene za 1 (visoka/nizka): teden in razdeljene po predmetnih področjih. Učenci so naloge - pozitivna – visoka aktivnost: »Grem na naslednji predmet/nalogo«, 693 - pozitivna/negativna – nizka aktivnost: «Potrebujem motivacije/prizadevanja za delo in empatične spodbude v obliki izziv«, poudarjanja močnih točk, izpostavitve določenega čustva ali - negativna – visoka aktivnost: «Vaje nudenja potrebne pomoči. sproščanja/Kontakt učitelja«. 7 DISKUSIJA Dodana vrednost prispevka je v iskanju rešitev, kako spletno učenje čim bolj približati klasičnemu učenju, predvsem v smislu socialne in psihološke podpore posamezniku, ki so jo učenci Slika 5: Več možnosti izbire glede na trenutno počutje vajeni v klasičnem razredu. učenca To smo storili preko vpeljevanja sprememb v spletno učenje na področju organizacije in preglednosti nad nalogami; z Vaje sproščanja, miselni in športni izzivi so povezave na vpeljevanjem več izbir pri delu smo želeli dvigniti motivacijo za spletne posnetke/vaje in na sklop vaj izdelan prav tako v Google delo, preko označevanja težavnosti nalog vplivati na manjši Slide orodju. občutek preobremenjenosti. Za lažje oblikovanje povratnih informacij učitelja učencu, pa smo dodali še evalvacijo počutja Preobremenjenost učenca. Za lažjo prilagajanje težavnosti smo v osnovnem urniku označili Sam sistem od učitelja terja zelo veliko časa in energije, kar tiste ure predmetov, za katere učitelji ocenjujejo, da so bolj je velika pomanjkljivost, za katero bomo iskali boljše rešitve, zahtevni (Slika 6). Na tak način učenci lažje izbirajo tiste predvsem v uporabi drugih spletnih platform. Naš sistem smo dejavnosti, ki bolj ustrezajo njihovemu trenutnemu razpoloženju. oblikovali v orodju Google Slide, ena izmed možnosti je tudi uporaba aplikacije Microsoft Teams v okolju Microsoft 365, ki pa je za uporabo malce zahtevnejša. Nadaljnje delo bo usmerjeno tudi v iskanje bolj optimalnih tehničnih rešitev. 8 ZAKLJUČEK V prispevku smo iskali načine, kako izboljšati izkušnjo e-učenja za učence na način, da bi povečali preglednost napredka učenca, povečali njihovo motivacijo in jih podprli v učenju in predvsem v učni proces vključili tudi počutje učencev. Slika 6: Z zvezdico označene, po mnenju učitelja, bolj V izvedeni anketi med osnovnošolci so učenci navedli tri zahtevne naloge glavne razloge, zakaj pri e-učenju niso bili uspešni in sicer težave z organizacijo, motivacijo in preobremenjenost. Te trije vidiki so Evalvacija počutja učenca bili izhodišče za preoblikovanje že obstoječih e-gradiv s spletnim orodjem Google Slides. Ob zaključku delovnega dneva oz. po izpolnitvi zadanih nalog Na podlagi literature in lastnih izkušenj smo tako zasnovali učenec odgovori na vprašanje o njegovem počutju tekom model za prilagoditev gradiv za e-učenje, s katerim želimo delovnega procesa, ki učitelju nudi pomembno informacijo o učenem omogočiti boljšo organizacijo, višjo motivacijo za delo njegovem počutju (Slika 7). in zmanjševati občutek preobremenjenosti za delo. Prav tako pa pomagati učitelju k večji preglednosti učenčevega dela. V kakšni meri smo bili pri tem uspešni, bo pokazala uporaba in nadaljnje študije. Pomanjkljivosti takega modela vidimo v tem, da je za samo oblikovanje potrebno zelo veliko časa. Če želi imeti učitelj pregled nad delom posameznega učenca, mora izpolnjevati vsak svoj dokument, kar poveča obremenjenost učitelja tako pri Slika 7: Evalvacija počutja učenca pripravi, kot tudi pri pregledovanju gradiv. V vsakem primeru pa mora povratno informacijo še vedno oblikovati za vsakega 6.3 Oblikovanje povratne informacije posameznega učenca posebej. Smernice, da bi tudi povratne informacije računalniško prilagajali s pomočjo algoritmov, v Predvidevali smo, da ima vsak učenec svoje Google Slide e- teoriji prinašajo zelo veliko prednosti, v praksi pa je iskren gradivo, kar mu daje možnost, da vnaša samoocene narejenih človeški stik, četudi preko spleta, še vedno nenadomestljiv. nalog in drugih opomb direktno v dokument, kar prihrani veliko časa. To daje tudi učitelju možnost, da sproti spremlja napredek učenca in predvsem oblikuje konstruktivne povratne informacije LITERATURA - dnevne, tedenske ali ob zaključku sklopa določene snovi, kar [1] Žagar, D. 2009. Psihologija za učitelje. Filozofska fakulteta. ključno poveča motivacijo učencev za delo. Ljubljana. Povratna informacija je sestavljena iz učenčeve uspešnosti pri delu (npr. št. pravilnih odgovorov), njegove 694 [2] Woolfolk, A. 2002. Pedagoška psihologija. Educy. [11] Clarke, A. 2008. E-learning skills. Palgrave Ljubljana. Macmillan.New York. [3] Marinič, A. 2015. Povezanost čustev in učenja: kako učitelji [12] Kokalj, R. 2003. Strateško orodje sodobne organizacije. zaznavajo pomen čustev za učenje (Diplomsko delo). Doba. Maribor. Univerza na Primorskem. Pedagoška fakulteta. Koper. [13] O’Regan, K. 2019. Emotion and e-learning. Online [4] Stephenson, J. 2002. Teaching & learning online: Learning. 7(3), 78–92. DOI= pedagogies for the new technologies. London. Kogan Page. https:/ pdfs.semanticscholar.org/6512/4ed7a152be5d49930 [5] Rosenblit S. 2005. »Distance education« and »e-learning«: eeb834d3c2c96bd9881.pdf Not the same thing. Higher Education. 49 (4). 467-493. [14] Cleveland-Innes, M. & Campbell, P. 2012. Emotional Springer. Israel. presence, learning, and the online learning environment. [6] Rashty, D. 2001. Traditional Learning vs. E-Learning. The International Review of Research in Open and DOI= Distributed Learning, 13(4), 269. https://rashty.com/articles/Traditional_Learning_vs_eLear DOI=https://doi.org/10.19173/irrodl.v13i4.1234 ning.pdf [15] Pekrun R., Linnenbrink-Garcia L. 2012. Academic [7] Neuhauser, C., 2002 . Learning Style and Effectiveness of Emotions and Student Engagement. In: Christenson S., Online and Face-to-Face Instruction. American Journal of Reschly A., Wylie C. (eds) Handbook of Research on Distance Education, 16(2), pp.99-113. Student Engagement. Springer, Boston, MA. DOI=https://doi.org/10.1007/978-1-4614-2018-7_12 [8] Sansone, C., Smith, J.L., Thoman, D. B., MacNamara, A. 2012. Regulating interest when learning online: Potential [16] ALICE: Adaptive Learning via Intuitive/Interactive, motivation and performance trade-offs. The Internet and Collaborative and Emotional systems. EU Union. DOI= Higher Education,Vol. 15 (3), 141-149. https:/ joinup.ec.europa.eu/collection/education-culture- and-sport/document/alice-adaptive-learning- [9] Khan, S., B., Jumani, N., B. 2012. e-Learning versus intuitiveinteractive-collaborative-and-emotional-systems- Traditional Learning in Pakistan. Asian Journal of alice Distance Education. Clarke, A. 2008. E-learning skills. Palgrave Macmillan.New York. Vol 10(1). 28-34. [17] Feidakis, M., Daradoumis, T., Caballé, S., & Conesa, J. DOI=https://www.academia.edu/3313733/e_Learning_ver 2012. Design of an emotion aware e-learning system. sus_Traditional_Learning_in_Pakistan. International Journal of Knowledge and Learning, 8(3/4), 219-238. DOI= https://doi.org/10.1504/ijkl.2012.051676 [10] Daniels, L. M. & Stupnisky, R. H. 2012. Not that different in theory: Discussing the control-value theory of emotions [18] Google Slides. DOI= in online learning environments. The Internet and Higher https://www.google.com/slides/about/ Education, 15(3), 222–226. DOI=https://doi.org/10.1016/j.iheduc.2012.04.002 695 Spremljanje srčnega utripa s pomočjo IKT pri predmetu šport Monitoring the heart rate with the help of ICT in P. E. Lessons Marina Tomić OŠ Milana Šuštaršiča Ljubljana Štembalova ulica 2a 1000 Ljubljana, Slovenija marina.tomic83@gmail.com POVZETEK Sodoben način poučevanja prav gotovo zajema tudi uporabo 1 UVOD informacijsko-komunikacijske tehnologije (IKT). To je način Živimo v obdobju, ko so družbene, gospodarske, izobraževalne poučevanja, kjer se uporabljajo vsa sodobna orodja in in vzgojne potrebe čedalje večje, zato je toliko bolj pomembna obvladovanje le-teh, je ena pomembnejših kompetenc 21. uvedba informacijsko-komunikacijske tehnologije (IKT) v vse stoletja. Uporaba IKT je ena izmed dodatnih možnosti učitelja za segmente našega življenja. Družbeni razvoj tako teži k razvijanju drugačen, bolj inovativen didaktičen pristop k poučevanju in razširjanju visoke tehnologije. Danes uporabljajo računalnike določenih vsebin. Inovativni pouk je način poučevanja, pri in druge informacijsko-komunikacijske tehnologije ljudje v vseh katerem učitelj učence usmerja, da le-ti z raziskovanjem, delovnih okoljih na vseh področjih. Tako je seveda pomembno ustvarjalnostjo in uporabo IKT pridejo do spoznanj o učni snovi in neizogibno IKT uvesti v čim večji meri tudi v predšolsko in in pri tem nadgrajujejo/izpopolnjujejo svoje znanje. V prispevku osnovnošolsko izobraževanje. Če se bo učence že v osnovni šoli je predstavljena uporaba IKT pri predmetu šport. Učenke so svoj navajalo na različne IKT, bodo le-ti kot odrasli lažje razvili srčni utrip spremljale s pomočjo merilca srčnega utripa, mobilne ustrezne veščine za prilagajanje na vse novosti. Zato je potrebno aplikacije in ročnega merjenja. izobraževanje otrok v vrtcih in osnovnih šolah prilagoditi času in prostoru, v katerem živijo, jih izobraževati in vzgajati tako, da KLJUČNE BESEDE bodo lahko obvladovali hiter razvoj tehnologije v družbi [1]. IKT, merilec srčnega utripa, šport, srčni utrip Spremembe, ki jih je s seboj prinesla IKT, niso zaobšle niti izobraževanja. Ross je že leta 1982 zapisal, da se izobraževalni ABSTRACT sistem spreminja skladno z družbenimi, zgodovinskimi in The modern way of teaching certainly includes the use of ekonomskimi dejavniki, ki vključujejo tudi tehnološke information and communication technology (ICT). Mastering spremembe. Tako je IKT v izobraževalni sistem prinesla številne the way of teaching, where all modern tools are used, is one of spremembe, ki jih morajo udeleženci znati izkoristiti, da bi bil the most important competencies of the 21st century. The use of njihov učinek optimalen. V slovenskih osnovnih šolah je bila ICT provides the teacher additional possibilities for a different, informacijska tehnologija prvič predstavljena v začetku more innovative didactic approach to teaching certain contents. osemdesetih let prejšnjega stoletja. Na nacionalni ravni se je Innovative teaching is a way of teaching in which the teacher načrtno začela uvajati šele v sredini devetdesetih let dvajsetega directs students to gain knowledge about the subject matter stoletja, s projektom RO – računalniško opismenjevanje, ki je za through research, creativity and the use of ICT, whilst upgrading začetek poskrbel za osnovno računalniško opremo in / improving their knowledge. The paper presents the use of ICT izobraževanje za uporabo le-te na slovenskih šolah. Cilj projekta in P.E. lessons. Pupils monitored their heart rate with the help of je bil izvesti široko računalniško izobraževanje za učitelje in a heart rate monitor, a mobile application and manual ravnatelje, opremiti vse osnovne in srednje šole z IKT in measurement. programsko opremo ter omogočiti raziskovanje in razvoj uporabe računalnikov v šolah, s tem pa ustvariti sodobnejši, KEYWORDS aktivnejši pouk ter sodobno vodenje in poslovanje šole [1]. ICT, heart rate sensors, sport, heart rate 2 KAJ JE INFROMACIJSKO- KOMUNIKACIJSKA TEHNOLOGIJA (IKT)? Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed Informacijsko-komunikacijska tehnologija (v nadaljevanju IKT) for profit or commercial advantage and that copies bear this notice and the full je skupen izraz različnih računalniških, informacijskih in citation on the first page. Copyrights for third-party components of this work must komunikacijskih naprav, ki so postale naš vsakdanji be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia spremljevalec [2]. Tehnološki napredek je zajel tudi področje © 2020 Copyright held by the owner/author(s). šolstva, zato so se bile šole primorane informatizirati. IKT je 696 postal nepogrešljiv pripomoček pri učenju in poučevanju. Glavni računalnik, omrežna računalniška postaja, LCD projektor, skener, cilji vključevanja IKT v pouk so informacijska pismenost, nove digitalna kamera, digitalni fotoaparat, interaktivna tabla … Pri spretnosti in bogatejše izkušnje. Za ustrezno in smiselno rabo predmetu šport lahko učitelji uporabijo različno opremo: IKT pri pouku je odgovoren usposobljen učitelj. Tehnologija prenosni računalnik, kamera, LCD projektor, merilci srčnega omogoča učiteljem, da pouk načrtujejo bolj učinkovito, od utripa … Skoraj bolj pomembno od poznavanja strojne opreme učencev pa zahteva, da so pri pouku aktivni in motivirani [3]. pa je, da pozna učitelj vrsto in način uporabe programske opreme, Enotne definicije, ki bi natančno opredelila IKT ni, vsem pa ki mu je na voljo in se uporablja za posamezne predmete. Prav je skupno to, da se v opredelitvi omenja beseda komunikacija. V tako je pomembno, da se učitelj sam, npr. na spletu, pozanima o literaturi je mogoče zaslediti več opredelitev IKT. možnih novih, boljših didaktičnih programih in predlaga nabavo le-teh, kar pa pomeni, da mora biti seznanjen z načini zagotavljanja ustrezne programske opreme in zato vključen v 3 UPORABA IKT PRI POUČEVANJU načrtovanje nabave nove opreme za uporabo IKT. Ob Računalnik oz. IKT danes že imata svoje mesto v našem poznavanju strojne in programske opreme, ki je na voljo, je izobraževalnem sistemu in poučevanju nasploh, v nekaterih pomembno načrtovanje za poučevanje predmeta. Tukaj je šolah bolj, v drugih manj uspešno. Veliko je govora o možnostih potrebno jasno razločevati med načrtovanjem vključevanja IKT sodobnejšega in kvalitetnejšega pouka in poučevanja, ki jih v pouk za dosego ciljev pri drugih predmetih in na drugi strani tehnologija omogoča, o možnostih prehoda od pouka, ki temelji med načrtovanjem razvijanja učenčevih sposobnosti na področju na pomnjenju velike količine podatkov, k reševanju praktičnih IKT. Učinkovita izraba IKT se bo tako odražala v izboljšanju problemov, ki zahtevajo od učenca kreativno mišljenje in konec poznavanja posameznega predmeta in tudi na učiteljevih koncev tudi takšno znanje. Pomembne so didaktične oblike in razlagah snovi. metode dela ter zavedanje, na kateri stopnji znanja so učenci in učitelji pri uporabi IKT pri pouku, da bi lahko učence miselno in 3.1 PREDNOSTI IN SLABOSTI IKT motivacijsko razgibali in se predvsem izognili morebitnim Tako kot vse stvari ima tudi uporaba IKT svoje prednosti in negativnim učinkom na učni načrt. Uporaba IKT pri pouku je ob slabosti. ustrezni opremi odvisna seveda od učitelja. Učiteljevi odzivi na Himmelsbach [4] je v svojem članku predstavil pet prednosti različne pristope k uporabi IKT so odvisni namreč od njihovega in pet slabosti uporabe IKT pri pouku; individualnega znanja, lastnega prepričanja in pristopa k poučevanju (npr. občasna uporaba projektorja pripelje do hitre Prednosti uporabe IKT pri pouku navade na takšen način dela). Če učitelj pogosto uporablja - Uporaba IKT omogoča več eksperimentiranja in takojšnjo določeno opremo ali pristop, se le-ta izkaže za uspešno izhodišče pridobitev povratnih informacij. pri uvajanju bolj učinkovitega vključevanja IKT v pouk. Zato je zelo pomembna učiteljeva samozavest in prepričanje v lastne - Uporaba IKT pomaga pri vključevanju vseh učencev sposobnosti na področju uporabe IKT. Bolj samozavestni in (polna udeležba). sposobni učitelji so hitro pripravljeni sprejeti nove učne pristope - Pouk z uporabo IKT pripomočkov je bolj zabaven in (npr. predstavitev s pomočjo računalnika in projektorja), medtem učinkovit. ko manj samozavestni redkeje pristopijo k uporabi IKT. Učitelji - Z uporabo IKT v razredu imajo učenci takojšen dostop do z bolje razvitimi osebnimi sposobnostmi za uporabo IKT tako aktualnih informacij, ki lahko dopolnijo njihovo učno seveda lažje razumejo potencial, ki ga nudi IKT, in so tudi bolj izkušnjo. odločni za uporabo pri poučevanju. In prav zato je pomembna usposobljenost učiteljev za uporabo računalnika oz. IKT. Da - Živimo v digitalnem svetu, zato je uporaba IKT postala učitelji lažje in bolj jasno odločajo o tem, kako in kdaj jim lahko življenjska veščina. IKT pomaga pri poučevanju, je pomembno, da poznajo strojno in programsko opremo, ki jim je v šoli na voljo za uporabo. Za Slabosti uporabe IKT pri pouku učinkovito izrabo IKT je zato zelo pomembno, da poznamo - IKT je lahko v učilnici moteča. razpoložljivo strojno in programsko opremo [1]. - Uporaba IKT lahko zmanjša socialno interakcijo učencev. Tišler [1] v svojem delu pravi, da šole v svojih učnih načrtih po navadi ne predvidevajo, kako IKT vključiti v pouk, saj se po - Uporaba IKT naprav lahko spodbuja goljufanje v razredu navadi načrtuje le razvijanje učenčevih sposobnosti za rabo IKT in pri preverjanju znanja. pri predmetu računalništva. Vzrok temu je lahko pomanjkanje - Učenci nimajo enakega dostopa do tehnoloških virov. opreme za uporabo IKT ali premajhna pripravljenost za uporabo - Viri, ki jih učenci najdejo na spletu, velikokrat niso le-te. Najbolj uporabne se posebne učilnice, opremljene z več zanesljivi. računalniki (računalniške učilnice), na katerih lahko hkrati delajo vsi učenci v učilnici. Zato je seveda ustrezna opremljenost šolskih prostorov nujna, saj lahko le tako učitelji učinkoviteje 4 SMERNICE ZA UPORABO IKT PRI načrtujejo in uporabljajo IKT na različnih predmetnih področjih. PREDMETU ŠPORT Vsa oprema, ki je na šoli, pa nujno ne zadošča za smotrno in kvalitetno uporabo računalnika pri pouku, zato je pomembno, da Športna vzgoja/predmet šport je učni predmet, pri katerem se pri pouku ne uporablja zastarele opreme, ki prepogosto zataji, učitelj, poleg gibalnega znanja in sprostitve učencev zasleduje, kar lahko kar hitro pripelje do zastoja učne ure. Med strojno tudi veliko število vzgojnih ciljev in ciljev, vezanih na razvoj opremo lahko štejemo naslednje: osebni računalnik, prenosni temeljnih gibalnih sposobnosti oz. gibalne učinkovitosti 697 učencev. To je predmet, pri katerem moramo znati izvesti tako utripanje žil opazi s prostim očesom kot nihanje kože. Temu dejavnost učinkovito in varno, da bomo tudi kasneje v življenju utripanju pravimo srčni utrip ali pulz. Normalen srčni utrip to lahko redno in varno počeli. Športni pedagog uporablja IKT v odraslega netreniranega človeka (pri otrocih ta podatek ni procesu poučevanja z namenom, da učno vsebino ali cilj lažje in merodajen) je od 60 do 100 udarcev na minuto čez dan, medtem bolje ponazori, osmisli, utemelji, izboljša razumevanje, izboljša ko je ponoči veliko nižji (lahko tudi le okoli 40 utr./min.). Na eni kakovost demonstracije, spodbudi učence k razmišljanju in strani imamo maksimalni srčni utrip (maksimalno število utripov dejavnosti, pripomore h kakovosti procesa učenja. IKT je pri tem v minuti), na katerega načeloma ne moremo kaj dosti vplivati, saj pripomoček oz. orodje, ki pomaga pri pridobivanju znanja [5]. je slednji odvisen predvsem od starosti in dednih zasnov. Mlado Učni načrt predmeta šport uporabo informacijsko srce lahko doseže tudi do 200 udarcev v minuti, z leti ta vrednost komunikacijske tehnologije navaja v Splošnih izhodiščih, ki jim pada. Na drugi strani imamo srčni utrip v mirovanju, na katerega sledi učitelj športa. lahko vplivamo in ga s pomočjo treningov dolgoročno Markun Puhan [5] navaja, da je IKT v tretjem vzgojno znižujemo. Srce utripa v mirovanju počasi, med obremenitvijo izobraževalnem obdobju omenjena pri naslednjih učnih sklopih: pa se pulz pospeši, da zadosti potrebi po večjem pretoku, - Pri učnem sklopu Splošna kondicijska priprava: predvsem skozi obremenjene mišice. Med obremenitvijo – Ugotavljanje zakonitosti športne vadbe - izbor nalog, telesno pa tudi psihično, se utrip pospeši, v mladosti bolj kot v intenzivnost vadbe in trajanje obremenitve glede na starosti. Utrip lahko spremenijo nekatera fiziološka stanja (npr. različne cilje, tudi z uporabo IKT (merilniki srčne nosečnost), pa tudi bolezni. Najpomembnejšo fiziološko frekvence, porabe energije, števila korakov). spremembo utripa dosežemo z redno telesno aktivnostjo, ki - Pri učnem sklopu Ugotavljanje in spremljanje gibalnih lahko precej upočasni pulz, tudi do vrednosti pod 40/min v sposobnosti ter telesnih značilnosti: Pri obravnavanju mirovanju. Oseba, ki ima tako nizek pulz v mirovanju, ima veliko značilnosti biološkega razvoja učenci za spremljanje rezervo, ki jo lahko izrabi med obremenitvijo [6]. svojega telesnega in gibalnega razvoja ter vrednotenje sprememb uporabljajo tudi informacijsko-komunikacijske 6 PRIMER SPREMLJANJA SRČNEGA tehnologije. UTRIPA S POMOČJO IKT PRI - Pri Splošnih teoretičnih vsebinah: Odzivanje srčno-žilnega PREDMETU ŠPORT in dihalnega sistema na povečan napor pri športni vadbi (merjenje srčnega utripa… načrtovanje vadbe, pomen Spremljanje srčnega utripa s pomočjo IKT smo izvedli v 6. največje porabe kisika). razredu pri rednih urah predmeta šport v sklopu splošne kondicijske priprave. Pri uri je sodelovalo 12 učenk. 4.1 DODATNI DIDAKTIČNI NAPOTKI ZA Z navodili in opisom poteka ure/meritev so bile učenke UPORABO IKT PRI PREDMETU ŠPORT seznanjene že na prejšnji uri. Vsaka je meritve izvajala na način, ki ji je bil določen: Markun Puhan [5] navaja naslednje dodatne didaktične napotke • 1 učenka - s pomočjo ure Polar V800, ki omogoča za uporabo IKT pri predmetu šport: merjenje srčnega utripa, Pomembno je, da si učitelj prej odgovori na vprašanje kaj želi • 5 učenk - ročno, na notranji strani zapestja, proti palcu pri določeni uri z učenci doseči, šele nato pa kaj bo delal in katere (a. radialis) - 30 sekund in pripomočke bo a to uporabil (rekvizite, delovne liste, IKT) Učitelj naj presodi kdaj in katero sodobno tehnologijo bo • 6 učenk - s pomočjo mobilne aplikacije Srčni Utrip uporabil v procesu poučevanja; IKT sama po sebi namreč nima Plus dodane vrednosti. Je le orodje, kot svinčnik, zvezek, žoga, Meritve srčnega utripa so se izvajale po naslednjem blazina… ki učencem/dijakom pomaga pri učenju) zaporedju: Učenci so lahko na področju rokovanja z IKT znajo več od • srčni utrip v mirovanju (na začetku ure so se vse učitelja. V tem primeru naj jim učitelj omogoči, da izkažejo svoje učenke za 5 minut usedle na klop ter povsem umirile), znanje, sam pa naj bo pozoren na cilje, za katere želi, da jih • srčni utrip po ogrevanju, učenci usvojijo. • med vadbo in S pomočjo IKT lahko učenec ali dijak sprejema informacije • na koncu šolske ure v mirovanju (5 minut sedenja). vzporedno po več kanalih npr. poleg slušnega in kinestetičnega Izmerjene rezultate so si učenke sproti zapisovale na osebni še po vidnem kanalu, kar predstavlja pomembno dodano karton. Rezultate smo na naslednji uri analizirali in primerjali vrednost. Informacije in povratne informacije so tako med seboj. Na prenosnem računalniku smo si ogledali tudi natančnejše, razumljivejše in zato učinkovitejše. spreminjanje srčnega utripa pri učenki, ki je celo šolsko uro nosila uro Polar V800 (Slika 1). 5 SRČNI UTRIP Srce se med svojim delovanjem razteza in krči. Pri raztezanju se napolni s krvjo, pri krčenju pa kri potisne po žilah. Pri tem se kri iz njegove leve polovice pretoči skozi aorto v glavne arterije. Ker je pretok krvi pri krčenju srca velik, se v arterijskih žilah (ali žilah utripalnicah) zazna pulzni val, ki se otipa s prstnimi blazinicami, ko se žilo pritisne ob tršo podlago (kost ali mišico). Včasih se Slika 1. Spreminjanje srčnega utripa pri učenki 698 7 SKLEP [2] Zuljan, A. (2004). Za kakovostnejša družboslovna znanja: Uporaba IKT je sigurno ena izmed dodatnih možnosti učitelja za didaktični in znanstveni prispevki. Ljubljana: Fakulteta za drugačen oz. bolj inovativen didaktičen pristop k poučevanju družbene vede. določenih vsebin. Inovativni pouk je način poučevanja, pri [3] Bokal, Ž. (2017). Uporaba informacijsko komunikacijske katerem učitelj učence usmerja, da le-ti z raziskovanjem, tehnologije v družboslovju od 1. do 5. razreda. (Magistrsko ustvarjalnostjo in uporabo IKT pridejo do spoznanj o učni snovi delo, Univerza v Ljubljani, Pedagoška fakulteta). in pri tem nadgrajujejo/izpopolnjujejo svoje znanje. Učitelj mora Pridobljeno iz http://pefprints.pef.uni-lj.si/4791/ biti pri uporabi IKT pozoren, da njegovo vnašanje v pouk ni [4] Himmelsbach, V. (2019). 6 Pros & Cons of Technology in prekomerno in le takrat, kadar je to smiselno. Uporaba IKT naj the Classroom in 2019. Top Hat. Pridobljeno iz ne bo za vsako ceno in vsekakor ne namesto praktičnega dela https://tophat.com/blog/6-pros-cons-technology- pouka. Predvsem naj bodo sredstva IKT praktičnemu pouku classroom/ športne vzgoje v pomoč in dopolnitev. [5] Markun Puhan, Nives (2016). Smernice za uporabo IKT pri predmetu šport/športna vzgoja (delovna različica), LITERATURA Zavod RS za šolstvo, spletni vir: https://www.zrss.si/digitalnaknjiznica/smernice-ikt-sport/ [1] 1Tišler, T. (2006). Spodbujanje uporabe informacijsko- [6] Logar, K. (2010). Srčni utrip v mirovanju (SUVM). komunikacijske tehnologije na osnovni šoli. Vodenje za Tekaški forum. Pridobljeno iz spodbujanje informacijsko-komunikacijske tehnologije na http://www.tekaskiforum.net/clanki/2010/10/srcni-utrip- šolah. 10 - 21. v-mirovanju-suvm/?cbg_tz=-60 699 Pouk angleščine na daljavo s spletnim orodjem BookWidgets Distance English language teaching using the BookWidgets online tool Aleksandar Tonić Osnovna šola Toma Brejca Šutna 39 1241 Kamnik, Slovenija sandi.tonic@gmail.com POVZETEK with their students and give them feedback on their work. In conclusion, the paper focuses on advantages and disadvantages Leto 2020 je z epidemijo SARS-CoV-2 šolskemu sistemu v of using BookWidgets in the form of a short SWOT analysis. Sloveniji prineslo situacijo brez precendensa: karanteno, zaprtje izobraževalnih ustanov in pouk na daljavo. Zlasti osnovne šole KEYWORDS so se morale zato čez noč prilagoditi novim razmeram in pripraviti vse potrebno, da je pouk na daljavo stekel karseda Distance learning, ICT, BookWidgets, EFL nemoteno navkljub številnim težavam, ki so se ob tem pokazale. Učitelji so morali prilagoditi metode dela in v priprave na pouk 1 UVOD integrirati spletna orodja, ki bi omogočila tako napredek učencev pri doseganju učnih ciljev, kot zbiranje dokazov o učenju, dajanje Šolsko leto 2019/20 je poučevanju v Sloveniji postreglo z povratne informacije in komunikacijo z učenci. Prispevek velikim izzivom. Ko je decembra 2019 v kitajskem mestu Wuhan opisuje primer pouka angleščine na daljavo z uporabo prišlo do izbruha okužb z virusom SARS-CoV-2 (v nadaljevanju: Bookwidgets, spletnega orodja, ki uri pouka da interaktivno noto koronavirus), ki se je hitro razširil onkraj meja Kitajske, je bilo in učitelja opolnomoči, da ustvari interaktivne naloge, jih deli z le vprašanje časa, kdaj bo prvi primer okužbe zabeležila tudi učenci in jim po reševanju omogoči povratno informacijo. V Slovenija. A posledic – tudi za slovensko šolstvo – v takšni meri, zaključku se prispevek osredotoča na analizo prednosti in kot so se pojavile v tednih po prvih zabeleženih okužbah na naših slabosti orodja BookWidgets v smislu SWOT analize. tleh, verjetno številni niso pričakovali. V obdobju od 4. marca 2020, ko je bila slovenska javnost KLJUČNE BESEDE obveščena o prvem zabeleženem primeru koronavirusa, ni Pouk na daljavo, IKT, BookWidgets, tuji jezik angleščina preteklo veliko časa, ko je bilo potrebno slovenski izobraževalni sistem tako rekoč čez noč postaviti na glavo na način, da je še ABSTRACT vedno ostal – vsaj razmeroma – funkcionalen. Tako je bila v With the outbreak of the SARS-CoV-2 epidemic, the year 2020 četrtek, 12. marca 2020, ob 18. uri razglašena epidemija ter s tem caused an unprecedented situation in the Slovenian school naznanilo, da se s 16. marcem 2020 zapirajo vse vzgojno- system: quarantine, educational institution lockdown and izobraževalne institucije v državi. Takoj v petek in tekom distance learning. Primary schools in particular had to adapt to vikenda, ki je sledil, so predvsem številne šole intenzivno iskale the new situation overnight and measures had to be taken to načine, kako s poukom kar najbolj optimalno nadaljevati od 16. ensure the learning processes would continue as seamlessly as marca 2020 dalje. To je bil začetek obdobja brez precedensa: possible in spite of the many problems that arose from the pouk na daljavo za vse vzgojno-izobraževalne ustanove. situation. Teachers had to make a shift in their methods of teaching and incorporate in their lesson plans online tools that 2 POUK NA DALJAVO – SODOBNI IZZIV would allow for collecting evidence of learning, giving students feedback and communicating with them. This paper presents a 2.1 Organizacija pouka na daljavo z danes na case of English language distance learning by means of jutri: osnovnošolski primer BookWidgets, an online tool, that makes learning interactive and empowers the teacher to create interactive activities, share them Po četrtkovi večerni razglasitvi epidemije je bila v Osnovni šoli Toma Brejca Kamnik takoj naslednji dan aktivirana delovna skupina za načrtovanje pouka na daljavo. Člani delovne skupine smo intenzivno premlevali možnosti, kako učencem še naprej Permission to make digital or hard copies of part or all of this work for personal or zagotoviti obiskovanje pouka in kakovostno izobraževanje. classroom use is granted without fee provided that copies are not made or distributed Hkrati smo moči uperili v to, kako o aktualnem dogajanju hitro for profit or commercial advantage and that copies bear this notice and the full in učinkovito obvestiti ključne deležnike vzgojno-izobraževalnih citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). procesov na šoli: učitelje, učence in njihove starše. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 700 Medtem ko so učiteljice 1. in 2. razreda sklenile, da se bodo Sodobni pristopi kot ključno v procesu poučevanja na daljavo za izvajanje aktivnosti v okviru pouka na daljavo povezale zahtevajo od učitelja več časa za kvalitetno načrtovanje pouka. neposredno z učenci oz. njihovimi starši, smo v delovni skupini Barton [2] povzema, da neuspeh pri učencih izvira tudi iz tega, po tehtnem premisleku sklenili, da bomo vzpostavili da »skrbijo za učne stile, ne pa tudi za učence in učenje samo« izobraževalno okolje v oblaku na platformi GoogleDocs. Za ter izpostavi, da se je potrebno osredotočiti na personalizirano učence od 3.–9. razreda smo pripravili dostop do delovnih map učenje. »Vsi učenci morajo vedeti, zakaj in kako se učijo, in biti in se z učiteljskim zborom dogovorili, da učitelji v mape nalagajo opolnomočeni, da vzamejo učenje v svoje roke.« gradiva v obliki pdf datotek en dan vnaprej. Načrtovanje pouka poteka tako na zavedni kot na nezavedni V šolskih dneh, ki so sledili, izzivov za učitelje ni manjkalo. ravni, pri čemer mora učitelj še posebej upoštevati: Pri pouku na daljavo smo se srečevali s težavami, ki jih zaradi • znanja, ki so pomembna za učence, hitre spremembe načina izvajanja pouka ni bilo možno v celoti • jasno postavljene cilje, ki naj jih učenci usvojijo, predvideti vnaprej, med drugim: • Kako pomagati učencem brez ustrezne IKT opreme? • konkretno začrtane poti do zastavljenih ciljev, • Kako pomagati učencem s slabo internetno povezavo? • nabor dejavnosti, ki jih bo implementiral v pouk ter frekvenco implementacije le-teh, • Kako pomagati učencem, ki pri učenju na daljavo zaradi različnih razlogov niso imeli učinkovite • konkretno, nedvoumno in jedrnato podajanje navodil podpore domačega okolja? za izvedbo izbranih dejavnosti, • Kako vzpostaviti enostavno, hitro, predvsem pa • načine diferenciacije pri pouku na daljavo, učinkovito komunikacijo z učenci? • načine pridobivanja in vzdrževanja pozornosti • Kako vzpostaviti stik z neodzivnimi učenci in jih učencev, vzpodbuditi k delu? • vzpostavitev stika z učenci, ki spodbuja dobro počutje • Kako učinkovito pomagati učencem s posebnimi učencev in motivira za delo, potrebami? • pridobivanje dokazov o učenju in posledično • Kako motivirati za delo šibkejše učence? spremljanje napredka učencev, • Kako diferencirati pouk na daljavo tako, da so • vzpodbujanje sodelovalnega učenja in medvrstniške dejavnosti v izziv tudi zmožnejšim učencem? pomoči na daljavo, • Kako izbrati aktivnosti, ki naredijo pouk privlačen in • načine za kvalitetno preverjanje in ocenjevanje znanja. zanimiv? Poleg tega je, podobno kot pri klasičnem pouku, tudi pri • Kako učencem nuditi dobro razlago nove snovi? pouku na daljavo pomembno, da učencem jasno opredelimo namen učenja in s tem pri njih dvignemo raven zavesti o tem, kaj Pouk, ki je v celoti podprt z IKT in v katerem ni neposrednega in zakaj se učijo ter kdaj so pri učenju uspešni (kriteriji fizične prisotnosti učitelja in učencev, je tako čez noč zahteval uspešnosti). Prav ta dvig zavesti, t. j. ko učenci vedo, kdaj nekaj veliko mero iznajdljivosti v IKT segmentu sodobnih pristopov v znajo, je lahko pri njih ključen motivacijski dejavnik. poučevanju. 2.2 Sodobni pristopi v poučevanju angleščine in 3 SPLETNA ORODJA IN POUK NA IKT DALJAVO V času pouka na daljavo smo se učitelji ukvarjali s skupno dilemo: na spletu obstaja nebroj idej, aplikacij in digitalnih 3.1 Morje možnosti gradiv za delo na daljavo; toda kako za svoje skupine učencev Z uvedbo pouka na daljavo smo učitelji ne glede na pretekle izbrati najučinkovitejše? Takšne, ki bodo učinkovito razvijale izkušnje bili primorani razmišljati o uvedbi novih načinov dela z jezikovne zmožnosti in hkrati dopuščale povratne informacije v učenci. Številni smo se lotili raziskovanja raznoraznih spletnih smeri učitelj–učenec in obratno. Vzporedno s tem smo iskali orodij, ki omogočajo bodisi uporabo že pripravljenih gradiv, načine, kako iz učnih načrtov izluščiti in prilagoditi bistvene bodisi izdelavo novih, hkrati pa – kar smo hitro ugotovili, da je vsebine tako, da bodo učenci pri pouku na daljavo uspešni nujno – tudi neko obliko komunikacijskega kanala z učenci, skladno s svojimi zmožnostmi in bodo napredovali? Dodaten preko katerega smo preverjali, ali učenci opravljajo naloge in izziv je hkrati bil ugotavljanje in spremljanje (ne)napredka kako uspešno. posameznega učenca? Razvoj IKT sodobnemu učitelju ponuja številna didaktična Učni načrt za angleščino [1] opredeljuje IKT kot pomemben spletna orodja, mnoga od teh z integriranim formativnim podporni element pri pouku angleščine, saj učitelju »omogoča spremljanjem napredka učencev. Učitelji (in delno tudi učenci) uvajanje raznolikih oblik in metod dela v pouk ter pripravo in imamo v bogatem naboru teh orodij med drugimi na voljo npr.: prilagoditev besedil, nalog in drugih gradiv za doseganje • Wordwall (spletni kvizi na igriv način), različnih ciljev,« učenci pa ob IKT podpori radi sodelujejo in se lotevajo nalog, kar je pomemben motivacijski element. IKT pri • Kahoot (spletni kviz s točkovanjem in možnostjo pouku angleščine med drugim spodbuja sporazumevalno in časovne omejitve reševanja), medkulturno zmožnost, splošno razgledanost in sodelovalno • Socrative (spletni kvizi), ustvarjalnost. 701 • ActivePresenter (orodje za pripravo razlage snovi za lahko preveri svoj dosežek. Učitelj tako prihrani pri času, ki bi učence), ga sicer v klasični situaciji v razredu porabil za pregled • Padlet (spletna oglasna deska, npr. za objavo izdelkov pravilnosti rešitev nalog. učencev), V ozadju BW učitelju ponuja možnost spremljave napredka učencev v realnem času (angl. realtime tracking) ne glede na to, • Jamboard (razlaga snovi s pomočjo spletne table), ali učenci delajo na daljavo ali v šoli. Tako lahko učitelj na eni • MovieMaker (orodje za montažo video posnetkov), strani hitro identificira učence, ki potrebujejo dodatno vodenje ali pomoč, na drugi strani pa tudi tiste, ki morda potrebujejo • Interactive Worksheets (orodje za predelavo klasičnih dodatne izzive. učnih listov v interaktivno obliko), Ker se sodobni učenci večinoma že v domačem okolju • GoFormative (izdelava nalog za učence na osnovi pogosto srečujejo z uporabo IKT naprav, jih delo z BW – za povratne informacije in formativnega spremljanja), razliko od klasičnih metod in oblik dela – posledično še dodatno motivira. • Canva (orodje za pripravo vizualnih gradiv, npr. plakatov), 4.1 Prijava v orodje BW • BookWidgets (orodje za pripravo raznovrstnih Pred pričetkom dela v BW se mora uporabnik prijaviti na spletnih vaj z možnostjo spremljanja napredka in spletnem naslovu https://www.bookwidgets.com/. To lahko stori neposredne povratne informacije učencu), tako, da ustvari račun ali se prijavi z že obstoječim računom, npr. • okolja v oblaku kot so GoogleDocs, MS Office 365 idr. Googlovim ali Microsoftovim (Slika 1). 3.2 Prava izbira? Precej večji izziv kot samo iskanje, raziskovanje in preizkušanje orodij učitelju predstavlja odločitev o uporabi posameznih orodij za svoje skupine učencev. Učitelj na osnovi izkušenj in poznavanja skupin svojih učencev ter na osnovi karakteristik posameznikov v skupinah presodi: • Katera orodja so za učence glede na značilnosti skupine (starostna stopnja, predhodna znanja uporabe IKT, ipd.) primerna? • Kdaj v učnem procesu bodo posamezna izbrana orodja prišla v poštev (npr. ugotavljanje predznanja, obravnava nove snovi, preverjanje znanja, ocenjevanje znanja ipd.)? Slika 1. Okno za prijavo v orodje BW. • Kako pogosto bodo posamezna orodja uporabljena, da se učni proces z njimi ne zasiti in bi posledično pri učencih upadla motivacija za delo? Po prvi prijavi učitelj izbere svojo vlogo (npr. OŠ, SŠ, višješolsko izobraževanje), orodje pa ga nato vodi skozi Uvajanje IKT v pouk zahteva tudi tehten premislek o enostaven postopek izdelave gradiva. V meniju Podpora in pedagogiki 1:1. Ta zahteva »temeljito načrtovanje in zavedanje, navodila (angl. Support & Tutorials) so uporabniku tudi kasneje da ne gre za tehnologijo, ampak za spremembo pedagoške na voljo dodatne razlage, kako uspešno pripraviti gradiva za paradigme. Ena od poti, kako uresničiti novo pedagoško učence (Slika 2). Začetno 30-dnevno obdobje uporabe BW je paradigmo, je prav gotovo smiselno didaktično vključevanje brezplačno, kasneje pa je uporaba plačljiva. sodobnih tehnologij v poučevanje, učenje in vrednotenje.« [3] V času izvajanja pouka na daljavo je bila ena od odkritih možnosti za spremljanje napredka učencev spletno orodje BookWidgets. V nadaljevanju prispevka je predstavljen primer uporabe tega orodja pri pouku angleščine na daljavo v 5. in 6. razredu. 4 BOOKWIDGETS BookWidgets (v nadaljevanju: BW) je v angleškem jeziku zasnovano spletno orodje, ki uri pouka da interaktivno noto. Učitelju omogoča, da s pomočjo več kot 40 predlog ustvari interaktivne naloge v smislu vaj, kvizov, iger ipd. in jih deli z Slika 2. Podpora uporabniku v orodju BW. učenci, ki jih nato rešijo na svojih elektronskih napravah (npr. tablica, telefon, računalnik, iBooks). 4.2 Izbira gradiva Nadalje BW učencem lahko dá takojšnjo povratno Delo z orodjem BW je zelo intuitivno, pospremljeno s primeri informacijo o njihovem dosežku in napredku, saj je preverjanje rabe in sprotnimi napotki. Učitelj najprej izbere izdelavo novega rešitev številnih nalog lahko prednastavljena – en klik in učenec 702 gradiva (angl. widget). Pri tem lahko izbira med različnimi • naloga slikovnega odgovora (npr. učenec na vprašanje predlogami (Slika 3). Predloge so pregledno razdeljene v odgovori s sliko, ki jo posname s svojo napravo), skupine: • naloga povezovanja (npr. povezovanje besed ali • preverjanje (in ocenjevanje), povedi, povezovanje besed in slik ipd.), • igre, • naloga razvrščanja besed ali slik v ustrezne skupine. • slike in videoposnetki, • predloge za področje matematike, • umeščanje zunanjih aplikacij (npr. pdf datoteka, GoogleMaps, iskalnik Wikipedia idr.), • razno. Po izbiri vrste gradiva učitelj začne z vnosom navodil za delo in nalog. Za iztočnico lahko uporabi klasični učni list in ga prilagodi s pomočjo orodja BW. V nadaljevanju so predstavljeni nekateri primeri gradiv. Slika 4. Nekateri tipi nalog v orodju BW. Vsaki nalogi lahko po želji dodamo tudi slikovno ali zvočno predlogo, kar je pri pouku angleščine v osnovni šoli pogosto zelo uporabno, če ne celo nujno. V nadaljevanju so predstavljeni trije postopki priprave nalog, ki so bile uporabljene v času pouka na daljavo za učence 5. in 6. Slika 3. Del predlog za delo z BW. razreda. 4.3 Primeri BW gradiv PRIMER 1: Slušna naloga z dopolnjevanjem besedila povzeta po učbeniškem gradivu Touchstone 6 (6. razred) Za izdelavo BW gradiv najprej izberemo polje Create a widget. Vnos navodila ( Question): Nato med predlogami izberemo želeno možnost in v meniju, ki ga orodje odpre, izberemo Questions. Da dodamo navodila za Oglej si sliko in besedilo. Nato poslušaj (1-2x) telefonski reševanje oz. posamezna vprašanja izberemo možnost Add pogovor in ga dopolni. Povleci ustrezne besede na ustrezna question (Slika 4), nakar lahko izbiramo med različnimi tipi mesta. nalog, npr.: Vnos besedila ( Text) – pri vnosu besedila z oglatimi oklepaji • osnovno prosto besedilo (če npr. od učenca zahtevamo, <<>> označimo nabor besed, ki jih učenci lahko vstavijo v da si neko besedilo samo prebere), besedilo. Po želji dodamo še distraktorje: • naloga izbirnega tipa, kjer je pravilen samo en odgovor (angl. multiple choice), MAKING SUGGESTIONS • naloga z več možnimi pravilnimi odgovori, Mr Robinson: Hello 862330. • naloga, kjer učenec vpiše svoj odgovor na kratko (npr. Jill: Good <>, Mr Robinson. This is Jill kratki odgovori na vprašanja), <>. Can I speak to Roy? • naloga, kjer učenec vpiše svoj odgovor na dolgo (npr. Mr Robinson: Yes. Just a <>. Roy! Jill's on the krajši spis, pismo ipd.), <>. • naloga dopolnjevanja vrzeli (angl. gap fill), Jill: Hi, Roy, it's Jill. • naloga vnosa danih besed v besedilo (angl. drag and Roy: Hi, Jill. drop), Jill: What are <> doing? • naloga izbire rešitev v tabeli (npr. bralna naloga po principu drži / ne drži / ni v besedilu), Roy: I'm drawing <> for the School Festival. • naloga označevanja delov slike, Jill: Oh, I see. • naloga avdio odgovora (npr. učenec na vprašanje Roy: And you? odgovori ustno tako, da svoj odgovor posname s svojo Jill: I'm <> a magazine. There's a new film on napravo), at the Odeon <>. Let's see it together. 703 Roy: Well, what is it? Jill: It's the new James Bond. Roy: Oh, I'd <> to go, but not today. I really can't <> the time. Why don't we go on <>? Jill: All right. <> go on Sunday then. Vnos zvočnega posnetka ( Audio) – dodamo zvočni posnetek (npr. v formatu mp3), ki spremlja nalogo. Vnos slikovnega gradiva ( Image) – dodamo sliko (npr. v formatu jpg), ki spremlja nalogo. Slika 6. Naloga besedišča in pravopisa – učenčev Učenčev pogled: že med izdelavo naloge ali po vnosu vseh pogled. elementov naloge lahko s klikom na Preview preverimo, kakšen bo učenčev pogled (Slika 5). PRIMER 3: Slovnična naloga, Present Simple, povzeto po učnem gradivu Grammar Two (6. razred) Vnos navodila ( Question): Dopolni besedilo o sinjih kitih z glagoli v oklepajih v obliki PRESENT SIMPLE. Razmisli: kdaj glagol dobi končnico - s? Pazi tudi na pravopis. Vnos besedila ( Text): The blue whale <> (be) the largest animal in the world. It <> (weigh) 150 tonnes and <> (grow) 30 metres long. Baby blue whales <> (drink) 600 litres of their mother's milk every day. Blue whales <> (live) in the sea, but they <> (come) to the surface every 15 minutes. When a whale <> (breathe), it <> (blow) Slika 5. Slušna naloga z dopolnjevanjem besedila – water into the air. There <> (be) 83 kinds of whale. učenčev pogled. They all <> (have) different songs. Some people <> (hunt) whales to get meat and oil. PRIMER 2: Naloga besedišča in pravopisa – dopolnjevanje praznih polj z ustreznimi besedami na slikovni podlagi Vnos slikovnega gradiva ( Image) – dodamo sliko, ki učbeniškega gradiva My Sails II NEW (5. razred) spremlja nalogo. Vnos navodila ( Question): Učenčev pogled (Slika 7). V okvirčke vpiši manjkajoče besede za dele teles teh živali: Vnos slikovne podlage ( Background Picture) – dodamo ustrezno slikovno podlago. Vnos polj in pripadajočih rešitev ( Input Fields) – vpišemo iskane besede (kjer je več možnih rešitev, to označimo z znakom ##) in določimo pozicijo praznega polja na slikovni podlagi: beak Slika 7. Slovnična naloga, Present Simple – učenčev whisker##whiskers pogled. wing##wings 4.4 Vključitev učencev mane Pred samo vključitvijo učencev v učni proces z orodjem BW, lahko učitelj izbere še nekatere druge možnosti kot so: paw##paws • lokalizacija, t. j. prevod določenih delov gradiva, Učenčev pogled (Slika 6). • pošiljanje rešitev učitelju (da ali ne), • časovna omejitev reševanja, • skrivanje prikaza rešitev po zaključku reševanja, 704 • kratka povratna informacija učencu po zaključku reševanja idr. Ko je gradivo pripravljeno, ga učitelj lahko deli tako, da izbere možnost Share, ki omogoča: • delitev gradiva z učenci preko spletne povezave, • delitev gradiva z učenci preko QR kode in • tudi delitev gradiva z drugimi učitelji uporabniki orodja BW tako, da učitelj prejemnik lahko prejeto gradivo po svoje prilagodi in ga preko svojega računa deli s svojimi učenci. Slika 9. Pregled uspešnosti reševanja po učencih. Učenci, ki se udeležijo pri delu s pripravljenim gradivom, rešujejo naloge na svojih napravah in po reševanju lahko prejmejo takojšnjo povratno informacijo tako, da se prikaže 5 REFLEKSIJA njihov dosežek in pravilne rešitve. Če učitelj želi, lahko to možnost tudi onemogoči (npr. v izogib temu, da bi učenci, ki so Vsaka metoda in oblika dela, ki jo pri pouku na novo vpeljujemo, naloge že rešili, rešitve nemara posredovali tistim, ki k reševanju si zasluži temeljito refleksijo, saj le tako lahko ugotovimo, ali je nalog še niso pristopili). Pri nalogah, kjer to ni možno (npr. daljši bil nov način dela učinkovit ter kako ga lahko še izboljšamo. To pisni odgovori, naloge, pri katerih ni možno vnaprej predvideti je še toliko bolj pomembno, ko gre za pouk na daljavo v enoznačnih odgovorov ipd.) pa učitelj lahko v orodju nastavi razmerah, kot so se v Sloveniji pojavile v obdobju marec–junij možnost, da učenci posredujejo svojo rešitev, pri čemer dodajo 2020. Refleksijo lahko izvedemo podobno kot podjetja, ki se pri svoj e-poštni naslov. Ko učitelj pregleda njihovo rešitev in jo strateškem načrtovanju poslovanja rada poslužujejo t. i. SWOT točkuje, učencu preko e-pošte lahko poda povratno informacijo. analiz (S = strengths, slov. prednosti; W = weaknesses, slov. slabosti; O = opportunities, slov. priložnosti; T = threats, slov. 4.5 Povratne informacije in spremljanje nevarnosti). Razmislek o teh kategorijah je nanizan v Tabeli 1. napredka učencev Tabela 1. Razmislek o orodju BW v SWOT obliki. Med reševanjem posameznih gradiv učitelj v orodju v meniju Grades & Reporting lahko spremlja delo učencev. Učitelj v prvem delu menija za spremljanje napredka učencev dobi uvid, • integracija IKT v pouk, kar motivira učence za delo, katere naloge v gradivu so učenci bolj in katere manj uspešno • izboljšana dinamika pouka, reševali (Slika 8). • prihranek pri učiteljevem dragocenem času (zlasti če gre za pouk na daljavo v času karantene), ki ga lahko učitelj nato nameni za motiviranje in pomoč učencem, • stroškovni prihranek za šolo, saj so gradiva digitalna in se prihrani pri stroških tiskanja, obremenitev okolja ti je manjša, S os • enostavnost uporabe in bogat nabor tipov nalog za edn različna predmetna področja, pr • spremljanje napredka učencev, Slika 8. Pregled uspešnosti reševanja po posameznih • neposredna povratna informacija pri tipih nalog, ki nalogah. omogočajo samopreverjanje, V drugem delu menija za spremljavo učitelj spremlja dosežke • kompatibilnost z napravami z različnimi posameznih učencev. Vidi lahko, katere naloge je posamezni operacijskimi sistemi, učenec reševal zelo uspešno, uspešno ali neuspešno, kar je • možnost integracije v določena učna okolja (npr. prikazano z zeleno, rumeno in rdečo barvo (Slika 9). GoogleClassroom, Moodle, Canvas). S klikom na posameznega učenca se učitelju odprejo učenčeve rešitve, ki so že popravljene in točkovane. Učitelj tako samo še preleti naloge in upošteva, če je kje treba še dodatno upoštevati kakšno pravilno rešitev, ki je učitelj ni dodal ali predvidel vnaprej. Učitelj lahko v glavi gradiva ali pri posameznih nalogah doda komentarje, nato pa gradivo vrne učencu preko e-pošte, ki jo učenec mora vpisati pred zaključkom reševanja (opozorimo jih, da so pri vpisu natančni). Učenec popravljeno in komentirano gradivo prejme kot pdf priponko na svoj e-poštni naslov. 705 • nekatere predloge in tipi nalog preverjajo znanja na ki jih je s seboj prinesla epidemija koronavirusa, neprecenljive. (naj)nižjih taksonomskih stopnjah, Številni učitelji s(m)o odkrivali nove sfere modernih pristopov k poučevanju, učenci in njihovi starši so zagrizli v kislo jabolko • pri uporabi z velikim številom učencev lahko postane dajanje povratnih informacij zamudno, zlasti ko gre pouka na daljavo, vodstva šol pa so se ukvarjala z novonastalimi za naloge, pri katerih v ospredju ni samopreverjanje, težavami, ki jih ob začetku šolskega leta ni predvidel nihče. Prihodnost ni tako gotova, kot bi si želeli. Trenutno se šole • odgovori se na lokalnem računalniku (npr. v ukvarjajo z izvedbo pouka v šolskem letu 2020/21 z določenimi računalniški učilnici) shranijo; če bi BW naloge z isto omejitvami, da pouka na daljavo več ne bo, pa ni garancije. Niti povezavo reševali dve skupini učencev, je potrebno ni potrebna, saj mora po poti, ki smo jo učitelji prehodili v W uporabljati brskalnik brez sledenja zgodovine ali pa moramo odgovore prve skupine predhodno izbrisati, obdobju marec–junij 2020, v nas ostati zavest, da pouk na slabosti daljavo lahko je, tudi ko ga uradno ni. Moderni pristopi v • pri pouku na daljavo učitelj nima nadzora nad tem, ali poučevanju že in še bodo to narekovali, zato je nujno, da se učenci naloge opravljajo samostojno, kar je zlasti učitelji stalno strokovno izpopolnjujemo tudi v tej smeri. Ko pomembno, če moramo na daljavo z učenci opraviti bomo znali v klasični pouk vpletati sodobne tehnologije, tudi ocenjevanje znanja, kvalitetno presoditi katere so v posameznih primerih kakovostne • orodje ni kompatibilno za integracijo z slovenskim in uspešne, učencem postavljati jasne cilje in jim jasno dati vedeti, spletnim učnim okoljem Xooltime (eAsistent), kdaj so uspešni, takrat bomo poučevanju v prihodnje zagotovili gotovo prihodnost. • orodje je po preteku promocijskega obdobja plačljivo. ti • ostajamo v koraku s časom in učenci ter tako sledimo smernicam sodobnih pristopov v poučevanju, VIRI O nos • BW je orodje, ki se ob ustrezni in premišljeni uporabi [1] Andrin, A. et al. 2016. Učni načrt. Program osnovna šola. ilož Angleščina. Ljubljana. MIZŠ, ZRSŠ. Objavljeno na: pr izkaže za zelo koristnega v kontekstu pouka na daljavo. https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/O snovna-sola/Ucni-nacrti/obvezni/UN_anglescina.pdf (3. 8. 2020) ti • paziti moramo, da orodje uporabimo na način, ki zadosti potrebam različnih učencev, T [2] Barton, T. 2019. Teaching Strategies of the Future: 9 rnosva• paziti moramo, da orodja ne uporabljamo prepogosto, Concepts to Consider. Objavljeno na: ne saj lahko izgubi svoj čar. https://servelearn.co/blog/teaching-strategies-of-the-future- 9-concepts-to-consider/ (22. 7. 2020) [3] Šverc, M. et al. 2013. Trendi pedagogike 1:1 v inovativnem razredu. Eduvision. Objavljeno na: 6 ZAKLJUČEK http://eduvision.si/Content/Docs/Zbornik%20prispevkov% Za marsikoga, ki je aktivno udeležen v slovenskem (zlasti 20EDUvision%202013_splet.pdf (24. 7. 2020) osnovnošolskem) izobraževalnem sistemu, so bile nove izkušnje, 706 Pozitivni in negativni vidiki igrifikacije v izobraževanju Positive and negative aspects of gamification in education Marko Urh, Eva Jereb Univerza v Mariboru, Fakulteta za organizacijske vede Kidirčeva 55a 4000 Kranj, Slovenija marko.urh@um.si, eva.jereb@um.si POVZETEK Prispevek opisuje igrifikacijo v izobraževanju tako s pozitivnega 1 UVOD kot negativnega vidika. Igrifikacija pomeni uporabo elementov, Živimo v času interneta, pametnih telefonov, tablic in druge ki se pojavljajo v igrah in sicer v neigralnih kontekstih. V informacijsko-komunikacijske tehnologije. Omenjene prispevku so predstavljene osnove igrafikacije in njeni elementi. tehnologije so omogočile nasluten razmah dejavnosti, ki so del Z uvedbo igricikacije v nek specifičen proces lahko vplivamo na celotne človeške zgodovino - igre. Značilnost iger je, da se jih vedenje ljudi v tem procesu. Igrafikacije se je zaradi številnih ljudje udeležujejo in igrajo brez prisile in z veseljem. Industrija pozitivnih učinkov začela uporabljati na številnih področjih. video iger se močno razvija in nenehno pridobiva nove Eden izmed njih je tudi področje izobraževanja. S pravilno uporabnike [1], njen tržni delež v industriji zabave raste in uporabo igrafikacije se lahko poveča angažiranost, motiviranost, postaja glavni vir zabave [2]. Da bi igre pritegnile in ohranile učinkovitost in uspešnost študentov v izobraževanju. Vendar igralce se v industriji iger poslužujejo določenih tehnik in metod uvedba igraifkaicje v izobraževanje sama po sebi še ne zagotavlja znane pod imenom igrifikacija (angl. gamification). Igrifikacija uspeha. V prispevku so prikazani številni izsledki raziskav. S tem pomeni uporabo elementov, ki se pojavljajo v igrah. Najbolj želimo čim bolj objektivno prikazati področje igrifikacije tako s značilni elementi igrifikacije so točke, značke, lestvice, pozitivnega kot negativnega vidika. napredovanje, statusi, nivoji, nagrade in drugo. Namen igrifikacije je izboljšati sodelovanje med uporabniki, povečati KLJUČNE BESEDE motiviranost in uspešnost pri opravljanju določenih nalog in sicer Izobraževanje, igrifikacija, elementi igrifikacije z vključevanjem elementov iger in drugih elementov, ki naredijo neko nalogo bolj privlačno [3]. Igrifikacija se je izkazala za ABSTRACT učinkovito in uporabno na številnih področjih. Nekatera izmed The paper describes gamification in education from a positive teh so finance in finančna pismenost [4], kadrovski management and negative perspective. Gamification means using elements [5], informacijska pismenost [6], management informacijskih that can be found in games in non-gaming contexts. The paper tehnologij [7], management sprememb [8], management tveganj presents the basics of gamification and elements of gamification. [9], marketing [10], računalništvo [11], turizem [12], visoko By introducing gamification into a specific process, we can šolstvo [13] in drugo. Eno izmed področij, kjer se igrifikacija influence the behavior of people in that process. Gamification is največ uporablja je izobraževanje. Raziskave o igrifikaciji na used in many fields due to its many positive effects. One of them področju izobraževanja omenjajo številne pozitivne vplive na is also the field of education. Proper use of gamification can udeležence kot so povečana motiviranost, angažiranost, increase the engagement, motivation, efficiency, and učinkovitost in uspešnost. Obstajajo pa tudi negativne lastnosti, effectiveness of students in education. However, the use of ki so lahko posledica igrifikacije in njene nepravilne uvedbe v gamification in education does not guarantee success. The paper izobraževanje. V nadaljevanju so predstavljene osnove presents several research findings. We want to show the field of igrifikacije in igrifikacije v izobraževanju. gamification as objectively as possible, both from a positive and an opposing point of view. 2 IGRIFIKACIJA KEYWORDS Večji trend znanstvenega in raziskovalnega proučevanja Education, gamification, elements of gamification igrifikacija lahko zasledimo v letu 2010 in naprej. Igrifikacijo oz. njen pomen lahko definiramo kot uporabo elementov iger in njenih značilnosti v dejavnostih, ki niso igre [14]. Seznam elementov igrifikacije, ki jih je mogoče uporabiti v praksi [15]: točke: številčne enote, ki merijo napredek (točkovanje); značke: Permission to make digital or hard copies of part or all of this work for personal or vizualne ikone, ki kažejo dosežke (trofeje); lestvice: prikaz classroom use is granted without fee provided that copies are not made or distributed vrstnega reda udeležencev (uvrstitve); napredovanje: mejniki, ki for profit or commercial advantage and that copies bear this notice and the full kažejo napredek (napredovanje); status: prikaz določenih citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). dosežkov (naslov, rang); stopnje: vse bolj zahtevna okolja Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 707 (stopnje); nagrade: oprijemljivi, zaželeni predmeti (spodbude, povečali zadovoljstvo, motiviranost in angažiranost uporabnikov. nagrade; darila, …) in vloge: vloge igralca (razred, značaj, …). Dejavnosti in procesi podprti z elementi igrifikacije imajo tri Omenjene elemente lahko uporabimo z namenom vplivanja glavne učinke na udeležence: motivacijski, psihološki na vedenje posameznika ali skupine v nekem procesu. Poleg tega (sprememba občutkov o dejavnosti med in po njej) in vedenjski lahko s pomočjo igrifikacije naredimo določene nalog bolj (sprememba vedenja po igrificirani dejavnosti) [25]. zanimive in s tem povečamo verjetnost dokončanja neke naloge. Tega so se v industriji iger začeli zavedati že zelo zgodaj in ni naključje, da industrija iger postaja eden izmed glavnih virov zabave. Poslovna skupina Obstajajo ocene, da je bil leta 2019 trg Anksioznost Vzburjenost Stanje toka igrifikacije vreden okoli 6 milijard dolarjev [16]. Igrifikacija se Visok (anxiety) (arousal) (flow) je zaradi svojih lastnosti zelo uveljavila na številnih področjih, predvsem pa v izobraževanju. Z vključevanjem igrifikacije v izobraževanje lahko dokazano povečamo motiviranosti, ge učinkovitosti in uspešnost posameznikov v nekem izobraževanju. . nalo Skrb Nadzor (worry) (control) 3 IGRIFIKACIJA V IZOBRAŽEVANJU izziva oz (challenge level) Igre imajo pomemben pozitiven vpliv na razvoj motoričnih Nivo sposobnosti, kreativnosti, gibanja in so potrebne za celoten fizični razvoj posameznika [17]. V svetovnem merilu se tedensko porabi več kot tri milijarde ur za igranje video in/ali Apatija Dolgočasje Relaksacija računalniških iger in skoraj tretjina študentov igra tri ali več ur (apathy) (boredom) (relaxation) video in računalniških iger na povprečen šolski dan [18]. Za Nizek spodbujanje učencev, dijakov in študentov se že dalj časa Nivo sposobnosti uporabljajo različni zunanji vzvodi in mehanizmi kot so bralne Nizek (skill level) Visok značke, različne nagrade (materialne in nematerialne), različne Slika 1: Mentalno stanja igralca/izobraževanca glede na častna mesta, dekanove liste in drugo [19]. Omenjeni avtorji so njegov nivo sposobnosti in nivo izziva/naloge (prirejeno mnenja, da je namen takšnih nagrad dodatno motivirati osebe za po [22]). učenje oz. študij. Raziskava o vplivu elementov igrifikacije na motivacijo študentov, da obstajajo razlike med posameznimi elementi igrifikacije [20]. Tako je med posameznimi študenti pet 4 POZITIVNI VIDIKI IGRIFIKACIJE najbolj zaželenih elementov: (1) pridobivanje dodatnih točk za Igrifikacija pomeni uporabo elementov iger (točke, nagrade, prisotnost na predavanjih in vajah, (2) sodelovanje s sovrstniki in lestvice, …), ki se lahko uporabijo v izobraževanju za doseganje skupinsko delo, (3) pridobivanje dodatnih točk za aktivno pozitivnih učinkov pri učencih [26] in z namenom narediti sodelovanje na predavanjih in vajah, (4) pridobivanje dodatnih izobraževanje prijetno oziroma zabavno, kot so zabavne in točk za opravljanje domačih, seminarskih in drugih nalog in (5) prijetne video igre [2]. Uporaba elementov iger v izobraževanju nagrade za uspeh v obliki bonus točk. Pet najmanj zaželenih ima številne prednosti in se je pokazala za uspešno v elementov igrifikacije pa predstavljajo elementi kot so (1) kazni izobraževalnih okoljih [27]. Zaradi svojih pozitivnih lastnosti se za zamujanje časovnih rokov oddaje, (2) kazni za neuspešno je igrifikacija v izobraževanju zelo uveljavila. Raziskave s opravljanje obveznosti (npr. minus točke, idr.), (3) nagrade zgolj področja igrifikacije v izobraževanju poročajo o številnih iz naključne sreče (npr. na podlagi žreba, idr.), (4) razvrščanje v pozitivnih rezultatih. V nadaljevanju so nekateri izmed njih: [28] lestvice z anonimnimi udeleženci (npr. indeks in ocene) in (5) uporaba prikaza dosežkov pri učencih; [29] uporba izzivov, razvrščanje v lestvice z vidnimi udeleženci (npr. tekmovanje s nivojev, nagrad, časovnih pritiskov, točk in mini iger; [30] sovrstniki). Izobraževanje podprto z igrifikacijo ima nekatere uporaba značk; [31] uporaba točk, prikaza dosežkov in nagrad skupne lastnosti z določenimi teorijami učenja, ki priporočajo pri učencih; [32] uporaba nagrad; [33] uporaba značk za hitre in pozitivne povratne informacije, kratke naloge in doseganje nekaterih pozitivnih učinkov; [34] omenja različne postopne izzive prilagojene znanju in veščinam udeležencem elementi igrifikacije; [35] pozitivni učinki na kratkoročne izobraževanja [21]. Usklajenost med zahtevnostjo nalog in dejavnosti podprte z igrifikacijo. dejanskim znanjem udeležencem lahko pri udeležencih povzroči S pomočjo uporabe igrifikacije pri študentih, le ti postanejo stanje velike motiviranosti in angažiranosti, ki ga strokovno bolj motivirani za delo ter, da lahko določene naloge opravljajo imenujemo stanje toka (angl. flow). Na Sliki 1 lahko vidimo z večjim zadovoljstvom [36]. Prednost uporabe igrifikacije na mentalni model oz. stanje igralca/izobraževanca glede na njegov področju izobraževanja se kaže v takojšnji povratni informaciji nivo sposobnosti in nivo izziva/naloge. (v primeru, da so sistemi podprti z informacijsko- Stanje toka lahko opredelimo kot optimalno izkušnjo za komunikacijsko tehnologijo), ki je značilna za video in katero sta značilna popolna osredotočenost in angažiranost pri računalniške igre [26]. Rezultati raziskave o opravljanju nalog, neki aktivnosti [23]. Tok pri udeležencih sprožijo štirje elementi, ki so podprte z igrifikacjo povečuje motivacijo študentov in ki jih lahko najdemo v igrah [24]: jasni cilji in pravila, povratne njihovo medsebojno sodelovanje [37]. informacije in prostovoljno sodelovanje. Omenjene elemente bi Uvedba elementov igrifikacije v izobraževalni proces pa še bilo smiselno v čim večji meri uporabiti v izobraževalnih ne pomeni, da bodo udeleženci izobraževanja ustrezno procesih, saj bi s takšnim načinom dela lahko bistveno bolj motivirani, angažirani in bolj učinkoviti. Rezultati nekaterih 708 empiričnih raziskav o različnih elementih igrifikacije izvedenih Pri uvedbi igrifikacije v izobraževanje se pojavljajo še druga v izobraževalnih ustanovah so tudi mešani [37]. Nekatere od teh vprašanja kot so: (1) profiliranje uporabnikov in njihov odziv; (2) so: [38] uporaba točk in napredka; [39] uporaba značk in lestvic; kako primerno obremeniti študente glede njihovega znanja in [40] uporaba nivojev, izzivov, značk in lestvic; [35] mešani sposobnosti; (3) kulturne razlike v dojemanju igrifikacije; (4) učinki pri različnih učencih. individualne in kolektivne spremenljivke in drugo. Poleg Opazimo lahko, da se pri pozitivnih in mešanih učinkih omenjenih vprašanj se je potrebno zavedeti, da igrifikaicja pri pojavljajo podobni elementih igrifikacije. Iz tega lahko sklepamo, študentih lahko sproži tudi neželena vedenja kot so goljufanje, da ni problem v elementih iger temveč v načinu njihovega upad zanimanja za neko nalogo, slabša kakovost izdelkov, skrb posredovanja, izvedbe procesa ali drugih faktorjev. Različne za zasebnost in drugo. aktivnosti so primerne za samo določene udeležence in morajo biti realizirane na različne načine. Vedno bolj se poudarjajo potrebe po personalizaciji izobraževanja in po raziskavah o 6 ZAKLJUČEK razumevanju učinkov igrifikacije na individualni ravni Industrija iger je v porastu in igre (predvsem video in posameznika [41]. Glede na potencial, ki ga ima igrifikacija bi računalniške) postajajo glavni vir zabave. Kljub temu pa niso vse bilo smiselno prilagoditi elemente igrifikacije posamezniku, kar igre komercialno uspešne, saj so uporabniki tisti, ki se na pa zahteva poznavanje in uskladitev osebnostnih lastnosti in prostovoljni osnovi odločajo ali bodo igre igrali ali ne. Razlogov elementov igrifikacije. za neuspešnost neke igre je lahko več od nezanimivosti, prevelike zahtevnosti, nepravilne uporabe elementov iger in 5 NEGATIVNI VIDIKI IGRIFIKACIJE drugih faktorjev. Podobno je tudi z igrifikacijo v izobraževanju. Vpeljava elementov igrifikacije v izobraževanje še ne zadostuje, Kot vse stvari in storitve ima tudi igrifikacija v izobraževanju da postane takšno izobraževanje tudi zanimivo za uporabnike. določene pomanjkljivosti. Za dobro razumevanje učinkov Večina raziskav s področja igrifikacije v izobraževanju je bila igrifikacije v izobraževanju je potrebno dobro razumeti v preteklosti osredotočena na pozitivne učinke kot so povečana posamezen izobraževalni model, ki je podprt z elementi motivacija, angažiranost, učinkovitost in uspešnost (učencev, igrifikacije [2]. Negativno stran študij o igrifikaciji predstavlja dijakov ali študentov). Pomanjkljivo pa so bili raziskani tudi omenjen vzorec empiričnih študij, kar je posledica negativni vplivi, ki jih lahko ima igrifikacija v izobraževanju. Za metodoloških težav, kot so pomanjkanje primerjalnih skupin, uspešno vpeljavo elementov igrifikacije v izobraževalni proces kratkih časovnih rokov raziskav in drugo [25]. Pomanjkanje moramo podrobno razumeti elemente igfifikacije, ki lahko analiz uporabniških profilov, neustrezne metode oblikovanja in vplivajo na uporabnika. Obstajajo številni faktorji in njihovi preveč preprosta uvedba igrifikacije lahko privede do medsebojni vplivi, kot so kulturno okolje, osebnost posameznika, neustreznih rezultatov uvedbe igrifikacije v izobraževanju [3]. starost, spol, razlike med individualnim in skupinskim delom, Socialno primerjanje običajno pripelje do tekmovanja, s tem razumevanje vplivov posameznih elementov igrifikacije in drugo. pa se posamezniki zavedo pomanjkanja svojih spretnosti v O uspešni uvedbi igrifikacije v izobraževanje se lahko veliko primerjavi z ostalimi udeleženci [42]. Tekmovanje in naučimo tudi od nekaterih dobrih komercialnih poizkusov, ki so medsebojno primerjanje lahko zmanjša sodelovanje in reševanje prestali test časa in kritičnost uporabnikov. Nekatere izmed bolj problemov ter lahko pripelje do raznih oblik goljufanja [43]. znanih spletnih izobraževalnih platform so Duolingo, Khan Nekateri avtorji [44] so pripravili pregled literature o igrifikaciji Academy, Moodle, Lumosity, Neuro Nation in drugi. Za uspešno na področju izobraževanja in predstavili seznam kritičnih točk, uvedbo igrifikacije moramo razumeti in vedeti kateri elementi so ki lahko zmanjšajo notranjo motivacijo študentov. Poleg tega udeležencem v izobraževalnem procesu pomembni. Igrifikacija omenjeni avtorji navajajo, da igrifikacija ni primerna za vsako se veliko bolje obnese če se njeni elementi odražajo tudi realnosti izobraževalno okolje ter da je izredno težko doseči (npr.: dodatne točke za vaje, ustna pohvala, …). Doseganje uravnoteženost med nalogami in znanjem. V določenih virtualnih točk, ki v realnem svetu nimajo pomena, postane raziskavah poročajo o nerazumevanju pravil, kar lahko dolgočasno in nezanimivo. posledično zmanjša uspešnost izobraževanja [45]. Avtorja [46] poročata o nezanimivo postavljenem sistemu bonusov oz. nagrad. Različni avtorji [40] poročajo, da udeleženci v njihovem LITERATURA eksperimentalnem izobraževalnem procesu podprtem z [1] Alexander, J. T., Sear, J., in Oikonomou, A. (2013). An igrifikacijo niso dobro sprejeli takšnega sistema, ker so menili, investigation of the effects of game difficulty on player da sistem ni prijeten in da je izguba časa. Dogaja se, da študenti enjoyment, Entertainment Computing 4 (2013) 53–62. sčasoma izgubijo zanimanje za izobraževanje podprto z [2] Simões, J., Redondo, R. D., in Vilas, A. F. (2013). A social igrifikacijo, ker ni dovolj zanimivo [47]. 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Soc. 11(3), 85–99. 711 Vpeljava, dobre prakse in spoznanja poučevanja ter učenja na daljavo na Osnovni šoli Preska Introduction of distance teaching and learning, examples of good practice and insights in Preska primary school Tina Veselinovič OŠ Preska Preška cesta 22 1215 Medvode, Slovenija tina.veselinovic@sola-preska.si POVZETEK KEYWORDS V prispevku so opisani načini vpeljave poučevanja in učenja na Primary school, digitalization in education, distance teaching and daljavo na Osnovni šoli Preska. Predstavljena so spoznanja na learning, methods and tools ravni šole, učitelja in učenca, ki zajemajo metode ter predvsem tiste dejavnosti in pripomočke, ki so se izkazali za koristne. V obdobju zaprtja šol so v šolskem prostoru svoje mesto dobile 1 UVOD marsikatere nove in presenetljive prakse. Iznajdljivost in Izobraževanje na daljavo je v preteklih desetletjih mnogokrat fleksibilnost pod okriljem digitalne kompetence sta tako na strani pomenilo le alternativo, saj se doslej še nismo srečali z učitelja kot učenca postali najpomembnejši vrlini. Prispevek okoliščinami, v katerih je postalo tako rekoč nujno potrebno in vsebuje nekatere ideje, dobre prakse, metode in orodja za delo na skorajda edina opcija. Pred skoraj dvema desetletjema je Ivan daljavo v obdobju, ki je poleg novitet prineslo predvsem potrebo Gerlič v zborniku strokovne konference E-izobraževanje po še temeljitejši refleksiji učiteljevega in učenčevega dela ter doživeti in izpeljati izobraževanje na daljavo opisal kot obliko napredka. posrednega oz. indirektnega izobraževanja, kjer sta učitelj in učenec med seboj fizično ali tudi časovno ločena, kjer učitelj KLJUČNE BESEDE sproti preverja učni uspeh udeleženca in kjer se učno gradivo Osnovna šola, digitalizacija pouka, poučevanje in učenje na posreduje na daljavo s pomočjo medijev v tiskani ali elektronski daljavo, metode in orodja obliki [1]. Tedaj je e-izobraževanje pomenilo nadgradnjo oz. poučevanje in učenje v koraku s časom. Prehod v e- ABSTRACT izobraževanje je bil v času zaprtja šol nagel, zato je bilo tistim, The article presents ways of introduction of distance teaching and ki so se z njim do tedaj že seznanili, mnogo prihranjenega. Niko learning in Preska Primary School. It shows insights of the whole Schlamberger je v prispevku Pismo strankam – Predlogi za dvig school as well as individual students and teachers, which involve digitalnih kompetenc izpostavil problem nujnosti dviga digitalne methods and the most efficient activities and tools. During pismenosti. Po njegovem mnenju sta družba in država glede tega lockdown, the online school environment has produced several premalo ozaveščeni, saj se pomembnosti dviga digitalnih new and surprising methods. Suddenly ingenuity and flexibility kompetenc zavedajo le posamezniki in nekatere institucije [2]. became the most important virtues supported by digital Njegove ugotovitve so se v obdobju e-izobraževanja potrdile in competence for both teachers and students. The article presents skrbi izkazale za upravičene. some of the ideas, examples of good practice, methods and tools Na OŠ Preska smo se v času, ko se je v državi zaostrovala for distance teaching in the time when, apart from all the epidemiološka slika in se je slutilo zaprtje šol, že intenzivno novelties brought about, the need to reflect in depth in connection ukvarjali s pripravami na prihajajoče obdobje. Kot povsod to the work and progress of both teachers and students has drugod je bilo naenkrat zelo malo časa za načrtovanje, zato smo become apparent. se naslonili na tisto, kar lahko nemudoma ponudimo in kar so naši učenci ter sodelavci že (vsaj delno) poznali. V času zaprtja šol je pouk na daljavo na razredni stopnji večinoma potekal po elektronski pošti in s pomočjo videokonferenc, saj smo menili, da je za to starostno obdobje to najustreznejši način. Razredničarka je z učenci komunicirala preko staršev, brez sodelovanja katerih najbrž delovanje ne bi Permission to make digital or hard copies of part or all of this work for personal or bilo uspešno. Za komunikacijo so uporabljali svoje elektronske classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full naslove. citation on the first page. Copyrights for third-party components of this work must Za učence predmetne stopnje smo menili, da lahko učenje na be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia daljavo v veliki meri spremljajo povsem samostojno. Kmalu smo © 2020 Copyright held by the owner/author(s). si zadali cilj, da bomo obdobje šolanja na daljavo izkoristili za 712 računalniško opismenjevanje in poiskali načine, ki bi nas 3 PODPORA UČENCEM pripeljali do želenih rezultatov. Naša prizadevanja so predstavljena v nadaljevanju. 3.1 Organizacijska podpora učencem V tednu pred zaprtjem šol smo se učitelji večkrat sestali in v 2 PODPORA UČITELJEM dogovoru z vodstvom šole naredili načrt delovanja za čas, ko bi morali znanje posredovati s pomočjo elektronske tehnologije. 2.1 Organizacijska podpora učiteljem Pretehtali smo možnosti in vsak pri sebi preverili razpoložljivost potrebnih naprav ter lastno zmožnost njihove uporabe. V Za vzpostavitev in nemoten potek poučevanja na daljavo je dogovoru z računalničarko smo po potrebi posamezne težave vseskozi skrbela računalničarka, na katero smo se učitelji lahko individualno reševali. po pomoč obrnili katerikoli dan in skorajda katerokoli uro. V Razredniki so razredne ure in ostale razpoložljive trenutke dnevih pred zaprtjem šol nas je pozvala, naj se (ponovno) posvetili pogovoru in pripravi na obdobje izobraževanja na seznanimo s spletno učilnico Moodle in nam v primeru težav daljavo. Učence so uvodno seznanili s spletno učilnico Moodle, nudila pomoč. ki jo je večina učencev že poznala, saj so jo učitelji že več let Učitelji, ki spletne učilnice še niso uporabljali, so imeli uporabljali kot učinkovit pripomoček za popestritev in utrjevanje možnost individualnega izobraževanja. učnih vsebin. Na OŠ Preska učitelji v domačem okolju tudi za službene V vsakem razredu smo v dveh dneh izpeljali izobraževanje, namene uporabljamo lastne računalnike in ostalo opremo. ki ga je vodila računalničarka in je trajalo eno šolsko uro. Računalničarka je zato naredila poizvedbo, v kakšnem stanju so Namenjeno je bilo upravljanju in delu z e-učilnico Moodle. Poleg naše naprave. V najkrajšem možnem času smo s skupnimi tega so vsi učenci predmetne stopnje dobili svoj šolski močmi poskušali odpraviti večino težav in nadomestiti elektronski naslov, s pomočjo katerega so komunicirali z učitelji. nedelujoče ali zastarele naprave z razpoložljivimi iz šole. Poskrbeli smo, da smo učitelje opremili s komponentami, za 3.1.1 Pomoč pri zagotovitvi računalnikov katere smo menili, da bodo pri poučevanju na daljavo potrebne Šola je v času pred zaprtjem in v času le-tega večkrat pri učencih (mikrofon, zvočniki, kamera …). in njihovih starših poizvedovala o razpoložljivosti komunikacijske tehnologije in jih pozvala, naj sporočijo, če 2.2 Sodelovanje med učitelji menijo, da so naprave, ki jih imajo doma, neustrezne ali Četudi je sodelovanje potekalo v fizični odsotnosti, je bilo nedelujoče. Za poizvedbo smo uporabili več možnih kanalov konstantno in konstruktivno. Na pobudo računalničarke smo se (razredne ure, individualne razgovore, govorilne ure, družabna učitelji vsak dan od ponedeljka do petka ob 10. uri dopoldne omrežja, elektronsko pošto, sistem LoPolis …). srečevali preko videokonferenc, ki smo jih poimenovali Odmor Na šoli smo skupaj z Občino Medvode, Civilno zaščito in s s kavo. Na začetku smo uporabljali Zoom, kasneje pa po pomočjo donatorjev (Rotary Club in založba Rokus Klett) uspeli priporočilih Googlovo aplikacijo Meet. Sprva smo imeli nekaj skupaj zagotoviti 21 računalnikov. začetniških težav, a smo jih kmalu uspešno odpravili (prikaz slike, upravljanje s kamero, nadzor nad glasnostjo in aktivnostjo 3.2 Spletna učilnica Moodle mikrofona, deljenje zaslona …). Ažurno in sinhrono smo Z uporabo spletne učilnice Moodle smo na OŠ Preska začeli pred spremljali delo učencev, iskali rešitve in odpravljali težave. približno desetimi leti. V tem času jo je uporabljalo nekaj Videokonferenc smo se večinoma udeleževali vsi pedagoški učiteljev predmetne stopnje, zato so jo vsaj v grobem že spoznali delavci, če le nismo imeli takrat napovedanih video srečanj z mnogi učenci. Dostopna je na spletni strani OŠ Preska, ki deluje učenci. Redno sta sodelovala tudi ravnatelj in pomočnik na lastnem strežniku. Prav slednje je vseskozi bistveno ravnatelja, ki sta po potrebi dodatno pojasnjevala informacije, ki pripomoglo k nemotenemu delovanju spletne učilnice in sta jih sicer posredovala po elektronski pošti. neovirani komunikaciji med učenci in učitelji. Mnoga druga spletna okolja so se namreč srečevala s preobremenjenostjo, ki ji 2.2.1 Medgeneracijska pomoč med učitelji je botroval naval ob zaprtju šol. Posebej velja omeniti, da je bila v teh časih vidnejša vrzel med Moodle omogoča vnašanje besedil, nalaganje dokumentov, starejšimi in mlajšimi učitelji, ki se je nanašala predvsem na dodajanje spletnih povezav in uporabo različnih integriranih znanje pri uporabi komunikacijske tehnologije. Nekateri mlajši orodij, zato je tako rekoč solidno zastavljen in brezplačen predstavniki so starejšim kolegom pomagali pri usvajanju pripomoček za poučevanje in učenje na daljavo. računalniških spretnosti, uporabi aplikacij in urejanju ter uporabi Učitelji predmetne stopnje smo učilnico po presoji vsakega e-učilnice. Pomoč je bodisi potekala telefonsko bodisi preko posameznega učitelja razdelili po predmetih ali posameznih organiziranih videokonferenc, ki jih je sklical učitelj, ki je učiteljih, pri čemer pa smo se ušteli. Po zaključku poučevanja na določeno področje dobro poznal. Pripravljenost in dostopnost daljavo smo spoznali, da smo na začetku lahkomiselno verjeli, mlajših učiteljev je bila tu ključnega pomena in še eno spoznanje da se bomo v šole vrnili po 14 dneh, kot se je sprva načrtovalo. več, kako lahko tak pristop k delu pripomore k uspešnemu V bodoče bomo stremeli k enotnosti pri oblikovanju spletnih delovanju znotraj kolektiva. Mlajši učitelji so uporabljali in učilnic, kar bo predvsem učencem zagotovilo večjo preglednost. kolegom posredovali veščine digitalne tehnologije ter na ta način tudi sami obnovili marsikatero znanje. Tako se je tudi pri njih 3.3 Videokonference samih ohranilo, kar bi se v poplavi novosti sicer lahko z leti izgubilo. Vsako tako znanje se bo tako s strani mlajših kot Tako kot smo učitelji komunicirali med seboj, smo seveda želeli starejših učiteljev zagotovo s pridom uporabljalo v prihodnosti. komunicirati tudi z učenci. Prej omenjeni Odmori s kavo so nam 713 pod preprostim in šaljivim imenom omogočali tudi soočanje s 4.4 Quizizz tehnologijo, ki je prej sploh nismo uporabljali ali pa je večinoma Quizizz je pripomoček, ki so ga učenci zelo dobro sprejeli, a je nismo dobro poznali. Na začetku je bila to aplikacija Zoom, bolj kot ne namenjen le zabavi in popestritvi ob utrjevanju snovi. kasneje pa Google Meet, ki smo jo večinoma uporabljali tudi v Omogoča izdelavo preprostih kvizov in je prav tako brezplačen. stiku z učenci. Videokonference so se izkazale za koristne predvsem pri individualnem delu z učenci, kot npr. pri delu z učenci s posebnimi potrebami, učenci tujci, pri zagovoru bralne 5 UGOTOVITVE, SPOZNANJA IN NAČRTI značke . . Na ravni celotnega oddelka so se učenci srečevali predvsem z razredniki, na t. i. videokonferenčnih razrednih urah, Po zaključku obdobja poučevanja in učenja na daljavo smo ki so v času zaprtja šol nudile prepotreben stik s sošolci in dodobra pregledali rezultate dela in pretehtali možnosti za razrednikom. Kot manj učinkovite pa so se videokonference izboljšanje stanja. Temeljna ugotovitev je bila, da so bile izkazale za namen razlage nove snovi, na kar je vplivalo mnogo nekatere stvari zastavljene preveč ambiciozno, kar pomeni, da dejavnikov. Tako kot učitelji so se tudi učenci soočali z smo si predstavljali, da jih učenci poznajo veliko bolje, kot se je novitetami, ki so jim povzročale marsikatero preglavico. Razlago kasneje izkazalo. Verjetno smo v poplavi materiala in orodij, ki nove snovi smo učitelji velikokrat raje ponudili s pomočjo vseh smo jih v dobri veri želeli ponuditi učencem, nehote povzročili vrst video in zvočnih posnetkov, preko videokonferenc pa smo tudi zbeganost in stisko ob zahtevah po obvladovanju zagotovili možnost dodatne razlage snovi. računalniških spretnosti. Za naslednje šolsko leto smo si zadali Omeniti velja, da smo bili mnogi učitelji preko cilj, da predvsem učenci predmetne stopnje še dodatno videokonferenc učencem vselej na voljo in da jim je to zavedanje nadgradijo in okrepijo računalniško znanje. Ob zaključku pouka veliko pomenilo. Na naši šoli je namreč veliko otrok, ki v svojem za šolsko leto 2019/2020 smo naredili načrt za delo predvsem z okolju nimajo veliko družbe, zato jim je naša dostopnost obdobje učenci od 6. do 9. razreda. Vanj smo vpeli vse učitelje predmetne izolacije olajšala. stopnje, ki bodo na ta način tudi sami obnovili znanje za morebiten ponoven prehod k poučevanju in učenju na daljavo. V veliko pomoč pri oceni stanja in načrtovanju izboljšanja 4 NEKATERA ORODJA ZA USPEŠNO DELO nam je bila anketa, ki smo jo proti koncu obdobja poučevanja in NA DALJAVO učenja na daljavo posredovali učencem in staršem. Izpolnilo jo je skoraj 50 odstotkov staršev in okoli 25 odstotkov učencev. 4.1 YouTube Spraševali smo jih o opremljenosti in dostopu do komunikacijske tehnologije, obvladovanju dela z njo, kateri način dela jim najbolj Portal YouTube je že leta na prvem mestu po priljubljenosti med ustreza, kolikšna je stopnja samostojnosti učencev in uspešnost spletišči, ki ponujajo ogled in nalaganje videoposnetkov. Mnogi reševanja nalog, ali so navodila s strani učitelja razumljiva ipd. učitelji smo ustvarili svoj kanal, na katerem so lahko učenci našli Rezultate smo analizirali in jih predstavili pedagoškemu osebju najrazličnejše gradivo, ki smo jim ga pripravili. Pri pouku in staršem. slovenskega jezika so npr. lahko dobili razlago nove snovi, interpretacijo poezije, glasno branje odlomka iz berila ipd. Portal učenci dobro poznajo in uporabljajo tudi v prostem času, zato jim 6 ZAKLJUČEK je bilo tokrat prihranjeno seznanjanje z novimi orodji. Četudi je bil prehod k izobraževanju na daljavo nenaden, smo se 4.2 GoFormative na to za marsikoga neznano pot podali dokaj uspešno. Mnogi učitelji smo s trudom znova dokazali, da smo lahko kos novim in Brezplačna aplikacija nam omogoča izdelavo kvizov, zahtevnim nalogam. Težave smo reševali timsko in se zavedali, vprašalnikov ali testov, ki so nam lahko v pomoč pri preverjanju da naša neomajnost pomeni kakovost za najpomembnejše in ocenjevanju znanja. Vnašamo lahko že narejene teste, deležnike učnega procesa - naše učence. Proti digitalni oblikujemo naloge/vprašanja in jih točkujemo. Način pridobitve pismenosti smo s pomočjo medgeneracijskega sodelovanja povratne informacije je tako zelo enostaven in hiter. uspešno vodili starejše kolege, ki so se prvič srečali z marsikatero Reševanje takšnih testov je sicer zahtevalo veliko dodatne noviteto. Učencem smo nudili pomoč preko videokonferenc in razlage in zavedanja pomembnosti natančnosti ter upoštevanja spletne učilnice, kjer smo jim predstavili različna internetna pravil, a je bilo učencem kljub temu vznemirljivo in zanimivo. orodja za učinkovito delo na daljavo. Slabost brezplačne različice GoFormative je v tem, da dovoljuje O uspešnosti našega delovanja pričajo rezultati ankete, ki smo nalaganje relativno majhnega števila posameznih strani (do 20 jo posredovali staršem in učencem. Zadovoljni smo, da so strani). predvsem učenci naše udejstvovanje znali prepoznati kot dobro 4.3 Screencast-o-Matic in v njem videli sprejemljivo opcijo. Po vrnitvi v šolske klopi smo se posvetili področjem, za katera smo menili, da so bila v Orodje je v omejeni različici prav tako dostopno brezplačno in času dela na daljavo manj uspešna. Tem spoznanjem in omogoča snemanje zvoka ob sliki/predstavitvi. Za ozadje si izkušnjam bomo pri načrtovanju podobnih dejavnosti v bodoče lahko izberemo sliko ali pa drsnice, ob katerih razlagamo ali namenili največ pozornosti utrjujemo snov. Program ponudi shranjevanje videoposnetka na računalnik, tega pa lahko kasneje naložimo npr. na YouTube. Program je še posebej uporaben za delo z učenci s posebnimi VIRI potrebami. Učencu, ki ima denimo disleksijo, lahko učitelj ob [1] Geder, M. et al. 2003 . E-izobraževanje doživeti in izpeljati: predvajanju besedila glasno bere. zbornik strokovne konference. Maribor. Doba. 714 [2] Schlamberger, N. 2018. Pismo strankam – Predlogi za dvig BVH4L8Z5/?euapi=1&query=%27keywords%3dniko+schlamb digitalnih kompetenc. Slovensko društvo Informatika. erger%27&sortDir=ASC&sort=date&pageSize=25 (15. 9. 2020) Objavljeno na: http://www.dlib.si/details/URN:NBN:SI:DOC- 715 Od besede do besedila s pomočjo IKT From one word to a text with the help of ICT Tadeja Vučko OŠ Draga Kobala Maribor Tolstojeva ulica 3 2000 Maribor, Slovenija tadeja@osdk.si POVZETEK Oboje so učenci že poznali. V nadaljevanju bo predstavljen način dela na daljavo pri obveznem izbirnem predmetu nemščina. V preteklem šolskem letu smo v marcu čez noč prešli iz dela v razredu, ki smo ga bili vajeni tako učitelji kot tudi učenci, na delo na daljavo. Delo se je nadaljevalo s pomočjo informacijsko- 2 OBVEZNI IZBIRNI PREDMET NEMŠČINA komunikacijske tehnologije, učitelji pa so morali najti drugačne poti do ciljev, kot so si jih zastavili ob začetku šolskega leta. V Že v uvodnih besedah učnega načrta za obvezni izbirni predmet pričujočem prispevku so predstavljeni koraki od spoznavanja nemščina je poudarjeno, da imajo tuji jeziki pomembno vlogo pri posamezne besede v tujem jeziku do tvorbe celotnega besedila in vzgoji in izobraževanju. Nemščina kot tuj jezik je pomembna za nekaj orodij, ki so jih učenci uporabljali v obdobju dela na intelektualno rast posameznika, za oblikovanje samopodobe in daljavo. V sklopu spletnih nalog so učenci razvijali tako slušne samozavesti ter za vključevanje v družbi. [1] V splošnih ciljih in bralne kot tudi govorne in pisne spretnosti. predmeta je zapisano [1], da je temeljni cilj pouka vzpodbuditi zanimanje za drugo in drugačno. Pouk je usmerjen k učencu in KLJUČNE BESEDE njegovemu razvoju in postopni samostojnosti. [1] V sklopu doseganja operativnih ciljev učenci razvijajo in poglabljajo Pouk tujega jezika, IKT, aplikacije jezikovno znanje ter jezikovne sposobnosti (slušno in bralno ABSTRACT razumevanje, ustno in pisno sporočanje), postopoma se seznanijo In the past school year, in March, we moved virtually overnight z jezikovnimi normami, konvencijami in funkcijami. [1] Sprva from classroom work, which both students and teachers were je poudarek na reprodukciji, kasneje pa na produktivnem accustomed to, to distance education. The work continued with poglabljanju v tematske sklope. [1] the help of information and communication technology, and Pri poučevanju tujega jezika imamo torej v mislih teachers had to find different paths to the goals they had set at the posameznika, ki pri učenju tujega jezika na različne načine beginning of the school year. The paper presents the steps from spoznava novo besedišče. Svoje jezikovne sposobnosti poglablja learning a single word in a foreign language to creating a full text na področju slušnega in bralnega razumevanja ter pisnega in and some of the applications used by students during distance bralnega sporočanja, s čimer pa postane pozoren tudi na lasten learning. As part of these tasks, students develop both listening jezik in lastno kulturo. and reading skills, as well as speaking and writing skills. 2.1 Nemščina in IKT KEYWORDS Uporaba informacijske in komunikacijske tehnologije je v Foreign language teaching, ICT, applications učnem načrtu za obvezni predmet nemščina omenjena v razdelku »Medpredmetno povezovanje«. Sposobnost pridobivanja, vrednotenja in uporabe informacij pa je tesno povezana z 1 UVOD znanjem informacijskih tehnologij, ki ga učenci pridobijo na Zaradi zaprtja šol so učitelji morali poiskati nove poti do učencev področju računalništva in informatike. [1] Ker se je od izdaje in s tem tudi do znanja. Situacija je tako učence kot učitelje učnega načrta v letu 2001 marsikaj spremenilo, se je potrebno prisilila v komunikacijo preko računalnikov ali drugih mobilnih zavedati prednosti in slabosti, ki jih tehnologija prinaša in slednjo naprav. S tem pa je tudi zahtevala določena znanja in znati uporabiti na načine, da z varno in pravilno uporabo kompetence. Pri pouku tujega jezika smo se poslužili tehnologije, ki je učencem na razpolago tudi pri učenju tujega komunikacije preko šolske elektronske pošte in spletnih učilnic. jezika, najdejo orodja, ki jim pomagajo priti do cilja. 2.2 Priprava gradiv Kot sta ugotovila Petroman in Petroman [2], je načrtovanje in Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed priprava gradiv pri delu na daljavo pravi izziv ne glede vrsto for profit or commercial advantage and that copies bear this notice and the full izobraževalnega zavoda. Pri pripravi gradiv za delo na daljavo citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). mora učitelj upoštevati jezikovno predznanje učencev in jih Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia usmerjati k temu, da čim bolj samostojno dosegajo cilje učnega © 2020 Copyright held by the owner/author(s). 716 načrta, pri tem pa razvijajo jezikovne sposobnosti na vseh • Arnesove interaktivne vaje: https://interaktivne- ravneh. Pomembno je, da učence pri tem vodimo po korakih in vaje.si/nemscina/wortschatz/korperteile.html, jim hkrati omogočimo, da delo opravijo v svojem ritmu in glede [6], na svoje predznanje. Tako upoštevamo načela diferenciacije in • Quizlet: individualizacije. https://quizlet.com/375343493/flashcards [7], Učni sklop, ki smo ga v času dela na daljavo obravnavali v • Quizizz: osmem razredu pri izbirnem predmetu nemščina, je bil človeško https:/ quizizz.com/admin/quiz/5c9b78369f82cb telo. Cilj, ki so ga učenci morali doseči po predelanem učnem 001a41747d/körperteile [8]. sklopu, pa je bil zmožnost samostojnega poročanja o počutju in tvorba pogovora pri zdravniku. 2.3 Digitalne kompetence Pri delu na daljavo so učenci morali biti digitalno pismeni – obvladati so morali različna področja digitalnih kompetenc, kot so: informacijska pismenost, komuniciranje in sodelovanje, izdelovanje digitalnih vsebin, varnost in reševanje problemov. [3] Pri delu na daljavo so učenci te digitalne kompetence nujno potrebovali, da so lahko dosegali zastavljene cilje. 3 KORAKI DO CILJA 3.1 Začetki dela na daljavo Slika 1. V i-učbeniku so učenci spoznali zapis in izgovorjavo Ko smo zakorakali v prvi teden dela na daljavo, smo najprej novega besedišča. [4] hoteli doseči čim več učencev. Ker so učenci delo v spletnih učilnicah že poznali, so nekateri tudi hitro našli prve informacije. Spletnih strani, ki omogočajo spoznavanje in ponavljanje Drugim pa je bilo treba posredovati osnovna navodila za vstop v besedišča, je veliko. Prednost takšnih vaj je, da jih učenci lahko elektronsko pošto in spletne učilnice. Ko je bilo to urejeno, so ponovijo večkrat, pri interaktivnih vajah pa lahko izbirajo med učenci v spletni učilnici našli predvsem navodila za ponavljanje lažjimi in težjimi nalogami, mnoge imajo tudi možnost uporabe že predelane snovi in navodila za urejanje dostopov do e-gradiv. zvočnega posnetka. Med lažje naloge spadajo naloge prepoznavanja in povezovanja. Ko to znanje usvojijo, pa si 3.2 Spoznavanje besedišča izberejo še naloge, pri katerih je potrebno besede zapisati V drugem tednu pouka na daljavo so bili učenci v spletne samostojno. Ker pri reševanju spletnih nalog učitelj procesa ne učilnice že prijavljeni in smo lahko pričeli z novo učno temo. V more neposredno preverjati, so morali učenci v dokaz pošiljati uvodnem delu so se učenci seznanili z besediščem, ki ga slike svojega dela (zaslonske slike) oz. so reševali naloge z potrebujejo za poročanje o počutju in pogovor pri zdravniku. Pri zapisovanjem besed v delovni zvezk. tem so si lahko pomagali z različnimi spletnimi orodji (kot npr. s Pri izbiri nalog je bilo potrebno upoštevati učenčevo spletnim slovarjem PONS, ki so ga že poznali), pa tudi z predznanje in učne cilje. Zato so na začetku prednjačile naloge, učbenikom in delovnim zvezkom. S pomočjo i-učbenika [4] so kot so iskanje parov in igra spomin, ki jih je občasno podpiral novo besedišče, ki je bilo v učbeniku podprto s slikovnim tudi zvočni zapis. Tako so učenci vadili najprej bralno in slušno gradivom, tudi slišali, saj je v i-učbeniku možno pri branju razumevanje, čemur so dodali še izgovorjavo. Pozneje so spremljati še zvočne zapise in s tem vaditi tudi izgovorjavo. Kot nadaljevali z vajami zapisovanja besed, ki so jih reševali tudi v osnovno orodje za doseganje tega cilja so učenci uporabili delovnem zvezku. Pravilnost zapisa določene besede so lahko učbenik, saj jim je znan in so ga vajeni. Temu so dodali še preverili s pomočjo rešitev na spletu, zaslonsko sliko njegovo spletno različico. Slika 1 prikazuje stran v učbeniku, na opravljenega dela pa so poslali učitelju v dokaz. Tako se je krog kateri je besedišče zapisano. Besede so zapisane v ednini in (spoznavanje  učenje  uporaba znanja  ponavljanje in množini, s klikom na zvočnik pa so učenci vadili še izgovorjavo. utrjevanje) zaključil z evalvacijo znanja, saj so rešitve morali Čeprav smo v šoli i-učbenik uporabljali že od začetka preveriti in napake popraviti s pisalom druge barve. šolskega leta in so bili učenci z dostopom do e-gradiv seznanjeni, Vsako izmed naštetih orodij pa ima seveda svoje prednosti in se je izkazalo, da mnogi e-gradiv do začetka dela na daljavo niso slabosti. Prednost i-učbenika je zagotovo ta, da so ga učenci že koristili. Ob začetku dela na daljavo pa so si uredili dostop do e- poznali. Prav zato so vedeli, kaj pomenijo posamezna oznake, gradiv. kje najti slovar in razlago slovnice. Tudi delovni zvezek je v elektronski obliki, a so učenci rešitve zapisovali v svoje tiskane Za utrjevanje novega besedišča so učenci uporabljali različna delovne zvezke in jih nato pregledali ter napake označili z drugo spletna orodja. Nove besede so ponavljali s pomočjo nalog na barvo. V tem primeru se je slabost dela na daljavo pokazala v naslednjih spletnih straneh: tem, da med samim delom učitelj ni mogel spremljati zapisa v • LearningApps.org: https://learningapps.org [5], delovnem zvezku in nuditi dodatne razlage, če je bila potrebna. Aplikacijo LearningApps so učenci uporabljali predvsem v prvi fazi učenja, saj so pri mnogih nalogah možnosti že dane in 717 jih morajo le prepoznati. Lahko pa so v aplikaciji izbirali tudi primerna njihovemu znanju (torej vsebujejo nekoliko težje zahtevnejše naloge, ki so zahtevale samostojen zapis (npr. zapis besedišče, kot so ga vajeni). besed v množini). Prednost Quizlet-a je ta, da lahko besedišče poljubno 3.4 Samostojen zapis oblikujemo sami. Uporabimo lahko predpripravljen kviz in ga Ko so učenci potrebno besedišče usvojili in spoznali jezikovna spremenimo glede na cilje, ki jih želimo doseči. Quizlet omogoča sredstva, so jih morali uporabiti za samostojen zapis. Pri tem so tudi različne vaje iz spoznavanja besed. Učenci so besede si lahko pomagali z vsemi razpoložljivimi sredstvi (spletom, spoznali najprej s pomočjo slik, nato pa so morali prepoznati slovarji, učnimi gradivi). Dobili so smernice za delo. Pred tem poimenovanje delov telesa na sliki. V nadaljevanju so morali smo že pri pouku spoznali nekaj spletnih slovarjev in kako naj se dele telesa na sliki zapisati, zapisati so morali še slišane besede jih uporablja, da bodo zapisi pravilni. Pri oddanih nalogah sem in se preizkusiti v testu. Besedišče pa so lahko vadili tudi s opazila, da so tisti učenci, ki so naloge oddajali redno in mi redno pomočjo dveh iger – iskanja parov in zapisa prevoda. Aplikacija pošiljali tudi ekranske slike, bili bolje informirani in natančnejši. je tako nudila nabor nalog različnih težavnostnih stopenj, ki so Ti učenci so vedeli, kje najdejo posamezna jezikovna sredstva in razvijale tako slušno kot tudi bralno razumevanje in pisno na kaj morajo biti pozorni. O tem smo se pogovarjali tudi na sporočanje. videokonferencah. Medtem ko so učenci, ki nalog niso delali Podobno velja za interaktivne vaje, kjer so imeli učenci na redno, potrebovali veliko več usmerjanja in vodenja, da jim je razpolago zbirko naslovov z nalogami različnih težavnostnih določeno nalogo uspelo opraviti. stopenj. Te so učenci že poznali, saj so jih pogosto uporabljali v preteklih letih. Pri reševanju teh nalog pa so učenci delali samostojno, za dokaz je služila le ekranska slika. 4 ZAKLJUČEK Quizizz so uporabljali predvsem za reševanje že vnaprej V času dela na daljavo se je pokazalo, da so v prednosti bili tisti priravljenih kvizov, v katere so se morali vpisati z imenom, da učenci, ki so IK tehnologijo že obvladali, poznali spletne učilnice sem lahko sledila njihovemu delu in napredku. Podoben kviz so in e-gradiva in te redno uporabljali že prej. Pri delu smo rešili tudi v Arnesovi spletni učilnici. Izkazalo se je, da pri uporabljali i-učbenik, delovni zvezek in gradiva na spletu. Quizizz-u radi sodelujejo, ker ga doživljajo kot bolj sproščeno Največji izziv za učitelja je bil najti naloge, ki so primerne obliko učenja, saj so v povratne informacije vključene zabavne predznanju in zmožnostim otrok in so v pomoč pri doseganju slike in glasovi, pa tudi tekmujejo lahko drug z drugim, kar jih še ciljev. Zato sem se v pedagoškem procesu odločila, da nekatere dodatno motivira. naloge v omenjenih aplikacijah sestavim sama. Učenci so pri 3.3 Spoznavanje jezikovnih sredstev delu morali pokazati veliko mero samostojnosti in nenazadnje tudi motivacije. Ker mnoge aplikacije ne omogočajo preverjanja Ko so učenci spoznali novo besedišče, smo nadaljevali s uspešnosti reševanja nalog, so pri nekaterih nalogah morali spoznavanjem jezikovnih sredstev in posledično tudi slovničnih pošiljati zaslonske slike dela, ki pa niso nujno pomenile, da so pravil, ki so jih učenci spoznali s pomočjo i-učbenika, utrjevali z nalogo rešili samostojno in ne po sistemu poskusov in napak ali nalogami na spletu in nalogami v delovnem zvezku. s pomočjo danih rešitev. Pravo znanje učencev se je namreč Pri delu smo vključili video posnetke na YouTubu. Tudi pokazalo šele pri vsebini in kvaliteti oddane zaključne naloge. tokrat so si učenci najprej ogledali jezikovno lažje posnetke s Menim, da še zmeraj mnogo učencev potrebuje pomoč pri transkripcijo. Nato so reševali naloge, ki so vsebovale enaka ali uporabi mobilnih naprav in spletnih orodij. Prav tako potrebujejo podobna besedila z vrzelmi. Razbrati so morali posamezne veliko usmerjanja in preverjanja, saj sicer uberejo lažjo pot, ki informacije iz posnetkov in z njimi dopolniti besedila. Ponovno jih ne privede nujno do kakovostno opravljenega dela. Zato bodo je torej šlo za prepoznavanje znanega in nato za dopolnjevanje. učenci v tem šolskem letu pri pouku v šoli redno dobivali naloge V prvem delu učnega procesa so učenci prepoznavali slušno in v spletnih učilnicah, skupaj pa jih bomo pregledali in se pisno podobo. Znana jezikovna sredstva so nato prepoznavali v pogovorili o namenu in ciljih posameznih nalog. vedno daljših in kompleksnejših besedilih, tako v i-učbeniku kot tudi v drugih e-gradivih na spletu. Vadili so bralno razumevanje in se pripravljali na samostojen zapis. V tej fazi smo z učenci LITERATURA izvedli nekaj videokonferenc preko Zoom-a, da smo preverili [1] Kondrič Horvat, V. et al. 2001.Učni načrt: izbirni predmet: razumevanje navodil in so imeli učenci možnost postavljati program osnovnošolskega izobraževanja. Nemščina. vprašanja. Kot se je izkazalo, so bili učenci videokonferenc Ljubljana: Zavod RS za šolstvo. Dostopno na veseli in so se jih v velikem številu tudi redno udeleževali. https://www.gov.si/assets/ministrstva/MIZS/Dokumenti/O Prednost posnetkov na YouTubu je ta, da pogovore slišijo, snovna-sola/Ucni-nacrti/izbirni/3- lahko vadijo izgovorjavo in spremljajo razlike med zapisom in letni/Nemscina_izbirni.pdf. izgovorjavo. Nekoliko težje pa je najti avtentične posnetke, na [2] Petroman C., Petroman I. 2013. Improving the katerih ljudje ne govorijo v narečju in hkrati dovolj počasi, da development of learning materials for open and distance jim učenci lahko sledijo. Najdeni posnetki so pogosto prirejeni learning. In Procedia – Social and Behavioral Sciences 83 za učenje tujega jezika. Podobno je tudi z besedili. Avtentična (Elsevier). Dostopno na besedila (zapisi, članki, tuje spletne strani ipd.) velikokrat https://www.sciencedirect.com/science/article/pii/S187704 vsebujejo veliko novega besedišča in če slednje ni podkrepljeno 2813011245. s primernim slikovnim gradivom, postane za učence pretežko in [3] Carretero, S. Vuorikari, R. in Punie, Y. 2017. Okvir jim pade motivacija. Zato je pomembno najti gradiva, ki so digitalnih kompetenc za državljane. Osem ravni doseganja 718 kompetenc in primeri rabe. Ljubljana: Zavod RS za [6] Interaktivne vaje: https://interaktivne- šolstvo. vaje.si/nemscina/wortschatz/korperteile.html [4] Motta, G. 2017. Magnet 2. Ljubljana: Rokus Klett. [7] Quizizz: https://quizizz.com/admin Dostopno na: https://folio.rokus- [8] Quizlet: https://quizlet.com/375343493/flashcards klett.si/?credit=MAGNET2UC&pages=70-71. [5] LearningApps: https://learningapps.org. 719 Uporaba spletnega orodja Classkick pri izobraževanju na daljavo Using Classkick instructional tool during distance learning Anita Zupanc OŠ dr. Janeza Mencingerja Bohinjska Bistrica Savska c. 10 4264 Bohinjska Bistrica, Slovenija anita.zupanc@osbohinj.si POVZETEK dostop do informacij in povezovanje v realnem času, omogoča učinkovito obdelavo in predstavitev podatkov, uporabo e-gradiv IKT postaja vedno bolj pomemben del šolskega procesa in je ter podpira vseživljenjsko učenje [3]. Vsi učni načrti za osnovno vključen tudi v vse učne načrte. Pri izobraževanju na daljavo v šolo vsebujejo poglavje o uporabi IKT tehnologije pri pouku. času epidemije Covid-19 je ta element postal ključen, saj je Učni načrt za predmet angleščina tako kot enega od ciljev predstavljal most med učitelji in učenci. V luči dejstva, da se je uporabe informacijske tehnologije navaja: “komuniciranje in glede na analizo izobraževanja na daljavo največ učiteljev sodelovanje na daljavo” [4]. V mesecu marcu, z razglasitvijo posluževalo pisnih navodil za delo ter so kot dokaz o zanju epidemije, pa smo se učitelji in učenci znašli v situaciji, ko je učencev v veliki meri uporabljali rešene liste, članek predstavlja IKT tehnologija postala edini način za komunikacijo. V analizi eno od spletnih orodij, ki omogoča dajanje navodil in nalog na izobraževanja na daljavo Zavod za šolstvo navaja, da se je največ malo drugačen način, hkrati pa s pripravo nalog za učence in več učiteljev (kar 84,5 %) posluževalo pisnih navodil za delo [1]. možnostmi dajanja povratnih informacij učiteljem olajša delo. Prav tako je med predmetnimi in srednješolskimi učitelji največ KLJUČNE BESEDE od njih (15,2 % predmetnih in 16,7 % srednješolskih učiteljev) kot dokaz o znanju uporabljalo rešene učne liste. Classkick, IKT, izobraževanje na daljavo, spletno orodje Skupaj s sodelavkami v aktivu učiteljev angleškega jezika ABSTRACT smo odkrile brezplačno spletno orodje Classkick [2], ki nam je olajšalo pripravo pisnih navodil tako, da smo jim dodale IT has increasingly proved as one of the most important for parts posnetke, povezave in sličice, pa tudi pripravo gradiv za dokaz o of the school process and is included in all curricula. Distance zanju in oblikovanje povratne informacije o znanju za učence. learning during the Covid-19 epidemic has further increased the need to use IT as it proved to be the only means of communication between teachers and students. In light of the fact 2 SPLETNO ORODJE CLASSKICK that most teachers used written work instructions during the epidemic and worksheets as an evidence of learning, the article Spletno orodje Classkick najdemo na spletni strani presents one of the instructional tools available, namely the https://classkick.com. Tam se prijavimo kot učitelj z imenom in Classkick tool. It enables different ways of preparing work priimkom. Treba je poudariti, da je orodje sicer v angleškem instructions for students as well as making different exercises and jeziku, a je precej preprosto, saj v večini uporablja ikone, nudi pa providing feedback. tudi kratke videoposnetke za pomoč novim uporabnikom, kjer so predstavljene osnovne funkcije orodja. KEYWORDS Deluje po principu pripravljanja »nalog« s strani učitelja za Classkick, IT, distance learning, instructional tool učence. Te naloge niso nujno samo naloge, ki jih učenci rešujejo, ampak se lahko uporabijo tudi kot navodila za delo ali razlaga za učence. Naloge učencem dodelimo tako, da jim posredujemo 1 UVOD kodo za nalogo. Učenci se za uporabo spletnega orodja v orodje IKT tehnologija je v zadnjem času eden od ključnih gradnikov ne potrebujejo prijaviti, vpišejo samo posredovano kodo in svoje pouka. Polega razvijanja računalniške pismenosti je uporaba IKT ime (ki ga bo učitelj videl pri pregledovanju nalog). Ko učenci tehnologije smiselna tudi kot motivacijski moment, omogoča naloge opravijo (ali si jih v primeru razlage ogledajo), učitelj vidi njihova imena ter rešitve. Nato lahko učencem na različne načine poda povratno informacijo, ki jo le-ti vidijo, ko se po vpisu kode v spletno orodje ponovno prijavijo s svojim imenom. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full 2.1 Priprava nalog citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). Orodje Classkick od učencev zahteva minimalno znanje Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia programa (npr. kako napisati odgovor, kako spremeniti barvo in © 2020 Copyright held by the owner/author(s). 720 velikost besedila, kako narisati črto, kako prenesti sličico, kako posneti odgovor). Orodje nam ob prvi prijavi ponudi predlogo naloge za učence, skozi katero se naučijo uporabe orodja. Classkick ponuja tudi predloge različnih nalog učiteljev, ki jih lahko kopiramo in uredimo, lahko pa začnemo s prazno predlogo in nalogo pripravimo sami. Obstaja tudi tretja možnost, t. j. izbira predloge iz računalnika, ki pa mora biti v formatu PDF. Pri izdelavi naloge imamo v orodni vrstici več možnosti (glej Slika 1, po vrsti od leve proti desni): - osveži, - povečaj ali pomanjšaj, - uporabi miško, - uporabi svinčnik, - uporabi flomaster, - uporabi radirko, - vstavi okvirček za pisanje besedila, Slika 2. Primer pripravljene naloge - nariši ravno črto, - vstavi povezavo, - vstavi sliko (slikaj ali izberi iz naprave), - vstavi zvočni posnetek (posnemi ali izberi iz naprave), - vstavi sliko, ki jo uporabnik lahko premika, - vstavi kvadratek, v katerega uporabnik vpiše odgovor, in dodaj pravilno rešitev/ve, da bo program sam označil, ali je rešitev pravilna ali ne, - vstavi možnost izbire med petimi odgovori in označi pravilno rešitev, da bo program sam označil, ali je rešitev pravilna ali ne, - vstavi vnaprej pripravljeno nalepko (uporabnik jih oblikuje sam; npr. odlično, bravo, še enkrat preglej), ki nam pride prav predvsem pri pripravi povratne informacije, - spremeni ozadja, - število točk (določimo, koliko točk lahko učenec doseže na posameznem listu; točk ni potrebno dodeljevati, če ne želimo). Slika 3. Primer pripravljene razlage 2.2 Reševanje nalog Slika 1. Orodna vrstica za urejanje naloge Ko učitelj dokonča nalogo, nastavi t. i. »roster« (razpored dela), s katerim pridobi kodo, ki jo posreduje učencem. Brez posebne Nalogo razdelimo na več listov, ki jih lahko po želji dodajamo prijave v program, le z uporabo svojega imena (in priimka) lahko ali brišemo. učenec reši nalogo (ali si ogleda razlago). Vsak učenec ima Slika 2 prikazuje primer pripravljene naloge, kjer je učitelj možnost dvigniti roko (ikona roke), ki je uporabno orodje pripravil navodilo za reševanje naloge, slušni posnetek ter nalogo, predvsem pri pri pouku v šoli. kjer učenci označijo pravilno sličico. Učenci imajo na voljo zelo podobno orodno vrstico za Slika 3 prikazuje primer razlage, kjer je poleg zapisane reševanje nalog, kot jo ima na voljo učitelj, z izjemo možnosti za razlage učitelj pripravil tudi povezavo na spletno stran z dodatno ustvarjanje različnih vrst nalog. razlago in slušni posnetek. 2.3 Vrednotenje nalog Ko učenci nalogo rešijo, učitelj lahko rešene naloge pregleda. Izbere si lahko pogled, kjer vidi vse učence, ki so nalogo reševali. V filtrih ima več možnosti pogleda, od skrivanja učencev, ki z nalogo še niso začeli, ampak so jo samo odprli, do skrivanja imen učencev, pa možnost, ali učenec vidi doseženo število točk ali ne. Prav tako med filtri nastavimo možnost medvrstniškega vrednotenja in pomoči, ki je prav tako dodana vrednost orodja. Ko učitelj odpre pogled za vsakega posameznega učenca, ima več možnosti za dajanje povratne informacije: 721 - uporaba nalepk (ikona zvezdice), ki si jih prej pripravi različne uporabe; od razlage, do utrjevanja, preverjanja znanja in ali pa izbere vnaprej pripravljene (glej slika 4), celo dela v skupinah, saj omogoča tudi medvrstniško vrednotenje - dodeljevanje točk (če smo uporabili naloge izbire in pomoč. pravilnega odgovora ali vstavljanja odgovora, pri Hkrati Classkick dviguje motivacijo učencem, ki so v poplavi katerih smo predhodno označili možne pravilne pisnih navodil in posnetkov orodje videli kot svež veter, saj jim odgovore, program točke dodeli sam) omogoča, da izrazijo tudi sebe in se igrajo z barvami, velikostmi, - pisanje povratne informacije (glej slika 4, zeleno oblikami. Všeč jim je bila povratna informacija, ki so jo z besedilo), veseljem pričakovali. - snemanje posnetka s povratno informacijo (na ikoni mikrofona). VIRI IN LITERATURA [1] Analiza izobraževanja na daljavo v času epidemije Covid- 19 v Sloveniji. Delno poročilo, julij 2020, 2020. Ljubljana: Ministrstvo za šolstvo in šport: Zavod RS za šolstvo (spletna izdaja, dostopna na https://www.zrss.si/strokovne- resitve/digitalna-bralnica/podrobno?publikacija=297) [2] Classkick, dostopen na https://classkick.com [3] Kreuh, N. 2011. Izhodišča standarda e-kompetentni učitelj, Slika 4. Primer povratne informacije ravnatelj in računalnikar. Ljubljana: Ministrstvo za šolstvo in šport: Zavod RS za šolstvo (el. knjiga, dostopna na https:/ www.zrss.si/pdf/esolstvo-standard.pdf) 3 ZAKLJUČEK [4] Učni načrt. Program osnovna šola. Angleščina, 2016. Spletno orodje Classkick se je v praksi izkazalo kot zelo Ljubljana: Ministrstvo za šolstvo in šport: zavod RS za šolstvo. uporabno in kvalitetno orodje za izobraževanje na daljavo, saj je z vsemi zgoraj navedenimi možnostmi dovolj fleksibilno za 722 Razredna problematika in delo na daljavo Class issues and teleworking Astrid Žibert OŠ Gradec, Litija Bevkova ulica 3 1270 Litija, Slovenija astrid.zibert@osgradec.si POVZETEK nekaterih predmetih je bilo podajanje snovi lažje, učenci so lahko bolj ali manj samostojno predelali učno snov, pri nekaterih Tudi pri delu na daljavo je potrebno reševati težave učencev, saj predmetih pa so potrebovali tudi razlago učitelja. Ravno tako so učenci pri učenju ter sodelovanju s sošolci in sošolkami nekateri učenci potrebovali tudi pomoč pri soočanju z nastalo potrebujejo vodenje in včasih tudi pomoč. V okviru razrednih ur, situacijo in organizaciji svojega dela. Tudi razredne ure so ki so bile izpeljane na daljavo na temo medsebojnih odnosov v potekale na čisto drugačen način, preko video konferenc. V razredu in samostojnim šolskim delom učencev, je bil pripravljen letnem delovnem načrtu za izpeljavo razrednih ur je bila za vprašalnik s pomočjo spletnega orodja Google Docs, ki so ga mesec marec izbrana tema medsebojni odnosi in moje šolsko učenci rešili anonimno. S pomočjo tega vprašalnika lahko delo. Kljub temu, da učenci niso bili v šoli, sem se odločila, da ugotovimo, kako se učenci med seboj razumejo in kakšne težave bomo na razrednih urah čas namenili izbrani temi. se med samim učenjem in delom na daljavo pojavljajo. Ugotovitve pri analizi odgovorov vprašalnika predstavljajo osnovo za izpeljavo razredne ure na omenjeno temo. 2 PRIPRAVA NA RAZREDNO URO KLJUČNE BESEDE Pri izbrani temi razrednih ur po navadi izvedem anketo, ki jo učenci rešijo v šoli, sama pa jo potem analiziram v programu Delo na daljavo, Google Docs, razredna ura Excell ter rezultate predstavim učencem na razredni uri in ABSTRACT staršem na roditeljskem sestanku. V letošnjem šolskem letu pa takšen način pridobivanja podatkov učencev ni bil mogoč, zato It is also necessary to solve students' problems when teleworking, sem se določila, da bom podatke o šolskem delu učencev in as students need guidance and sometimes help in learning and njihovih medsebojnih odnosih pridobila preko aplikacije Google cooperating with their classmates. As part of the class meetings, Docs. which were extramural courses on the topic of interpersonal relationships in the classroom and independent schoolwork of 2.1 Aplikacija Google Docs students, a questionnaire was prepared using the online tool Google Docs, which students solved anonymously. With the help Google Docs je brezplačno spletno orodje, ki jo ponuja Google of this questionnaire, we can find out how students can work with v okviru svoje storitve Google Drive. V okviru spletne aplikacije each other and what problems arise during the learning by Google Dokumenti, ki delujejo tudi na mobilnih napravah za teleworking. The findings in the analysis of the answers to the Android, iOS, Windows, BlackBerry in kot namizna aplikacija v questionnaire represent the basis for conducting a class lesson on Googlovem ChromeOS-u. Aplikacija je združljiva z datotekami the mentioned topic. datotek Microsoft Office. Uporabnikom omogoča ustvarjanje in urejanje datotek v spletu ob sodelovanju z drugimi uporabniki v KEYWORDS realnem času [1]. Uporaba aplikacije se mi je zdela smiselna, saj se učencem ni bilo potrebno posebej prijaviti in ustvariti Telework, Google Docs, class meeting uporabniških imen in gesel, da so lahko rešili vprašalnik. 1 DELO NA DALJAVO 3 IZDELAVA VPRAŠALNIKA Učenci in učitelji smo bili letos primorani precej spremeniti svoj način dela z učenci. Nenadoma delo v razredu v živo ni bilo več 3.1 Izbor vprašanj mogoče, učitelji smo morali pripraviti pouk na daljavo. Pri Vprašanja, ki so bila vsebovana v vprašalniku sem pripravila v sodelovanju s šolsko svetovalno službo. Pomembno je bilo predvsem to, da so razumljiva in da bodo odgovori učencev Permission to make digital or hard copies of part or all of this work for personal or pokazali, kako se učenci počutijo v razredu, kako med seboj classroom use is granted without fee provided that copies are not made or distributed sodelujejo in kakšno je njihovo šolsko delo doma. Pripraviti je for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must bilo potrebno sociometrijo razreda [2]. Vprašanja so bila be honored. For all other uses, contact the owner/author(s). razdeljena na štiri dele. Prva del so bile trditve, ki so opisovale Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia odnose med sošolci in sošolkami, učenci pa so morali trditve © 2020 Copyright held by the owner/author(s). 723 označiti, v kolikšni meri veljajo zanje. Drugi del je bil zasnovan na enak način, učenci pa so ocenjevali trditve v zvezi s poukom in njihovim šolskim delom, ki ga opravljajo doma. Tretji in četrti del pa sta bila osredotočena na prepoznavanje pozitivnih in negativnih interakcij med posameznimi učenci. Rezultat tretjega in četrtega dela je dal odgovor o učencih, ki so v razredu zelo dobro sprejeti in ustrezno sodelujejo v skupini in tistih učencih, s katerimi je sodelovanje oteženo iz tega ali onega razloga. 3.2 Vnos vprašanj v Google Docs Če želimo pripraviti vprašalnik v spletni aplikaciji Google Docs, moramo imeti uporabniško ime in geslo za račun Google. Kot je prikazano Slika 83 med možnostmi na levi strani izberemo Obrazec. Slika 85: Vpis vprašanja Na levi strani v stolpec zapišemo trditve, v desni stolpec pa številke od 1 do 5, da bodo lahko učenci označili, do katere mere trditev zanje velja. Ker je pomembno, da izpolnijo vsa polja, pri vprašanju desno spodaj označimo Zahtevaj odgovor v vsako vrstici. Na enak način sem pripravila tudi sklop drugih trditev na temo moje šolsko in domače delo. Novo vprašanje dodamo tako, da na desni strani kliknemo na oznako + (Slika 86). Slika 83: Izbira Obrazci V desnem spodnjem kotu označimo plus in ustvarimo nov obrazec. Na Slika 84 lahko vidimo tudi kako lahko vprašalnik poimenujemo, pod naslovom pa zapišemo navodila za učence. Slika 86: Dodajanje novega vprašanja Za 7. razred sem želela narediti tudi sociogram, zato sem v Google Docs obrazec dodala še dve vprašanji (Slika 87). Pri prvem vprašanju so morali učenci na seznamu označiti tri sošolce ali sošolke, s katerimi najraje sodelujejo pri šolskem delu. Takšne vrste vprašanj pripravimo tako, da na desni strani označimo, da gre za vprašanje s potrditvenimi polji. Kot možnosti izbire pa zapišemo imena in priimke učencev. Slika 84: Poimenovanje vprašalnika Po poimenovanju vprašalnika in zapisu navodil za učence je potrebno pripraviti vprašanja. V mojem vprašalniku sta prvi dve vprašanji sestavljeni iz desetih trditev, za katere morajo učenci oceniti v kolikšni meri veljajo zanje. Takšna vprašanja pripravimo tako, da preimenujemo vprašanje in kot tip vprašanja izberemo Mreža z vprašanji z izbirnimi odgovori (Slika 85). Slika 87: Priprava vprašanja s potrditvenimi polji Na enak način sem pripravila tudi vprašanje, pri katerem so morali učenci označiti, s katerimi učenci težko sodelujejo pri šolskem delu. 724 Ko so bila vsa vprašanja vnesena v spletni obrazec, sem učencem posredovala povezavo do vprašalnika. Povezavo lahko pošljemo tako, da desno zgoraj kliknemo na vijolično obarvano polje Pošlji ter vpišemo e-naslove učencev (Slika 88). Če vsi učenci nimajo e-naslovov, lahko povezavo do vprašalnika dodamo v spletno učilnico. Povezavo preprosto kopiramo in prilepimo. Slika 88: Pošiljanje povezave do ankete Slika 91: Prenos odgovorov Vprašalniku lahko pred pošiljam še spremenimo barvo. To Kot je že omenjeno, se odgovori prenesejo v datoteki s naredimo tako, da v desnem zgornjem kotu kliknemo na paleto, končnico .csv, zato, če nismo vešči spreminjanja zapisa v kar nam omogoči izbiro poljubne barve. Tu lahko izberemo tudi datoteki, si odgovore raje natisnemo in sami vnesemo v Excell, slog pisave. kjer jih obdelamo in ugotovitve predstavimo z grafi ali povprečjem. 3.3 Izpolnjevanje vprašalnika Učenci so po prejemu povezave na vprašalnik odgovorili na 4 PREDSTAVITEV REZULTATOV vprašanja. Vprašalnik so rešili vsi učenci v razredu. Bil je anonimen, lahko pa bi bilo dodano tudi vprašanje, pri katerem bi Odgovore učencev si lahko ogledamo že v samem obrazcu pod morali vpisati svoje ime in priimek, vendar imam občutek, da zavihkom Odzivi, Povzetek (Slika 92). potem ne bi dobila iskrenih odgovorov. Mi, kot kreatorji Obrazca v Google Docs, lahko vedno preverimo, koliko učencev je na vprašalnik že odgovorilo. Pri zavihku Odzivi se pokaže število izpolnjenih obrazcev (Slika 89). Na ta način lahko tudi ugotovimo, ali so vsi učenci rešili vprašalnik. Slika 89: Štetje odzivov Ko na vprašalnik odgovorijo vsi učenci, lahko onemogočimo nove odgovore. To storimo tako, da pod zavihkom Odzivi označimo, da obrazec ne sprejema več odgovorov. Kako to označiti, je prikazano na Slika 90. Slika 92: Pregled odgovorov Rezultate uporabimo pri izpeljavi razredne ure na daljavo, kjer lahko učenci še ustno dopolnijo oziroma razložijo svojo izbiro odgovorov. Na razredni uri in roditeljskem sestanku predstavimo zgolj prva dva dela vprašalnika. Na zadnji dve vprašanji lahko rezultat podamo osebno otroku ali njegovim staršem oziroma skrbnikom. Slika 90: Zaključek reševanja spletnega obrazca Pod tem zavihkom lahko pregledamo tudi povzetek odgovorov učencev na vprašanja. Odgovore si lahko prenesemo tudi na računalnik, če kliknemo na tri pike desno zgoraj in izberemo Prenos odgovorov (Slika 91). Odgovori bodo preneseni v .csv datoteki. 725 5 ZAKLJUČEK Pri uvedbi pouka na daljavo je bilo potrebno spremeniti način vodenja razreda in pridobiti informacijo o delu učencev na daljavo ter njihovih medsebojnih odnosih ter narediti sociogram. V živo ni bilo moč dobiti odgovorov na moja vprašanja, zato sem s odločila, da uporabim aplikacijo Obrazci Google Docs. Pridobivanje odgovorov učencev na ta način je bil edini smiseln, saj z učenci nisem imela kontakta v živo. Hkrati pa je bilo to tudi za njih nekaj novega, zato so imeli nekaj več motivacije pri odgovarjanju na vprašanja. Slika 93: Rezultati pri tretjem vprašanju VIRI IN LITERATURA [1] Wikipedia. Google Docs (pridobljeno 10. 8. 2020). DOI= Učitelj razrednik pa dobi pri odgovorih na zadnji dve https://en.wikipedia.org/wiki/Google_Docs vprašanji (Slika 93) vpogled, katerim učencem je potrebno pri sodelovanju s sošolci pomagati. S temi učenci lahko pri [2] KOŠIR, Katja. 2011 . Pregled preučevanja vrstniških nadaljnjem delu več sodelujemo in jim pomagamo pri boljšem odnosov pri šolskih otrocih in mladostnikih. Anthropos 1-2 (221-222) 2011, str. 111-140 (pridobljeno 11. 8. 2020). vključevanju v skupino. DOI= http://www.dlib.si/stream/URN:NBN:SI:DOC- BNQ9EFOI/40c692c8-7793-4c12-a600- 905e7d476f7b/PDF 726 Poučevanje programiranja s snovanjem iger Teaching programming through game design Mateja Bevčič, Jože Rugelj University of Ljubljana, Faculty of Education Kardeljeva ploščad 16 1000 Ljubljana, Slovenija mateja.bevcic@pef.uni-lj.si, joze.rugelj@pef.uni-lj.si POVZETEK KEYWORDS Potreba po znanju programiranja se v svetu povečuje iz dneva v Programming, game design based learning dan. Zmožnost algoritmičnega razmišljanja in pisanja kode postaja bistvena veščina, saj je povezana z logičnim sklepanjem ter sposobnostjo reševanja problemov, in je pri iskanju zaposlitve 1 UVOD vedno bolj zaželena. Na področju računalništva primanjkuje Pomen igre za otrokovo učenje so izpostavljali že vodilni ustrezno usposobljenega osebja, zato je cilj projekta psihologi prejšnjega stoletja in ji pripisovali eno Coding4Girls spodbujati otroke v zadnjih letih osnovne ter v najpomembnejših vlog pri razvoju življenjsko pomembnih začetnih letih srednje šole k učenju programiranja, saj mnogo veščin, ne glede na starost ali razvojno stopnjo otroka. Otrok se učencev v tem odbobju izgubi zanimanje za računalništvo. hitro prilagaja novim okoliščinam, z lahkoto obvladuje Projekt želi za programiranje in nadaljevanje študija na področju spremembe in odkriva osnovne koncepte iz resničnega sveta [1]. računalništva navdušiti predvsem dekleta in s tem zmanjšati Na področju izobraževanja prihajajo vedno bolj v ospredje neenakost med spoloma, saj ženske predstavljajo le majhen delež aktivne oblike učenja, kjer se korenito spremenita vlogi učitelja zaposlenih na tem področju. V prispevku si bomo podrobneje in učenca. Pri tem je naloga prvega priprava primernega okolja ogledali pristop k učenju programiranja s snovanjem iger, in izzivov, usmerjanja in podajanja povratnih informacij predstavili pa bomo tudi pripravljene učne scenarije, ki jih lahko učencem, naloga učenca pa razmišljanje, vrednotenje ter učitelji uporabijo in jih po želji prilagajajo lastnim potrebam. samostojna gradnja znanja, pri čemer mu je lahko v veliko pomoč tudi informacijsko-komunikacijska tehnologija (IKT) [2]. KLJUČNE BESEDE Programiranje, učenje s snovanjem iger 2 UČENJE S SNOVANJEM IGER ABSTRACT Wu in Wang [3] opredeljujeta učenje s snovanjem iger (angl. The need for programming skills is growing day by day in the game design based learning) kot učni pristop, pri katerem world. The ability to think algorithmically and write code is učence spodbujamo k snovalskim odločitvam [4] z namenom becoming an essential skill as it is linked to logical thinking and razvijanja svojih lastnih ali spreminjanjem obstoječih iger na problem solving skills and is increasingly desirable when looking osnovi izbranega okvira za razvoj iger. Učinkovitost omenjenega for a job. There is a lack of appropriately qualified personnel in pristopa za poučevanje in učenje so prepoznali tudi številni the field of computer science, which is why the Coding4Girls raziskovalci. Kafai [5] trdi, da je učenje najbolj učinkovito, v project aims to encourage children in the last years of primary kolikor so učenci vključeni v postopek snovanja, saj le-to and early secondary school to learn programming, as many spodbuja njihovo razmišljanje in učenje, zlasti če snujejo nekaj students lose interest in computer science during this time. The osebnega in smiselnega. project aims to inspire girls to program and continue their studies Integracija učenja s snovanjem iger se uspešno uporablja v in the field of computer science in order to reduce gender številnih disciplinah [6]. Čeprav je pristop najbolj razširjen na inequality, as women represent only a small percentage of the področju računalništva, zlasti programiranja, konceptualnega workforce in this field. In this paper we will take a closer look at razmišljanja, kompetenc za delo z IKT in umetno inteligenco, pa the game design based learning approach and present prepared lahko najdemo tudi primere z drugih področij, kot so jezikovana learning scenarios that can be used and adapted by teachers as pismenost, oblikovanje ter tudi umetnost [3], [4], [7]. Za učitelje they wish. pa je bistvenega pomena, da je pristop dokazano učinkovit za poučevanje digitalnih kompetenc [6]. Permission to make digital or hard copies of part or all of this work for personal or 2.1 Učne teorije classroom use is granted without fee provided that copies are not made or distributed V tem poglavju si bomo ogledali številne učne teorije, ki for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must podpirajo uporabo učenja s snovanjem iger v izobraževalnih be honored. For all other uses, contact the owner/author(s). okoljih. Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 727 2.1.1 Konstruktivizem omenjenih učnih teorij in zato predstavlja odlično izhodišče za Piagetova konstruktivistična teorija učenja pravi, da morajo biti učenje programiranja. Pri tem pomaga tudi dejstvo, da je igranje učenci aktivni ustvarjalci v procesu pridobivanja znanja ter iger vedno bolj popularno in si veliko učencev želi svojo igro tudi poudarja pomen razumevanja in znanja o svetu in okolju, kjer izdelati. Pri tem morajo skozi zahteven postopek od osnovne naše izkušnje in ideje sodelujejo pri oblikovanju tega znanja [8]. ideje do razčlenitve na manjše dele in povezave v smiselno celoto. Duffy and Jonassen [9] kot bistvem pojem konstruktivizma Za pomoč imajo na voljo učitelja in vrstnike, vseeno pa igro navajata še sodelovanje in socialna pogajanja, saj ponujata oblikujejo sami in imajo na koncu svoj lasten izdelek, kar jih še možnosti za razvijanje novega razumevanja s pomočjo razprav, posebej motivira. kjer lahko učenci spoznajo še stališča. Učenci v procesu snovanja iger komunicirajo s svojimi učitelji, vrstniki in kontekstom, zato takšno učno okolje zagotavlja ustrezna pogoje za proces 3 PROJEKT CODING4GIRLS oblikovanja znanja [10]. Coding4Girls je projekt, ki ga financira Evropska unija v 2.1.2 Območje bližnjega razvoja programu Erasmus+. Nastal je z željo vzbuditi večje zanimanje deklet za izobraževanje na področju računalništva, saj se za to Koncept območja bližnjega razvoja je opredelil Vigotsky [11], ki področje tradicionalno zanimajo predvsem fantje. V projektu se poudarja vlogo odraslega človeka ali izkušenejšega vrstnika v trudimo odpravljati napačne predstave o vlogi žensk na področju razvoju učenca. Pri snovanju iger imajo učenci možnost računalništva in zmotno prepričanje o njihovih manjših sodelovanja v skupinah, kjer si lahko pomagajo, skupaj sposobnostih za računalniško programiranje. Glavni cilj projekta oblikujejo igre in razvijajo dodatne kompetence [6], pri čemer je ozaveščanje deklet o širokem naboru možnosti, ki jih področje imajo tudi pomoč učitelja za nasvete in usmeritev. računalništva in programiranja ponuja za profesionalni in osebni 2.1.3 Konstrukcionizem ravzoj ter priprava na nadaljnje izobraževanje na tem področju. Papertova konstrukcionistična teorija poudarja, da se učenci Pri tem seveda ne izključujemo fantov, saj je tudi spodbujanje največ naučijo, ko sami gradijo svoje znanje [12]. Teorija enakosti med spoloma pomemben cilj projekta [16]. zagovarja dve bistveni predpostavki – prva je miselna konstrukcija znanja, do katere pride preko izkušenj iz resničnega 3.1 Pričakovani rezultati sveta, druga pa zagovarja, da lahko učenci učinkoviteje ustvarijo V tem razdelku so predstavljeni rezultati projekta Coding4Girls. novo znanje z izdelavo izdelka, ki je zanje osebno pomemben [3]. Igra ima za učence vlogo artefakta in je po mnenju Caportona 3.1.1 Metodološki okvir za reševanje problemov [13] primerna za konstrukcionistično učenje, saj so postale igre Pripravili smo metodološki okvir, ki temelji na snovalskem pri mladih zelo priljubljene, kar pomeni, da je postopek razmišljanju (angl. design thinking) in mlade spodbuja k izbiri oblikovanja le-teh zanje vznemirljiv in pomemben. poklicne poti na področju računalništva. Okvir bo učence spodbudil, da si pred oblikovanjem podrobne rešitve problema 2.1.4 Trialoško učenje ustvarijo širšo sliko ter razmišljajo o tem, kako lahko digitalna Za trialoško učenje je bistvenega pomena interakcija, do katere tehnologija pomaga reševati probleme iz vsakdanjega življenja pride med ustvarjanjem konkretnih artefaktov. Aktivnosti so [16]. organizirane tako, da učenci v obliki sistematičnega procesa med seboj sodelujejo in razvijajo nek artefakt na osnovi skupnega 3.1.2 Spodbujanje razvoja programerskih spretnosti s znanja, npr. ideje, pravila, cilje ali igro [14]. Vlogo artefakta ima pomočjo izobraževalnih iger lahko tudi računalniška igra, saj jo učenci oblikujejo od začetne Učence in dijake med 10. in 16. letom starosti želimo spodbujati ideje ter jo skupaj izboljšujejo z upoštevanjem različnih k sodelovanju v programerskih aktivnostih s pripravljenimi pogledov. Različna IKT orodja (npr. Google Drive) omogočajo aktivnostmi. Le-te si sledijo po težavnosti, od lažjih do težjih, ki takojšnje deljenje idej in nadaljevanje dela, kar lahko izboljša so namenjene predvsem uspešnejšim učencem ( low entry – high ustvarjanje novega znanja in vpliva na nadaljnje delo drugih ceiling approach) [17]. Učenci tako dobijo delno rešene naloge, učencev [15]. ki jih morajo sami dokončati v vizualnem programskem jeziku Snap! 2.1.5 Problemsko učenje Problemsko učenje poudarja uporabo problemov iz resničnega 3.1.3 Izobraževalne vsebine za učitelje sveta in proces skupinsega odkrivanja pri učenju, pri čemer je Pripravili smo 22 učnih scenarijev, ki omogočajo integracijo vloga učitelja zagotoviti ustrezna učna gradiva in vire [6], predlaganega pristopa s snovalskim razmišljanjem in učenja s obenem pa je pomembno, da so učenci čim bolj samostojni. Pri pomočjo izobraževalnih iger v šolsko prakso [16]. Učni scenariji snovanju iger gredo skozi različne faze – izdelava prototipa (faza so v pisni obliki na voljo na spletni strani projekta1 v angleškem izdelave), izvedba (faza konstrukcije) in evalvacija igre in slovenskem jeziku ter v jezikih vseh ostalih partnerjev v (prehodna faza) [3]. projektu. Na YouTube kanalu2 pa so objavljeni tudi videovodiči Pristop učenja s snovanjem iger, ki smo ga uporabili v okviru s podrobnejšo razlago učnih scenarijev v angleščini. projekta Coding4Girls, zajema veliko elementov zgoraj 1 Spletna stran projekta Coding4Girls: 2 YouTube kanal projekta Coding4Girls: https://www.coding4girls.eu/ https:/ www.youtube.com/channel/UC0DEdwkV9PsJ4Fb70MA JQrg 728 3.2 Učni scenariji aritmetičih operatorjev za računanje. Aktivnosti smo skušali povezati s problemi iz resničnega sveta Učitelj lahko predstavi tudi rešitev s kot so npr. pobiranje odpadkov in onesnaževanje zraka. Pred for zanko. pripravo učnih scenarijev smo tudi raziskali, kakšne so 11. Mačje Spoznavanje zanke »ponavljaj dokler« preference deklet pri igranju iger. Ugotovili smo, da imajo zavetišče ter operatorjev za primerjanje dekleta rada igre vlog [18] ter igre z raziskovanjem [19], rada vrednosti. svoj lik urejajo [20], motivira jih zgodba v ozadju [21] in Uporaba naključnega premikanja in povratne informacije [22], v igri pa so dekletom pomembni tudi naključne hitrosti likov, kombinacija izzivi in zabava med igranjem [23], [24]. 12. Lovljenje dogodkov za začetek s klikom miške Pripravljeni učni scenariji se delijo na dva dela: v prvem delu zdrave hrane ali pritiskom na tipko, opcijska učenci v enem scenariju spoznajo po en programerski koncept, v uporaba spremenljivke in pogojnega drugem delu pa se koncepti prepletajo. Učitelji lahko uporabijo stavka za preprečevanje začetka igre. predlagani vrstni red scenarijev ali pa ga po želji priredijo. Prav Načrtovanje dialogov in aktivnosti tako lahko priredijo aktivnosti ali dodajo svoje naloge. Scenariji 13. Sestavi zgodbo likov v zgodbi, pošiljanje in vsebujejo specifikacijo pričakovanega predznanja, splošne ter prejemanje obvesil za izvedbo specifične učne cilje, koncepte, pričakovane rezultate, navodila dialogov med liki. za izvedbo aktivnosti po korakih, vprašanja za spodbujanje 14. Onesnažen Uporaba sporočil s klikom na lik za razprave ter dodatne naloge za sposobnejše učence [17]. zrak paralelno izvajanje dogodkov, risanje Pripravili smo tudi navodila za učence za posamezno aktivnost, kroga. ki učencem pomagajo pri samostojnem reševanju nalog. Uporaba neskončne zanke za premikanje lika, obračanje lika za 3.2.1 Seznam učnih scenarijev 15. Ulovi miš naključno število stopinj, uporaba Tabela prikazuje seznam učnih scenarijev in učne cilje, s časovnika za konec igre. katerimi se učenec pri aktivnosti sreča prvič. Lažji scenariji so v Uporaba spremenljivke za določanje 1. delu (1 – 12), zahtevnejši pa v drugem (13 – 21). 16. Kupovanje cene izdelka, preverjanje vrednosti hrane za piknik spremenljivke in prirejanje njene Tabela 1 Seznam učnih scenarijev vrednosti glede na potek igre. Ime aktivnosti Učni cilji 17. Računanje Spoznavanje menjave ozadja in obleke lika s pomočjo spremenljivke. 1. Uvod v okolje Seznanjanje z vizualnim programskim Uporaba zanke »čakaj dokler« Snap! jezikom Snap!, dodajanje in urejanje lika in ozadja. 18. Recikliranje spremenljivka ne doseže določene vrednosti. 2. Lik oživi Sestavljanje kode za premikanje in govorjenje lika. 19.1 Zaigraj na Ustvarjanje melodije s sestavljanjem 3. Premikanje po Premikanje po x in y osi ter zanka klavir 1* zaporedja tonov. odru ponovi x krat. 19.2 Zaigraj na * Učitelj uporabi eno ali drugo 4. Menjava obleke klavir 2* aktivnost. in obrat Spreminjanje obleke lika. Izvedba kviza s spreminjanjem ozadja, Dodajanje zvoka (uvažanje ali 20. Test menjava obleke lika glede na 5. Zvoki na kmetiji snemanje), ki se izvaja ob pritisku pravilnost odgovora. tipke. 21. Enostavni Uporaba dogodkov za premikanje lika Pacman Spoznavanje s kloniranjem objektov. s tipkami, bloka za zaznavanje barve 6. Kameleon na in pridobivanje boolean vrednosti, počitnicah spoznavanje neskončne zanke ter pogojnega bloka »če..., sicer«, podajanje odziva in sprememba obleke glede na pozicijo lika. 7. Pomagaj princu Spoznavanje blokov za risanje v in princeski najti kombinaciji s premikanjem lika, svoje živali nastavitev lika na začetke koordinate. Uporaba zanke pri risanju lika, 8. Risanje s kredo obračanje za x stopinj ter menjava ozadja. 9. Pobiranje smeti Uvod v spremenljivke preko štetja in čiščenje parka točk pri pobiranju odpadkov, paralelno izvajanje kod, podvajanje likov in kod. 10. Nahrani Nastavljanje vrednosti spremenljivke Slika 1 Del kode in oder iz učnega scenarija 6 - Kameleon mucke znotraj zanke, spoznavanje naključnih števil, združevanja nizov ter logičih in na počitnicah 729 3.3 Coding4Girls okolje LITERATURA Kot dodatek k učnim scenarijem je bilo izdelano Coding4Girls [1] Rugelj, J. and Lapina, M. 2019. “Game design based okolje, ki je sestavljeno iz platforme za učitelje ter igre za učence. learning of programming,” Proceedings of SLET-2019 – Vsaka aktivnost je razdeljena na 4 korake: 1) Učenec se sprehaja International Scientic Conference Innovative Approaches po 3D svetu in 2) igra mini igro, ki je povezana z vsebino. 3) Ko to the Application of Digital Technologies in Education mini igro konča, se prikažejo navodila ter razlaga programerskih and Research, Stavropol – Dombay, Russia, 20-23 May konceptov, nato pa sledi 4) izziv v programskem okolju Snap! 2019. Aachen: CEUR workshop proceedings, vol. 2494. [25]. 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And Felicia, P. “Gameplay 00000494_1585754616.pdf engagement and learning in game-based learning: A 731 Prepoznavanje disleksije s spletno aplikacijo Screening for dyslexia using web application Milena Košak Babuder Blažka Korun Ema Štarkl, Gaja Nenadović Univerza v Ljubljani Univerza v Ljubljani Univerza v Ljubljani Pedagoška fakulteta Pedagoška fakulteta Filozofska fakulteta Kardeljeva ploščad 16 Kardeljeva ploščad 16 Aškerčeva cesta 2 1000 Ljubljana, Slovenija 1000 Ljubljana, Slovenija 1000 Ljubljana, Slovenija milena.kosak@pef.uni-lj.si Erika Stanković, Sara Jakop, Dušica Boben Jure Žabkar Luka Vranješ Center za psihodiagnostična Univerza v Ljubljani Univerza v Ljubljani sredstva, d.o.o. Fakulteta za računalništvo in Fakulteta za računalništvo in Litostrojska 44d informatiko informatiko 1000 Ljubljana, Slovenija Večna pot 113 Večna pot 113 dusica.boben@center-pds.si 1000 Ljubljana, Slovenija 1000 Ljubljana, Slovenija jure.zabkar@fri.uni-lj.si POVZETEK accessible way of recognising dyslexia in children as early as possible. In comparison with traditional approaches it enables Disleksija je nevrološko pogojena bralno-napisovalna motnja, ki quicker and more extensive testing. In addition to that, it is izvira iz razvojnih posebnosti ali iz posebnosti delovanja appropriate for remote testing in an environment familiar to the osrednjega živčevja. Zanjo je značilna šibka sposobnost branja child. in črkovanja, ki ni v skladu z drugimi sposobnostmi ter pomanjkljivi avtomatizacija in tekočnost branja in črkovanja. KEYWORDS Disleksija ni povezana s stopnjo inteligentnosti, čeprav jo ponavadi zaznamo pri osnovnošolcih prav zaradi učnih težav. Z Dyslexia, web application, testing namenom čim prejšnjega prepoznavanja disleksije pri otrocih smo razvili spletno aplikacijo, ki vsebuje štiri sklope nalog za 1 UVOD prepoznavanje različnih simptomov disleksije. Aplikacija je dostopna širši javnosti in v primerjavi s klasičnimi pristopi Disleksija je kot najpogostejša oblika motenj branja in pisanja omogoča hitrejše in bolj množično testiranje; primerna je za ena izmed najbolj raziskanih motenj v skupini specifičnih učnih testiranje na daljavo, v otroku domačem okolju. težav. Zanje velja, da se razprostirajo na kontinuumu od lažjih do izrazitih ter od kratkotrajnih do tistih, ki trajajo vse življenje. KLJUČNE BESEDE Disleksija je notranje (nevrofiziološko) pogojena Disleksija, spletna aplikacija, testiranje bralnonapisovalna težava in izvira iz razvojnih posebnosti ali iz posebnosti delovanja osrednjega živčevja. Vključuje skupino ABSTRACT raznolikih, a medsebojno povezanih dejavnikov, ki so del Dyslexia is a specific learning disorder, which is neurological in posameznika in vplivajo nanj ter na njegovo delovanje skozi vse origin. It stems from developmental peculiarities or from specific življenje [1]. Obstaja kar nekaj vzročnih teorij o disleksiji, a characteristics of functioning of the central nervous system. It is večina raziskovalcev trdi, da je glavni razlog za težave pri characterized by poor reading and spelling abilities, which are disleksiji pomanjkljivo fonološko zavedanje, ki se kaže kot not in accordance with other abilities, and by impaired slabša sposobnost prepoznavanja, razlikovanja in manipuliranja automatization and spelling and reading fluency. Dyslexia is not z glasovi ter slabša sposobnost naučiti se ujemanja glasov in črk. related to the level of intelligence, even though it is precisely the To poudarjajo tudi številne opredelitve disleksije, ki vsebujejo learning difficulties that usually lead to detecting dyslexia in podobne komponente. Disleksijo opisujejo kot učno težavo ali pa primary school pupils. The purpose of developing this web nevrološko motnjo, ki vpliva na razvoj zmožnosti branja in application, which consists of four tasks, was to provide a freely pisanja [2]. Zaradi značilnih težav natančnega in/ali tekočega prepoznavanja besed, šibkega črkovanja in šibke sposobnosti dekodiranja posamezniki težje usvajajo branje, bralno razumevanje in pisanje. Težave pa niso omejene le na branje in Permission to make digital or hard copies of part or all of this work for personal or črkovanje. Prisotne so tudi težave z vzdrževanjem pozornosti, classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full avtomatizacijo novega znanja ter z groboin finomotoričnimi citation on the first page. Copyrights for third-party components of this work must spretnostmi. Ob nevrološko pogojenih razlikah pa so prisotne be honored. For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia tudi kognitivne težave, ki lahko vplivajo na organizacijske © 2020 Copyright held by the owner/author(s). spretnosti, na zmožnost računanja ter druge kognitivne in 732 čustvene sposobnosti. Posamezniki z disleksijo so lahko izjemno ocenjevalno shemo, dajo informacijo, katere bralne zmožnosti je nadarjeni in izvirni pri reševanju različnih vrst problemov, učenec že uspel razviti).; Preizkus tekočnosti branja po modelu, pogosto pa imajo tudi dobre vizualne sposobnosti [3]. V ki temelji na kurikulumu za 2., 3. in 4. razred [16], Test populaciji je približno 10 % otrok in mladostnikov z disleksijo. glasovnega zavedanja [17]. V svetu je ja IKT postala glavno Raziskave navajajo, da je pogostost motnje enaka pri obeh sredstvo za tako za odkrivanje disleksije s presejalnimi testi kot spolih, z nekoliko večjo pogostostjo pri dečkih [4]. Ponavadi tudi za intervencije, ki so prilagojene učnimi težavami in disleksijo zaznamo pri osnovnošolskih otrocih zaradi počasnega potrebami otrok in mladostnikov [18]. Uporaba IKT predstavlja napredka pri učenju branja in pisanja. Težave se pogosto izjemen dejavnik za izboljšanje običajnih metod odkrivanja odražajo v nižjem učnem uspehu in posledično slabši disleksije, sproža pa tudi raziskovanja novih perspektiv, kar samopodobi, zato je pomembno, da jo čim prej prepoznamo in zadeva identifikacijo posameznikov z disleksijo [18]. Rooms ustrezno obravnavamo. S tem preprečujemo stigmatizacijo otrok (2000) izpostavlja potencialne koristi uporabe IKT za in mladostnikov z disleksijo, njihovo lažje vključevanje v družbo osnovnošolske otroke z disleksijo in poudaril, da je lahko in manj težav v odrasli dobi. V Sloveniji so učenci z blago do dostopna in na voljo, ne da bi se učenci z disleksijo počutili zmerno izraženo disleksijo po Zakonu o osnovni šoli [5], deležni drugače ali izključeni, vključuje veččutne pristope (slušni, ustni, prilagojenih metod in oblik poučevanja in preverjanja znanja, vizualni, kinestetični) ter vključiti sisteme za izboljšanje težav tisti z izrazito disleksijo pa so po Zakonu o usmerjanju otrok s otrok z disleksijo [19]. Diagnostično ocenjevanje s pomočjo IKT posebnimi potrebami [6] deležni intenzivnejših prilagoditev in omogoča tako psihologom kot drugim strokvnim delavcem, da dodatne strokovne pomoči. V procesu prepoznavanja in na enostaven in hiter način izvedejo pregled kognitivnih diagnostičnega ocenjevanja disleksije, za katerega je potreben sposobnosti in drugih vitalnih spretnosti [20]. Interaktivna multidisciplinarni tim strokovnjakov (psiholog, specialni in multimedija, navidezna okolja, nevronske mreže, programska rehabilitacijski pedagog, logoped, učitelj), ločimo več stopenj – oprema, mehka logika, tehnike, ki temeljijo na igrah, in mobilne od detekcije, klasifikacije, načrtovanja pomoči in spremljanja aplikacije pomagajo in povečajo učinkovitost običajnih napredovanja do evalvacije [7]. Prvo stopnjo prepoznavanja oseb postopkov presejanja disleksije, in vsak od njih ima sofisticirane z disleksijo (detekcija) predstavljajo presejalni preizkusi, katerih funkcije, ki olajšajo postopke ocenjevanja [28]. V svetu je že namen je prednostna obravnava identificiranih oseb, ki dokaj dobro uveljavljena uporaba IKT za prepoznavanje učencev potrebujejo diagnostično ocenjevanje ter informiranje z disleksijo, saj je učiteljem na voljo več različnih programov, od posameznikov o verjetnosti pojava disleksije pri njih [8]. S presejalne programske opreme do podrobnejših računalniških presejalnimi preizkusi omogočajo potrditev disleksije pri ocenjevalnih baterij. Večina teh računalniških programov za učencih in izvajanje ustrezne obravnave, še preden se pri njih odkrivanje disleksije se opira na ocenjevanje branja in črkovanja, pojavi občutek neuspeha [9]. Motnja se med posamezniki zelo skupaj s kognitivnimi sposobnostmi, kot sta fonološko zavedanje razlikuje; testi za odkrivanje disleksije obsegajo testiranje in verbalno pomnjenje, ki podpirajo razvoj pismenosti in ki so na spomina, črkovanja, razumevanja besedila, bralne naloge, hitro splošno dobri napovedniki disleksije [21]. Tako klasični testi, kot poimenovanje, pozornost idr. Cilj projekta je bil razviti aplikacija imajo svoje prednosti in slabosti. Prednost klasičnih računalniški sistem za zgodnje odkrivanje znakov disleksije in z testov je, da je pri njih prisoten testator. Oseba, ki test izvaja, njo povezanih motenj pri osnovnošolskih otrocih z namenom hkrati tudi opazuje otroka, sproti preverja njegovo razumevanje, čimprejšnjega ukrepanja in nudenja ustrezne pomoči v šoli. prilagaja navodila, da jih otrok razume, opazuje otrokovo pozornost, morebitno utrujenost. Hkrati lahko oseba otroka 1.1 Diagnostično ocenjevanje disleksije spodbuja, mu nudi oporo. Slabost klasičnih preizkusov pa je Zgodnja detekcija disleksije je ključnega pomena za predvsem časovna zamudnost, ki jo lahko odpravimo s pomočjo zagotavljanje ustreznih oblik pomoči in podpore učencem z aplikacije ter izpostavljenost posameznika. Aplikacijo lahko disleksijo. Zaradi večdimenzionalne narave motnje se za rešuje več otrok naenkrat, tako lahko v kratkem časovnem učinkovito odkrivanje disleksije uporablja več različnih testov, obdobju ocenimo veliko otrok in presejemo rizične otroke od preizkušenj in baterij. Pomembno je dobro presejalno testiranje, nerizičnih. Aplikacija je dobra tudi z motivacijskega vidika, saj ki loči učence s tveganjem za nastanek motenj branja in pisanja je bolj podobna računalniški igri, kot ocenjevanju. od učencev brez tveganja. V slovenskem prostoru imamo kar nekaj preizkusov za ugotavljanje težav na področju branja in pisanja, s katerimi preverjamo različne elemente branja in pisanja 2 METODOLOGIJA (fonološko zavedanje, hitrost in pravilnost branja, avtomatizacijo Sledili smo protokolu razvoja psiholoških testov po mednarodnih branja, bralno razumevanje, pisanje po nareku, pisno izražanje): smernicah (npr.različne smernice International Test Test v motenosti branja in pisanja oz. Šalijev test [10] – test je le Commission) in ameriških standardih za pedagoške in delno standardiziran za populacijo otrok drugega razreda; SNAP psihološke pripomočke [22]. Pregledali smo vire, ki usmerjajo – profil ocene posebnih potreb (SNAP ni test v psihometričnem razvijalce računalniško ali internetnih psiholoških testov. Pri smislu, temveč pripomoček za zbiranje informacij o učencu, ki našem delu smo prehodili šele prve faze razvoja: pregledali so pomembne za ugotavljanje morebitnih težav pri določeni teoretično ozadje disleksije, se odločili, komu bo aplikacija spretnosti.) [11]; Enominutni test glasnega branja [12]; Preizkus namenjena in opredelili teoretično strukturo testov. Izvedli smo bralnega razumevanja [13]; Bralni test [14] - (test je tudi nekaj začetnih meritev. standardiziran merski instrument, ki ugotavlja splošno bralno Kot velevajo standardi, so pri razvoju sodelovali strokovnjaki zmožnost ob koncu prvega triletja); Ocenjevalna shema bralnih z različnih področij: za disleksijo, razvoj psiholoških zmožnosti učencev 1.–3. razreda: OSBZ [15] - (test je pripomočkov in računalničarji. standardiziran merski instrument in podatki, zbrani z 733 Odločili smo se, da bo aplikacija namenjena 8-letnikom. Otroci z disleksijo imajo pogosto težave z razumevanjem Pripravljena bo tako, da jo bodo lahko izpolnjevali praktično koncepta zaporedja in posledičnosti, kar se kaže v težavah pri sami. Na začetku bo potrebno dovoljenje odrasle osebe – starša urejanju elementov v zaporedje, priklicu abecede, vrstnega reda ali skrbnika, ki bo imel dovolj navodil za pomoč otroku, če jo bo dni v tednu in mesecev. Naloga, ki smo jo oblikovali, preverja ta potreboval. otrokovo zmožnost urejanja števil, mesecev in dni v tednu v Preizkus je sestavljen iz štirih sklopov nalog, ki zahtevajo ustrezno zaporedje. Postavke se stopnjujejo po težavnosti glede rabo kognitivnih procesov, ključnih za uspešno branje in pisanje: na to, ali je elemente potrebno urediti v pravilnem ali obratnem fonološko zavedanje, bralno razumevanje, kratkoročni spomin in vrstnem redu. koncept zaporedja. Za vsak test smo izdelali naloge in navodila. Pilotna raziskava bo vključevala osemletne otroke, od tega 10 Predvsem smo se posvečali nazorni in jasni predstavitvi načina s potrjeno disleksijo in 20 brez. Glavna raziskava bo vključevala reševanja otroku; preko različnih vaj preverjamo, da otrok 50 do 100 otrok s potrjeno disleksijo, 100 brez disleksije, 100 s dejansko razume nalogo, saj je to ključno za veljavnost meritve. sumom na disleksijo. Vključitveni kriterij za otroke z disleksijo Fonološko zavedanje obsega zavedanje, da je govor je odločba Zavoda RS za šolstvo, za otroke s sumom na disleksijo sestavljen iz besed, besede pa iz različnih zlogov in glasov, kar subjektivna pritožba brez odločbe, za otroke brez disleksije pa posledično posamezniku omogoča povezovanje črk s rezultat nad 20. percentilom na Ocenjevalni shemi bralnih pripadajočimi glasovi [23]. V klasičnih preizkusih tipa papir- zmožnosti za učence od 1. do 3. razreda [14]. Izključitveni svinčnik nalogo ponavadi izvajamo tako, da testator prebere kriteriji za udeležence so materni jezik, ki ni slovenščina, besedo, iz katere je potrebno izločiti določen glas ali pa določiti primarne vizualne ali slušne okvare, primanjkljaji na področju prvi ali zadnji glas v njej, testiranec pa ustno poda odgovor. Za inteligentnosti ali katerekoli druge duševne in nevrološke motnje. namene spletne aplikacije smo način odgovarjanja prilagodili, saj V splošnem je struktura sklopov nalog enotna: vsak sklop je nismo imeli dostopa do tehnologije, ki bi omogočala zanesljivo sestavljen iz navodila, prikaza reševanja, vaje in postavk, ki se avtomatsko prepoznavanje govora, pisno podajanje odgovorov točkujejo. Pri oblikovanju navodil smo bili posebno pozorni, da pa bi prineslo še kopico drugih težav, ki bi lahko prispevale k niso predolga, da vključujejo preproste in kratke stavčne manjši veljavnosti preizkusa, zato smo se odločili za različico strukture, a da hkrati zajamejo vse informacije, ki so potrebne za postavk izbirnega tipa. Otroku se zaporedoma predvajajo različni jasnost zahtev naloge. Prikaz reševanja služi seznanitvi z nalogo, možni odgovori, za vsakega pa mora označiti, ali je pravilen ali vaje pa preverjanju, da otrok res razume, kaj se od njega napačen. Besede, ki smo jih vključili v postavke, so štiričrkovne pričakuje. Vaje so oblikovane tako, da v primeru napačnega besede z enim soglasniškim sklopom. Soglasniški sklop se v odgovora pravilni začne utripati ali se poveča, kar služi kot enakomernih deležih besed pojavi na začetku, v sredini ali na namig. Pri vsakem sklopu ima otrok pred reševanjem dela, ki se koncu besede, glas, ki ga je potrebno izločiti je v polovici besed točkuje, možnost večkratnega poslušanja navodil in reševanja vaj. prvi v soglasniškem sklopu, v polovici besed pa drugi. Polovica Uporabniški vmesnik smo oblikovali tako, da je privlačen za besed je izmišljenih, polovica pa ne. otroke, da posamičen prikaz ne vsebuje nepotrebnih in motečih Bralno razumevanje zahteva rabo višjih miselnih procesov, dražljajev ter preveč elementov naenkrat, da se informacije kot sta delovni spomin in inhibicija, okrnjeno bralno prikazujejo zaporedoma in da je barvni kontrast med besedilom razumevanje pri otrocih z disleksijo pa dosledno dokazujejo in ozadjem ustrezen in nemoteč v skladu s specifičnimi izsledki številnih raziskav [24, 25, 26]. V nalogo smo na podlagi lastnostmi vidnega procesiranja otrok z disleksijo. vnaprej izbranih kriterijev, ki pri otrocih napovedujejo kasnejšo pismenost in sposobnost branja, in upoštevanja tekočnosti in hitrosti branja otrok z disleksijo vključili štiri besedila. Besedila 3 NALOGE se razlikujejo po dolžini (krajše in daljše) in po zahtevnosti (lažje in zahtevnejše), predstavljena pa so v obliki zgodbe s temami iz 3.1 Preverjanje fonološkega zavedanja vsakodnevnega življenja. Otrok po prebranem besedilu Splošna oblika postavk je: »Beseda je x, x. Kaj dobiš, ko rečeš x odgovarja na dihotomne postavke tipa da/ne in postavke brez y?«, pri čemer je x beseda, iz katere je treba izločiti glas y. izbirnega tipa. Pri vsaki postavki se zaporedoma zaslišijo trije možni odgovori, Številni posamezniki z disleksijo izkazujejo primanjkljaj v testiranec pa mora za vsakega določiti, ali je pravilen ali napačen. kratkoročnem spominu in imajo težave z zapomnitvijo Ko določen odgovor označi kot pravilnega, se naloga premakne informacij, ki niso smiselno povezane [23]. Izsledki raziskav so na naslednjo postavko, za vse ostale odgovore pa se šteje, kot da najbolj dosledni glede primanjkljajev v verbalni komponenti jih je označil za napačne. Med podajanjem odgovorov pri kratkoročnega in delovnega spomina [27, 28, 29, 30, 31, 32, 33]. določeni postavki lahko s pritiskom na ikono zvočnika na ekranu Naloga, ki smo jo oblikovali, predstavlja različico klasične ponovno posluša vprašanje. naloge preverjanja obsega kratkoročnega spomina s slušnimi Po slišanem in izpisanem navodilu sledi prikaz reševanja ki verbalnimi dražljaji (besedami). Da bi bila naloga bolj privlačna je sestavljen iz dveh delov. V prvem ponazorimo sam proces za otroke, smo jo postavili v kontekst hranjenja živali v izločanja glasu iz besede. Najprej se predvaja zvočni posnetek, živalskem vrtu. V nalogi mora otrok s kliki na sličice živali npr.: »Beseda je dres, dres. Kaj dobiš, ko rečeš dres brez d?«. nahraniti živali v enakem vrstnem redu, kot so naštete v Nato se prikaže animacija, kjer iz besede dres izgine črka d, nato predhodno slišanem zaporedju. V nalogi se pojavlja 16 živali. pa se predvaja zvočni posnetek: »Pravilni odgovor je res.« V Izbrali smo takšne, ki naj bi bile otroku poznane in katerih imena drugem delu ponazorimo način podajanja odgovora za isti primer. niso predolga. Najdaljša dolžina imena živali je 6 črk, največje Ponovno se zasliši beseda in vprašanje. Nato se zasliši prvi možni število zlogov v imenu pa tri. odgovor des, prikažeta se dva gumba, zelena kljukica in rdeč križec, kurzor pa se premakne na križec in ga klikne. Nato se sliši 734 drug možni odgovor, res, ki je pravilen, ponovno se prikažeta oba izbrali, saj so za slovenščino že določene norme hitrosti branja gumba, kurzor pa se premakne na ikono zvočnika in še enkrat pri osmih letih za dolžino besedila 80 besed. Pri obeh dolžinah posluša vprašanje, nato pa pritisne kljukico. Zasliši se: »Res je besedil je eno besedilo manj, drugo bolj zahtevno. Kriteriji, ki pravilni odgovor, zato klikneš kljukico.« Po končanem prikazu smo jih upoštevali pri določanju zahtevnosti pri obeh dolžinah reševanja ima posameznik možnost ponovno poslušati navodila besedil, so bili: koliko je povedi, ali so povedi eno- ali ali pa iti naprej na vajo. Primer, ki smo ga izbrali za prikaz večstavčne, koliko je stavkov v večstavčnih povedih, koliko je reševanja, je lahek, saj je potrebno izločiti prvi glas v besedi, dolgih besed nad s tremi zlogi ali več, koliko besed vsebuje vendar je podoben testnim postavkam. soglasniške sklope, ali je sklop v besedi eden ali jih je več in Primeri, ki smo jih izbrali za vajo, so beseda ma brez m, on koliko je v sklopu soglasnikov. Karakteristike oblikovanih brez n in bam brez b. Izbrali smo primere, ki so lažji kot testne besedil so prikazane. Posamezna vprašanja so pri vseh besedilih postavke, saj so krajši in ne vsebujejo soglasniškega sklopa, enakega tipa, prilagojena so le toliko, da ustrezajo vsebini vedno pa se izloči prvi ali zadnji glas v besedi. Služijo ogrevanju, določenega besedila. Prvo vprašanje je slikovno. Pri njem seznanitvi z nalogo ter preverjanju osnovnega razumevanja testiranci izberejo sličico, ki se najbolj ujema z vsebino besedila. zahtev naloge. Za vsako besedo oz. vprašanje, ki se nanjo nanaša, Izbrani motivi se skladajo s širšo tematiko besedila, a je glede na sta podana dva možna odgovora, pri čemer je vedno prvi napačen besedilo očitno ustrezen samo en. Drugo vprašanje je podobno in drugi pravilen. Če otrok posamezen odgovor neustrezno prvemu, saj sprašuje, o čem govori besedilo, le da so tokrat označi kot pravilnega ali nepravilnega se zasliši in izpiše odgovori besedilni. Med njimi je eden od napačnih odgovorov opozorilo: »To ni pravilni odgovor. Poslušaj še enkrat.« Ponovno blizu pravilnemu, eden pa je popolnoma nepovezan z vsebino se zasliši vprašanje, le da se sedaj kljukica in križec prikažeta besedila. Tretje vprašanje podrobneje sprašuje, kaj je počel tako, da se ustrezni gumb poveča, kar otroku služi kot namig. Ko subjekt v besedilu, pri četrtem in petem vprašanju pa testiranci otrok pri posameznem možnem odgovoru pritisne ustrezni gumb, ocenjujejo pravilnost oz. napačnost trditve. se naloga nadaljuje z zvočnim posnetkom naslednjega možnega odgovora oz. naslednje vaje. Po tretji vaji ima otrok možnost 3.3 Kratkoročni spomin ponoviti vajo ali nadaljevati na testne postavke. Splošna oblika postavke je: »Nahraniti moraš x.«, kjer je x Vsaka postavka, ki se točkuje, ima tri možne odgovore, zaporedje živali. Živali so prebrane v ritmu ena žival na sekundo. pravilni odgovor pa je v enakomernih deležih postavk prvi, drugi Zaporedje živali je podano v obliki zvočnega posnetka ob ali tretji izmed podanih. Vrstni red postavk oz. besed je naključen. praznem ekranu, nato pa se na pojavi 6 sličic različnih živali, enakomerno razporejenih čez ekran v dve vrsti po 3. Živali, ki so prikazane, so izbrane naključno, vendar tako, da nikoli nista prikazani dve ali več vizualno ali semantično podobni živali hkrati. Otrok nato nahrani živali z zaporednimi kliki na sličice živali v istem vrstnem redu, kot jih je slišal. Ob kliku na žival se zasliši zvok hranjenja živali. Ko zaključi s hranjenjem, pritisne na puščico, živali izginejo in zasliši se novo zaporedje živali. Med klikom na puščico naprej in začetkom predvajanja zvočnega posnetka naslednjega zaporedja je razmak treh sekund. Figure 1: Naloga s fonološkim zavedanjem. 3.2 Branje in bralno razumevanje V nalogi se na zaslonu najprej prikaže besedilo nato pa še vprašanja, ki preverjajo razumevanje tega besedila, z odgovori, med katerimi testiranec izbira. Besedilo se prikaže na levi polovici zaslona, testiranec pa, ko ga je prebral, sproži prikaz prvega vprašanja s klikom na gumb. Takrat se zabeleži tudi čas, ki ga je porabil za branje besedila in klik na gumb. Naloga dopušča tudi možnost vključitve naprave za sledenje pogledu, s Figure 2: Naloga z branjem in bralnim razumevanjem. katero bi bilo preverjanje hitrosti branja natančnejše, hkrati pa bi lahko bralce razvrščali v skupine po podobnosti vzorcev branja Naloga je sestavljena iz navodil, prikaza reševanja, treh vaj in na podlagi strojnega učenja, kar bi pripomoglo pri odkrivanju 15 postavk. Prikaz reševanja je sestavljen iz dveh delov. Prvi del znakov disleksije. Vprašanja se prikazujejo posamezno na desni je namenjen seznanitvi z živalmi, ki se bodo pojavljale v nalogi, polovici zaslona, pri čemer besedilo ves čas ostane vidno. Pod s čimer zagotovimo, da napačen odgovor ni posledica vsakim vprašanjem so prikazani vsi možni odgovori, od katerih neustreznega prepoznavanja prikazanih živali. Na ekranu se ena je vsakič pravilen le eden, tako vprašanja kot vsi odgovori pa so za drugo prikažejo sličice vseh 16 živali. Zraven vsake prikazane opremljeni še z zvočnim posnetkom, v katerem so prebrani. Ko živali se predvaja zvok njenega tipičnega oglašanja, ime živali se testiranec odgovori na prvo vrpašanje, se prikaže naslednje itn. pod sličico tudi izpiše, prikaz pa je dolg 3 sekunde. V drugem do zadnjega. Za preverjanje smo pripravili 4 besedila, od katerih delu otroka seznanimo z načinom podajanja odgovora. Zasliši se sta dve krajši – 35 besed, dve pa daljši – 80 besed. Ti dolžini smo zvočni posnetek: »Nahrani slona, kravo.« Nato se na ekranu 735 pojavijo sličice, kurzor klikne najprej na slona in nato na kravo. na zaslonu eden naenkrat prikazujejo elementi, pri tem pa je vsak Nato se zasliši in izpiše: »Ko zaključiš s hranjenjem živali, klikni opremljen z zvočnim posnetkov prebrane besede ali števke. na puščico.« Kurzor klikne puščico. Primer, ki smo ga izbrali, je Vrstni red prikaza elementov je določen in enak za vse testirance. zaporedje dolžine dveh enot, ki je tudi najkrajša dolžina, ki se Ko so prikazani vsi elementi, jih testiranec razvršča tako, da z pojavi v postavkah. Otrok ima po prikazu reševanja možnost še miško klikne nanje v pravem vrstnem redu, pri čemer lahko svoj enkrat poslušati navodila ali iti naprej na vajo. odgovor pred končno oddajo tudi popravlja. Naloga ima 8 Pri prvi vaji je potrebno nahraniti sovo, na ekranu pa se pri tej primerov, od katerih so pri 4 elementi sekvence besede – dvakrat vaji pojavi le ena žival namesto šestih. Namenjena je seznanitvi so uporabljene besede za dneve, dvakrat pa za mesece – pri 4 pa s potekom reševanja. Pri drugi vaji mora otrok nahraniti leva in so elementi števila. V dveh primerih razporeja testiranec besede miš, gre za dve kratki besedi, ena dvozložna in ena enozložna, za dneve in mesece v pravi vrstni red, v dveh pa v obratni. Enako pri tretji pa opico in zajca, ta vaja je težja, saj sta besedi daljši kot je pri številih, le da pri njih v pravi vrstni red razporeja dve pri drugi vaji, prav tako sta obe dvozložni. Pri vaji otrok dobi sekvenci, prav tako dve pa v obratni. Kot pravilni odgovor povratno informacijo v slušni in pisni obliki glede na to, ali je štejemo, če so pravilno razvrščeni vsi elementi in gre vrstni red rešil pravilno ali napačno. Pri napačnih odgovorih se izpišejo v pravo smer. V nalogi si števila ne sledijo po vrsti, v korakih po različne povratne informacije glede na tip napake: ali je nahranil dve (v dveh primerih, enkrat pri razporejanju od najmanjšega do preveč ali premalo živali, koliko živali preveč je nahranil, ali je največjega in enkrat pri razporejanju od največjega do nahranil živali, ki so naštete v zaporedju, vendar v napačnem najmanjšega), v korakih po dve pri vsakem drugem številu (v zaporedju, ali je nahranil zgolj nekatere živali ali pa nobene živali enem primeru) ali v različnih korakih (v enem primeru). Otrok iz zaporedja, ali je isto žival nahranil večkrat. V vsakem primeru odgovorov ne poda ustno, saj tehnologija prepoznave govora za po povratni informaciji živali ostanejo na ekranu, še enkrat se slovenščino še ni dovolj razvita, da bi jo lahko uporabili pri zasliši zaporedje, nato pa se najprej poveča prva žival iz testiranju z avtomatskim preverjanjem rezultatov. zaporedja, nato pa še druga, kar služi kot namig. Živali, ki niso Primer naloge: naštete v zaporedju, v tej točki ne more več klikniti. Ko reši Navodilo: "Razporedi dneve v tednu od torka naprej." pravilno, se naloga premakne na naslednjo vajo. torek, sreda, četrtek, petek, sobota Po tretji vaji ima otrok možnost ponoviti vajo ali iti na testni del. V testnem delu se stopnjuje dolžina zaporedja živali. Najkrajša dolžina je dve enoti, najdaljša pa šest enot, pri vsaki 4 APLIKACIJA dolžini pa so tri različna zaporedja. Pred vsakim zaporedjem, ki Razvili smo tako zaledni del aplikacije kot njen uporabniški je za eno enoto daljše od prehodnega, se predvaja zvočni vmesnik. Aplikacija deluje v okviru strežniškega sistema na posnetek: »Zdaj moraš nahraniti eno žival več.« Živali se Fakulteti za računalništvo in informatiko; na ta način smo pojavljajo preko vseh zaporedij v enakomernih deležih, v zagotovili ustrezne zmogljivosti aplikacije ob morebitnem posameznem zaporedju pa se ista žival ne pojavi več kot enkrat. hkratnem večjem številu uporabnikov ter za varnost podatkov, ki Zahtevnost postavk se, poleg dolžine zaporedja, stopnjuje tudi jih aplikacija beleži. Vsaka naloga vsebuje pisna in slušna preko dolžine imena živali, kjer je preko zaporedij znotraj ene navodila, ki so sicer skrbno pripravljena tako, da bi jih morali dolžine in preko različnih dolžin vključenih čedalje več živali s razumeti tudi otroci, vseeno pa računamo na pomoč odraslih, če čedalje daljšimi imeni. otrok navodil ne bi razumel. Navodilom sledi kratek demo – predstavitev reševanja, pri kateri otrok dobi nazorno vizualno predstavo o nalogi, ki jo bo reševal. Sledi sklop vaj, med katerimi se testiranje ne izvaja; vaje so namenjene zgolj preverjanju otrokovega dojemanja navodil – ali je otrok razumel, kaj mora pri nalogi delati. Med vajami lahko kadarkoli ponovno pogledajo tudi navodila. Figure 3: Naloga s kratkoročnim spominom. 3.4 Zaporedja V nalogi se na zaslonu v pomešanem vrstnem redu prikažejo elementi, testiranec pa jih mora pravilno razvrstiti, s čimer smo želeli preveriti sposobnost razporejanja v določen vrstni red. Za Figure 4: Naloga z zaporedji. elemente smo izbrali besede za dneve in mesece ter števila. Pred prikazom elementov se na zaslonu izpiše in hkrati zasliši prebrano navodilo, v katero smer je treba razporejati, npr. Zaledni del aplikacije smo razvili s pomočjo ogrodja Django, »Razporedi dneve v tednu od četrtka nazaj.« ali »Razporedi za bazo smo uporabili PostgreSQL, za uporabniški vmesnik pa števila od največjega do najmanjšega.« Po podanem navodilu se programski jezik Javascript. Ob vpisu starosti na začetni strani se 736 v bazi ustvari nov zapis za uporabnika. Vsakič, ko uporabnik reši [7] Magajna, L. Prepoznavanje in diagnostično ocenjevanje nalogo, se zanj ustvari nov zapis z rešitvijo, časom pričetka učnih težav: osnovna izhodišča in pristopi. V Magajna, L. in reševanja, trajanjem reševanja in morebitnimi drugimi podatki, Velikonja, M. (ur.), Učenci z učnimi težavami – npr. kolikokrat je popravil rešitev, če je bilo popravljanje rešitev prepoznavanje in diagnostično ocenjevanje (str. 10-26). možno. Ljubljana: Pedagoška fakulteta, 2011. Ker smo aplikacijo razvili v času izbruha pandemije covid-19, [8] Cooper, R. Dyslexia. V Pollak, D. (ur.), Neurodiversity in je nismo mogli testirati na osnovnih šolah. Odločili smo se za Higher Education: Positive Responses to Specific Learning poskusno testiranje pri otrocih, ki smo jih sami poznali. Tako je Differences (str. 63–90). The Atrium, Southern Gate, aplikacijo preizkusilo 9 otrok, a smo s pomočjo njihovega Chichester, West Sussex: John Wiley Sons Ltd, 2009. reševanja ugotovili pomanjkljivosti in nejasnosti v aplikaciji, tako da smo jo lahko izpopolnili. Testiranje večjega števila otrok [9] Snowling, M. J., “Early identification and interventions for nameravamo izvesti v šolskem letu 2020/21. dyslexia: A contemporary view,” Journal of Research in Special Educational Needs, let. 13, št. 1, str. 7–14, 2013. [10] Šali, B. Test motenosti v branju in pisanju (T – MBP). 5 ZAKLJUČEK Ljubljana: Zavod SR Slovenije za rehabilitacijo invalidov, S pomočjo aplikacije za presejalno testiranje disleksije bomo 1971 lahko hitreje in bolj točno opredelili skupino otrok, ki ima [11] Weedon, C. in Reid, G. SNAP-3 : profil ocene posebnih povišano tveganje za razvoj disleksije in potrebuje dodatno potreb, 3. izdaja : računalniško podprto ocenjevanje in diagnostiko. Pričakujemo, da se bo s tem za otroke z disleksijo izdelava profila specifičnih učnih težav (5–14 let) : priročnik. pomembno skrajšal čas čakanja na učno pomoč. V Sloveniji Ljubljana: Center za psihodiagnostična sredstva, 2018. podobnih testov za prepoznavanje disleksije v elektronski obliki [12] Gradišar, A. in Pečjak, S. 1991. še ni; obstajajo klasična testiranja otrok ob prisotnosti [13] Elley, W. B., Gradišar, A. in Lapajne, Z. 1995. strokovnjaka, vendar zaradi daljših čakalnih dob in težje dostopnosti (v primerjavi s spletno aplikacijo) obravnava otroka [14] Pečjak, S., Magajna, L. in Podlesek, A. Ocenjevalna shema zamuja, s čimer izgubljamo dragocen čas za pomoč otrokom z bralnih zmožnosti učencev 1.–3. razreda: OSBZ. Ljubljana: disleksijo. Potrebo po elektronskem testiranju je prepoznala tudi Znanstvena založba Filozofske fakultete, 2012. stroka, ki si ob aplikaciji za testiranje želi še razvoja ločene [15] Pečjak, S., Magajna, L., Podlesek, A. in Potočnik, N. 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S.Working memory impairment in children with 738 Zbornik 23. mednarodne multikonference INFORMACIJSKA DRUŽBA – IS 2020 Zvezek H Proceedings of the 23rd International Multiconference INFORMATION SOCIETY – IS 2020 Volume H Interakcija človek-računalnik v informacijski družbi Human-Computer Interaction in Information Society Uredili / Edited by Veljko Pejović, Matjaž Kljun, Vida Groznik, Domen Šoberl, Klen Čopič Pucihar, Bojan Blažica, Jure Žabkar, Matevž Pesek, Jože Guna, Simon Kolmanič http://is.ijs.si 7. oktober 2020 / 7 October 2020 Ljubljana, Slovenia 739 740 PREDGOVOR Interakcija človek–računalnik v informacijski družbi je konferenca, ki jo organizira Slovenska skupnost za proučevanje interakcije človek–računalnik. Namen konference je zbrati raziskovalce, strokovne delavce in študente s področja in ponuditi možnost izmenjave izkušenj in raziskovalnih rezultatov, kakor tudi navezave stikov za bodoča sodelovanja . Tokratna, peta reinkarnacija konference se že drugič odvija pod okriljem SIGCHI poglavja ACM Chapter Bled, ki je nastalo tudi kot posledica prejšnjih konferenc. O rasti HCI skupnosti v regiji pa priča tudi vse večje število prispevkov, ki prihajajo z vseh večjih visokošolskih zavodov v Sloveniji. Teme, ki jih konferenca pokriva segajo od bolj uveljavljenih, kot so vizualizacija, snovanje grafičnih in uporabniških vmesnikov, ki temeljijo na govoru, personalizacija in prilagajanje interakcije uporabnikom, pa do virtualne in nadgrajene resničnosti ter uporabniških vmesnikih v turizmu, umetnosti in e-učenju. FOREWORD Human-computer interaction in information society is a conference organized by the Slovenian HCI community. The purpose of the conference is to gather researchers, practitioners and students in the field and offer the opportunity to exchange experiences and research results, as well as to establish contacts for future cooperations. This year's fifth reincarnation of the conference is, for the second time, organized by the SIGCHI Chapter ACM Chapter Bled, which has been established also as a result of previous conferences. The growth of the HCI community in the region is witnessed by the doubled number of contributions coming from all major higher education institutions in Slovenia. The topics covered by the conference range from the more established ones, such as visualization and design of graphical and audio user interfaces, personalisation and interaction adaptation, to virtual and augmented reality, and the ap plication of user interfaces in tourism, arts, and e-learning. 741 PROGRAMSKI ODBOR / PROGRAMME COMMITTEE Nuwan T Attygalle (Univerza na Primorskem) Bojan Blažica (Inštitut Jožef Stefan) Klen Čopič Pucihar (Univerza na Primorskem) Jordan Deja (Univerza na Primorskem) Vida Groznik (Univerza na Primorskem) Jože Guna (Univerza v Ljubljani) Matjaž Kljun (Univerza na Primorskem) Simon Kolmanič (Univerza v Mariboru) Ines Kožuh (Univerza v Mariboru) Elham Motamedi (Univerza na Primorskem) Marko Tkalčič (Univerza na Primorskem) Domen Šoberl (Univerza na Primorskem) Veljko Pejović (Univerza v Ljubljani) Jure Žabkar (Univerza v Ljubljani) 742 Investigating the Role of Context and Personality in Mobile Advertising Andrej Martinovič Veljko Pejović Faculty of Computer and Information Science, University Faculty of Computer and Information Science, University of Ljubljana, Slovenia of Ljubljana, Slovenia am6694@student.uni-lj.si Veljko.Pejovic@fri.uni-lj.si ABSTRACT Machine learning and recommender systems are at the core More than three billion smartphones carried by their users at of modern advertising solutions [9]. The selection of the ad virtually all times, represent an unprecedented platform for to be show to the user benefits from the history of purchases, in-situ advertisement delivery. While recent efforts in data information on the similarity among users, but also on the analysis and machine learning led to significant advances in information about a user’s personality [6]. the way relevant content is selected to be shown to a user, Moving to the mobile domain, contextual information, thorough investigation on how the content should be dis- such as location may impact the relevance of an ad [2]. The played to a mobile user is yet to be conducted. In this work we context, that can be sensed by a smartphone, such as a user’s present our preliminary research on the role of the context location, his physical activity, time of day, and other factors, in which an advertisement is consumed and the personality can also be used to determine the suitability of a moment of a user consuming it on the perception of the ad content. for information delivery [7]. We conduct a 7-week study with 14 mobile users who were While the previous work focuses on the content or the exposed to both video and picture ads. Through mobile sens- timing of the ad delivery, the type of the ad, to the best of our ing and experience sampling we capture the information on knowledge, has not been examined in the mobile domain. the context in which the ad was seen, the user’s attitude Nevertheless, the type of the ad, whether it is a picture, a towards the ad, as well as the user’s personality traits. Statis- short or a long video, or perhaps an interactive content (e.g. tical analysis based on mixed-effect modelling demonstrates a short game) is an important parameter that influences the that personality traits play an important role in ad percep- overall design of an ad, the platforms at which the ad can tion, as does the ad type, with picture ads being preferred to be shown, advertisement budget, etc. In this paper we focus video ads, while the effect of the context on ad perception on the perception of an ad type in mobile computing and appears to be negligible. pose the following research question: Can the contextual information collected by the mobile phone sensors and the CCS CONCEPTS information on a user’s personality predict a user’s perception • Human-centered computing → Interaction techniques; of different types of mobile ads? Ubiquitous and mobile devices; Empirical studies in ubiq- uitous and mobile computing. 2 METHODOLOGY KEYWORDS To obtain ecologically valid data on mobile ad perception in different contexts we developed a data collection mobile mobile advertising, multilevel models, ubiquitous computing application that serves ads, captures a user’s attitudes to- 1 INTRODUCTION AND BACKGROUND wards the displayed ads, and collects sensor data pertaining to the context of use. In the rest of the section we present Tremendous amounts of digital traces, just-in-time sensor the details of our app. information, and the advances in data processing have re- sulted in major shifts in how the advertising is performed. Mobile Application Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are We implemented a full-fledged mobile app that caters to the not made or distributed for profit or commercial advantage and that copies need of our target users – students at our University. The bear this notice and the full citation on the first page. Copyrights for third- application was built for the Android platform and serves party components of this work must be honored. For all other uses, contact as a utility tool allowing its users to: obtain information the owner/author(s). Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia on nearby restaurants providing subsidised student meals, © 2020 Copyright held by the owner/author(s). get real-time public transport timetables, record or share important student notes, retrieve latest student related news 743 Figure 1: Data collection app: one of the functionalities (left), advertisement (center) and an ESM questionnaire (right). feeds, save and access their most needed school gadgets, and was engaged with the ad. The last question focused on the ap- organise their class schedules (Figure 1 left). propriateness of the displayed ad. The answers are recorded with five-level Likert scales. Figure 1 represents the data col- Mobile ads. Mobile ads come in different flavours ranging lecting workflow, where a user made an action, which led to from simple picture-based ads, over video ads, to more inter- the ad being displayed, followed by the ESM questionnaire. active game-like ads. We opted to investigate the two most frequent types of ads in our study – pictures and videos. We Personality test. Previous research demonstrates that per- further divide the video ads into two groups – short videos, sonality traits have a moderate effect on a user’s attitude with the length of 30 seconds or less, and long videos with towards advertisement [1]. Therefore, we included the BFI- the length between 30 and 80 seconds. From each of the 10 personality test [8] as a part of our app. The test includes three groups – pictures, short videos, and long videos – we ten questions about a user’s traits answered on a seven-point gathered 31 different publicly available ads and pre-loaded Likert scale. The processed BFI-10 data, assessing a user’s them on our server. After five actions that a user makes personality along the five dimensions (extraversion, agree- within our app, a request is made to our back-end system ableness, openness, conscientiousness, and neuroticism), was which responds with a random ad of a randomly chosen cat- further compared to the statistics calculated on a larger pop- egory. Simultaneously, we activate mobile phone’s sensors ulation set in order to extract the percentiles to which the and capture the user’s context, including the physical activity participants personality trait scores belong [8]. (through Android’s Google Activity Recognition function- ality), location (clustered as work, home, or other, according Data collection campaign to the method described in [7]), screen brightness, battery Our data collection campaign lasted for seven weeks in level, time of day, and the Internet connectivity type. spring 2020 and included 14 participants who in total viewed Experience sampling method (ESM) questionnaires. ESM is 994 ads, out of which 501 they labeled, i.e. an ESM question- commonly used to gather the participants own thoughts, naire was completed immediately after the ad was viewed. emotions, behaviour, etc [3]. In our case it provided us with The distribution of labeled and unlabeled ad types is roughly feedback regarding the participants assessment of overall ad even. The viewing was reasonably evenly distributed among suitability. With the included questionnaire we also wanted users, with the least active participant contributing 2.4% and to measure the interaction level between the user and the the most active participant contribution 12.6% of the data. displayed ad. Thus, the questionnaire consisted of following In our study we included 12 picture ads, 9 short video ads, questions: what was shown on the ad, which brand/trademark and 10 long video ads. The ads were randomly shown both was advertised, and was the ad shown in an appropriate form. within and among users, i.e. each two users saw different ads The first two questions were used to assess whether the user where a participant shown a picture ad from a specific brand 744 need not have seen a video ad from the same trademark. model comparison remains above the 0.05 threshold, again The majority of viewed ads, that are labeled, were pictures indicating the superiority of the basic model. (40.5%), followed by short videos (34.7%). The least amount Since the context is shown to be irrelevant, we focus on the of user feedback was from long videos (24.8%). The average content and the type-based models. With the inclusion of ad score (questionnaire answers ranging from "Strongly dis- type, as a part of fixed effects, we were able to build a model agree" to "Strongly agree" were transformed to the integer that preforms better then the basic one. We suspect that [-2, 2] scale) over all ads was 0.377, yet it differs across the ad different users score different ad types in different manners, types. Labeled pictures had an average score of 0.695, short thus we included the type parameter as a random slope. videos 0.253, and long videos 0.032. Metrics AIC, BIC show a significant decrease, indicating that the new model preforms better than the previous one. 3 MOBILE AD PERCEPTION MODELLING The analysis of the model reveals that picture ads receive a Our data collection study elaborated in Section 2 has resulted predominantly positive score, short videos neutral-negative, in a heterogeneous dataset with an uneven number of dat- and long videos very negative score. Slope coefficients for apoints across users, across contextual characteristics, and ad type were also found to be varying within users. We ad types. The natural organisation of our data into groups further experiment with content-based models, where the makes multilevel modelling-based analysis particularly ap- each particular ad is encoded as its own content category.The propriate. Such models generalise the linear regression in a AIC, BIC, and chi-square-based comparison indicate that the manner that allows that the effect of a group (e.g. a particular content has a statistically significant impact on ad scoring. user, a personality type, etc.) is disentangled from the effect With both content and ad type being relevant we further of predictors, such as contextual variables [4] [5]. investigate whether it is possible to combine both models With hierarchical modeling we gradually increase the and also include the ad viewing duration as a parameter. model complexity by including different parameters as a Indeed, our best preforming model includes the duration of part of fixed or random effects. At each step we need to com- ad watching, and cross-level interaction of ad content and ad pare our new model to the previous one. This is done by type as fixed effects, and ad type as the random effect. The preforming a chi-squared test checking if the residual sum of conditional 2 𝑅 metric of such a model is 0.455 whilst the squares of the new model is statistically significantly smaller marginal 2 𝑅 is 0.204 indicating a reasonably good fit. than that of the old model. To further verify which model is better we calculated the AIC (Akaike information criterion) Personality-based model and BIC (Bayesian Information Criterion) metrics, where The above user ID-based model demonstrates the impact smaller values indicate a better model, since the relative of individual traits on the ad perception. Nevertheless, the amount of information lost is lower. model is not suitable for real-world use, as it requires that an In this section we present the results of multilevel mod- individual’s data is available before predictions can be made. elling with two models constructed on the labeled data in Therefore, we now design a model that, instead of data from a order to investigate the impact of different parameters on particular user, is based on the information about personality the ad perception – a model where the user ID is the group- traits of a user. Such information can be obtained quickly ing variable and a model where the user’s personality is the through a personality test. grouping variable. We then use both labeled and unlabeled The basic personality-based model only includes a group- data in a semi-supervised learning fashion to construct our ing variable based on personality traits without any fixed final predictive model rooted in users’ personalities. effects or random slopes. As before, we find that the inclu- sion of context parameters does not improve the basic model User ID-based model so we focus on the ad content and ad type as the next model- The basic user model includes merely the participants’ IDs as ing level. Gradually increasing the complexity of our model the grouping variable. From there on we gradually increase we come to similar conclusions as in the previous section. the model complexity by separately adding context-based The fixed effects include a cross-level interaction of ad con- parameters. We experiment with the inclusion of the physical tent and ad type, where the random effects include ad type activity, location, screen brightness, battery level, time of only. The final personality-based model demonstrates that day, and the internet connectivity type information in our ad types are marked differently within different personality model, and find that none of the contextual variables have a groups. One particular group consisting of extrovert, non- statistically significant influence on whether a user marks an conflicting, non-conscious, and emotionally stable users is ad as appropriate or not. In addition, the comparison of the found to stand out. In the mentioned group pictures had an basic model with the context-based ones reveals that the AIC average score of -0.4, short videos 0.636 and long videos -0.75. and BIC metrics increase, and the p-value of the chi-squared To see if the scores were indeed significantly different, we 745 preform a Welch’s t-test between this outlying and all other (R)MSE and mean absolute error (MAE) of our model and personality groups (Table 1). We find that the difference in the baseline model that predicts the mean score across the short video scoring between the compared groups is not dataset. Average RMSE, MSE, and MAE for the personality- statistically significant, whilst the scores of pictures are. based model are 0.967, 1.014, and 0.785, whereas the baseline results in 1.117, 1.347, and 0.865, respectively, indicating that Metrics Pictures Short videos Long videos the personality-based predictive model fits the data better t-test -4.087 1.026 -1.545 2 p-value 0.001 0.326 0.162 than the majority classifier. The 𝑅 metric’s conditional value 95% conf. interval [-1.771, -0.565] [-0.467, 1.286] [-2.089, 0.416] of the model is 0.488 and the marginal is 0.308. Outlying group avg. -0.4 0.636 -0.75 Other groups avg. 0.768 0.227 0.086 4 DISCUSSION AND CONCLUSION Table 1: Welch’s t-test between the outlying personality group (extrovert, non-conflicting, non-conscious, and emo- In this paper we examined of the role of context and a user’s tionally stable) and other personality groups. personality on ad perception. While our initial assumption was that users would prefer either picture or video ads de- pending on the context of viewing, we discovered that picture Even though we built a personality-based model with ads are almost universally better accepted. This surprising the intent to make it more general, we found that not all finding might stem from our data collection limitations – personality combinations are included, as our sample size is conducted during the COVID-19 pandemics, the data fails to not large enough. With 14 participants, out of 16 different capture the full range of locations and activities we would ex- possible personality groups (openness omitted) only 7 are pect to see during regular times. A prominent role of a user’s covered. The final model’s 2 𝑅 metric conditional value is personality in the perception of an ad is another interesting 0.377 and the marginal is 0.198. finding. We discover that certain personalities actually prefer short videos over picture ads. Our general predictive model Predictive personality-based model takes personalities into account and is able to predict the The user ID-based model demonstrates that who is watching attitude that a previously unobserved user will have towards the ad is more important than in what situation is someone an ad better than the baseline model. The initial analysis also watching the ad. Predictions of an attitude towards an ad demonstrates that the content of the ad, a property that was could be used to decide whether to show an ad of a cer- outside of the scope of our study, may significantly impact tain type, or whether to show an ad at all. Yet, personalised the perception and should be further examined. user-based models would require labeled data for each user, making their construction impractical. The analysis of the REFERENCES personality-based multilevel models demonstrates that gen- [1] Aliosha Alexandrov, Susan Mayers, and Sandipan Sen. 2010. 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Journal of Computer Applications 180, 7 (Dec 2017), 17–22. 746 Interaktivna vizualizacija proračuna Republike Slovenije s Sankeyevim diagramom Interactive Visualization of the Slovenian Budget with the Sankey Diagram Tea Tušar tea.tusar@ijs.si Jožef Stefan Institute Jamova cesta 39 Ljubljana, Slovenia Slika 1: Sankeyev diagram za splošni del proračuna za leto 2020 POVZETEK different budget categories and the cash flows between them, we Predstavljamo spletno aplikacijo z interaktivno vizualizacijo pro- visualize both the general and the specific budget part. Interaction računa Republike Slovenije. Z dvema Sankeyevima diagramoma, allows to change views, so that more details can be shown. The ki prikazujeta različne kategorije proračuna in denarne tokove application does not produce pre-selected aspects of the budget, med njimi, vizualiziramo tako splošni kot posebni del državnega but is intended for free searching among its data and as such proračuna. Interakcija omogoča spreminjanje pogledov, s ka- represents an alternative to existing budget visualizations. It is terimi lahko prikažemo več podrobnosti. Aplikacija ne ponuja available at http://proracun.herokuapp.com vnaprej izbranih vidikov proračuna, ampak je namenjena pro- stemu raziskovanju po njegovih podatkih in kot taka predstavlja KEYWORDS alternativo obstoječim vizualizacijam proračuna. Na voljo je na state budget, interactive visualization, Sankey diagram naslovu http://proracun.herokuapp.com. KLJUČNE BESEDE 1 UVOD državni proračun, interaktivna vizualizacija, Sankeyev diagram Živimo v času velepodatkov, družabnih omrežij in takojšnje ko- munikacije, ki nam v vsakem trenutku nudijo ogromne količine ABSTRACT informacij. Ta preobremenjenost z informacijami nam otežuje We present a web application with interactive visualizations poglabljanje vanje in njihovo preverjanje. Tako se pogosto za- of the Slovenian budget. With two Sankey diagrams that show našamo na tuje interpretacije in se nehote znajdemo v pasivni vlogi prejemnika informacij, ki so lahko tudi pomanjkljive ali Permission to make digital or hard copies of part or all of this work for personal (namenoma) napačne. or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and Temu se je moč izogniti z lastnim preverjanjem podatkov, ki the full citation on the first page. Copyrights for third-party components of this pa je lahko zelo zahtevno opravilo. Na voljo moramo imeti dostop work must be honored. For all other uses, contact the owner/author(s). do podatkov, možnost obdelave velike količine podatkov, metode Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). za vizualizacijo ter znanje potrebno za umestitev podatkov v širši kontekst in njihovo pravilno interpretacijo. Pri tem nam lahko 747 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Tea Tušar pomagajo orodja, ki pridobivanje in obdelavo podatkov opravijo predstavlja 48,4 % vseh javnofinančnih odhodkov. Sledijo pokoj- namesto nas. ninska blagajna s 27,1 % odhodkov, zdravstvena blagajna s 14,2 % V prispevku predstavljamo novo takšno orodje (slika 1), na odhodkov in občinski proračuni z 10,3 % odhodkov [10]. voljo na naslovu http://proracun.herokuapp.com, ki preko interaktivne vizualizacije s t.i. Sankeyevim diagramom uporabniku 2.1 Struktura proračuna pomaga pri razumevanju proračuna Republike Slovenije in iska- Državni proračun je sestavljen iz treh delov. nju informacij v njem. To je relevantno, saj je državni proračun I. del: Splošni del proračuna vključuje bilanco prihodkov največja izmed štirih blagajn javnega financiranja in predstavlja in odhodkov, račun finančnih terjatev in naložb ter ra- nekaj manj kot polovico vseh javnofinančnih odhodkov [10]. Raz- čun financiranja. Izkazuje se po ekonomski klasifikaciji kriva fiskalno politiko, razvojne cilje, prednostna področja ter (skupina kontov, podskupina kontov in konto). politične in strateške prednostne naloge vlade. II. del: Posebni del proračuna izkazuje porabo javnofi- Kot pri vseh vizualizacijah, ki predstavljajo kompleksne po- nančnih sredstev posameznih proračunskih uporabnikov datke, je tudi tu bistvenega pomena interaktivnost. Pri obsežnih preko institucionalne klasifikacije (nadskupina proračun- zbirkah podatkov namreč zaradi omejitev ljudi na eni in raču- skih uporabnikov, skupina proračunskih uporabnikov in nalniških vizualizacij na drugi strani ni mogoče vseh podatkov proračunski uporabnik) ter vključuje odhodke in druge iz- pokazati naenkrat. Bolje se izkaže interakcija, pri kateri upo- datke delovanja predstavljene po programski klasifikaciji rabnik s svojimi dejanji sproža spremembe pogledov. Za razliko (politika, program in podprogram). od statičnega pogleda, ki lahko naenkrat prikaže samo en vidik III. del Načrt razvojnih programov predstavlja načrt od- podatkov, interakcija podpira številne poizvedbe. Še posebej je hodkov po podprogramih, ukrepih, skupinah projektov, koristna pri preiskovanju na več ravneh podrobnosti, ko nam projektih in virih financiranja po posameznih letih za ce- omogoča, da se (postopoma) premaknemo od pregleda na najvišji lotno obdobje izvajanja projektov in ukrepov. ravni preko vmesnih pregledov do najbolj podrobnega pregleda, ki lahko prikazuje le majhen del vseh podatkov [5]. Tako za splošni kot za posebni del proračuna so na voljo tudi Naloga, ki jo novo orodje naslavlja, ni predstavljanje ali razla- dodatne obrazložitve. V nadaljevanju se osredotočamo le na ta ganje vnaprej izbranih vidikov proračuna, temveč podpora pri dva dela proračuna. prostem raziskovanju po njegovih podatkih, ki uporabniku po- maga, da najde lastne vpoglede vanje. Kot tako je torej dopolnitev 2.2 Dostopnost podatkov obstoječim vizualizacijam proračuna, kot so razlagalne infogra- Na spletišču državne uprave (https://www.gov.si/) je pod okriljem fike in druge vizualizacije, ki jih pripravlja Ministrstvo za finance Ministrstva za finance podanih mnogo informacij o državnem Republike Slovenije (več o njih v razdelku 2.3). Orodje je name- proračunu [8]. Med njimi so prosto dostopni tudi podatki o spre- njeno tako navadnim državljanom kot novinarjem in drugim jetih proračunih za vsa leta med letoma 2004 in 2021. Ti so na profilom, ki jih proračun tako ali drugače zadeva in ga želijo voljo v tabelarični obliki v datotečnem formatu PDF za vse tri raziskati ter tako bolje razumeti. dele proračuna. Namenjeni so torej predvsem pregledu in niso V nadaljevanju najprej na kratko predstavimo državni pro- primerni za dodatno računalniško obdelavo. račun, njegovo strukturo, dostopnost podatkov in obstoječe vi- Ravno nadaljnji obdelavi pa so namenjeni podatki v datoteč- zualizacije. Nato se posvetimo novemu orodju za vizualizacijo nem formatu CSV na portalu Odprti podatki Slovenije (OPSI, proračuna. Po opisu Sankeyevega diagrama razložimo kako ga https://podatki.gov.si/). Na portalu sta za vse proračune med le-lahko obogatimo z uporabo interakcije. Predstavimo tudi podrob- toma 2014 in 2021 na voljo splošni in posebni del proračuna, od nosti izdelave vizualizacije in razpravljamo o njenih lastnostih. leta 2019 naprej pa še načrt razvojnih programov [11]. Vsi podatki Prispevek zaključimo s povzetkom in zamislimi za nadgradnjo uporabljeni v tem prispevku izhajajo iz portala OPSI. orodja. 2.3 Obstoječe vizualizacije 2 DRŽAVNI PRORAČUN Ministrstvo za finance poleg golih podatkov o proračunu od Državni proračun Republike Slovenije je gospodarsko-politični leta 2017 naprej objavlja tudi infografike s ključnimi podatki akt, ki vključuje predvidene prihodke in odhodke države za eno o proračunu, s katerimi želi proračun približati širšemu krogu leto. Sprejme ga Državni zbor po predpisanem postopku. Kadar so državljanov. Primer takšne infografike je prikazan na sliki 2 [9]. dejanski prihodki manjši od načrtovanih ali nastanejo nove obve- Infografika izpostavlja določene vidike posebnega proračuna – znosti, ki v proračunu niso bile predvidene, vlada lahko predlaga v tem primeru 16 politik, pri čemur so nekatere združene, saj je originalnih politik, zajetih v proračun, 24. Manjše število politik je rebalans proračuna1. Z njim proračun uskladi s spremenjenimi okoliščinami. lažje za razumevanje, a neizogibno skriva nekatere podrobnosti. Državni proračun je ena od štirih blagajn javnega financiranja. Poleg infografik so od začetka leta 2020 na voljo tudi tri vr- Preostale tri so ste (interaktivnih) vizualizacij proračuna [12]. Prva omogoča pokojninska blagajna, iz katere se pretežno izpla- čujejo pokojnine in invalidnine, vpogled v trenutno stanje prihodkov in odhodkov proračuna, zdravstvena blagajna, ki pokriva predvsem stroške delovanja zdravstvenih domov, bolnišnic in ki se dnevno osvežuje. Iz nje je razvidno ali se proračun izvaja zdravil ter skladno s pričakovanji. Druga vizualizacija je interaktivna in za občinski proračuni, ki obsegajo prihodke in odhodke vseh 212 občin. Največja blagajna je ravno državni proračun, ki vseh 24 politik proračuna omogoča podrobnejši pogled porabe v posebnem oknu, v katerem so odhodki dodatno razdeljeni po programih in kontih. Odhodki vsake politike so prikazani tudi za pretekla leta (od leta 2009 naprej). Tretja vizualizacija pa nudi 1V času pisanja tega prispevka se pripravlja rebalans proračuna za leto 2020 [13]. vpogled v posamezne projekte, kjer interaktivnost omogoča iska- Povod zanj je izraziti upad proračunskih prihodkov med epidemijo COVID-19, hkrati pa rast izdatkov zaradi sprejetih ukrepov vlade za omilitev posledic krize in nje projektov po različnih kriterijih, med drugim tudi po tem v ohranitev gospodarske aktivnosti. kateri regiji in občini se izvajajo. 748 Interaktivna vizualizacija proračuna Republike Slovenije Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Slika 2: Infografika bilance odhodkov za posebni proračun za leto 2020 (vir: Ministrstvo za finance [9]) Slika 3: Izpis dodatnih podatkov ob interakciji s katego- 3 INTERAKTIVNA VIZUALIZACIJA S rijo (zgoraj) in tokom (spodaj) posebnega dela proračuna za leto 2020 SANKEYEVIM DIAGRAMOM Kot dopolnitev obstoječim grafičnim prikazom predlagamo vizu- alizacijo proračuna z dvema Sankeyevima diagramoma – enim za splošni in drugim za posebni del proračuna. 3.1 Sankeyev diagram Sankeyev diagram (poznan tudi kot aluvialni diagram) prikazuje kategorije in kvantitativne odnose med njimi [4]. Kategorije so vizualizirane kot pravokotniki (na sliki 1 obarvani v sivo), odnosi med njimi pa kot tokovi (na sliki 1 v različnih barvah). Širina toka je sorazmerna s količino, ki povezuje dve kategoriji. Čeprav je Sankeyev diagram poimenovan po diagramih ener- getske učinkovitosti parnega stroja Matthewa Sankeya iz leta Slika 4: Podrobnejši pregled kategorije Izobraževanje in 1898 [3], je bil v rabi že prej. Eden najbolj poznanih Sankeye- šport posebnega dela proračuna za leto 2020 vih diagramov je Napoleonova ruska kampanija, ki jo leta 1869 ustvaril Charles Minard [7]. Sankeyev diagram je videti kot nalašč za vizualizacijo pro- • Sprememba pogleda. S klikom na kategorijo spremenimo računskih podatkov, saj lahko na eni sami sliki prikaže mnogo pogled tako, da se približamo izbrani kategoriji in vsem raznolikih prihodkov in odhodkov ter morebitno razliko med njenim podrejenim kategorijam (ter v primeru posebnega njunima vsotama. Na sliki 1 so bilance označene s temno sivo proračuna tudi njenim prvim nadrejenim kategorijam). barvo in postavljene na sredino grafičnega prikaza. Kategorije na Na ta način lahko prikažemo kategorije in tokove, ki so levi kažejo prihodke v proračun, kategorije na desni pa njegove v izvirnem pogledu predrobni ali preveč nagneteni, da bi odhodke. Sankeyev diagram dobro prikaže tudi kako se neka jih lahko dobro videli. Primer takšne spremembe pogleda kategorija razčleni na več podkategorij in kakšna so razmerja na diagramu posebnega dela proračuna je ilustriran na med njimi. Na sliki je to vidno za hierarhijo bilanca – skupina sliki 4. Tu je kategorija Izobraževanja in športa povečana kontov – podskupina kontov – konto (na strani prihodkov in čez celoten zaslon, kar nam omogoča, da v podrobnosti vi- odhodkov). dimo njene podkategorije in njihova medsebojna razmerja. Sankeyevega diagrama za posebni del proračuna zaradi omeje- Hkrati pa vidimo tudi katera ministrstva so odgovorna nega prostora v prispevku ne prikazujemo v celoti (v nadaljevanju za to politiko. V takšnem pogledu se lahko odločimo, da bomo videli nekatere njegove dele). nadaljujemo s pregledovanjem drugih kategorij (s klikom nanje) ali pa se s klikom na katerikoli tok vrnemo na pr- 3.2 Uporaba interakcije votni pogled. Sankeyevemu diagramu lahko izrazno moč povečamo z uporabo • Izbira podatkov. Preko zavihka (ni viden na slikah) lahko interakcije. Predlagano orodje podpira naslednje interakcije: izberemo leto proračuna, ki nas zanima. Trenutno imamo na voljo podatke za proračune za leta 2019, 2020 in 2021. • Izpis več podatkov. Ker se zneski v državnem proračunu med seboj precej razlikujejo, so nekatere kategorije in to- Ob spremembi leta se izrišeta nova dva Sankeyeva dia- kovi lahko zelo debeli, drugi pa komaj vidni. Poleg tega je grama (za splošni in posebni del proračuna), ki vsebujeta na določenih ravneh število kategorij in tokov precejšnje. podatke za izbrano leto. To pomeni, da ne moremo izpisati imena vseh kategorij, ampak se omejimo le na največje. Interakcijo lahko kori- 3.3 Izdelava vizualizacije stimo za to, da se imena kategorij (tudi tistih najmanjših) 3.3.1 Priprava podatkov. Kot že omenjeno, so vsi podatki, upo- v celoti izpišejo šele takrat, ko se z miško postavimo nad rabljeni v tem orodju, pridobljeni s portala OPSI [11]. Podatki so njimi (glej sliko 3 zgoraj). Na podoben način interakcijo vzorno pripravljeni, saj z njihovim rokovanjem nismo imeli težav. uporabimo tudi pri premikanju miške nad tokovi, kjer se Pred uporabo smo podatke dodatno obdelali. Najprej smo odstra- ob tem pokaže več informacij o toku (njegov izvor in ponor nili vse tiste povezave med kategorijami, pri katerih so bili zneski ter znesek, slika 3 spodaj). manjši od 1000 EUR. S tem smo želeli izpustiti podatke, ki so 749 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Tea Tušar relativno majhni in, v kontekstu državnega proračuna, praktično uporabe za posledico (pre)malo nadzora nad končnim izgledom, nepomembni. Poleg tega smo na tak način zmanjšali velikost ki bi ga želeli dodatno prilagoditi, a to ni mogoče. Moteča so tudi podatkovne zbirke in malenkost izboljšali odzivnost orodja, ki se občasna prekrivanja imen v kategorijah (glej spodaj desno na ob velikem številu kategorij in tokov zmanjša. sliki 1), ki se jim je pri interaktivnih vizualizacijah težko izogniti. Izračunali smo tudi vse skupne zneske po kategorijah. Nato smo pripravili uporabniku prijazen zapis zneskov, ki števila zao- 4 ZAKLJUČKI kroži in uporablja okrajšave za milijon in milijardo. Končno smo Predstavili smo novo vizualizacijo proračuna Republike Slove- podatke preoblikovali v obliko, ki jo zahteva knjižnica za izris nije s Sankeyevim diagramom, ki podpira interaktivnost in tako Sankeyevih diagramov (več v tem v nadaljevanju). Tako pripra- omogoča poglobljeno raziskovanje kategorij in denarnih tokov vljene podatke smo shranili za uporabo v nadaljevanju (opisana proračuna. Na ta način vizualiziramo tako splošni kot posebni obdelava podatkov se izvede samo enkrat – orodje nato deluje del proračuna. na že obdelanih podatkih). V nadaljevanju bi želeli poskusiti na isti način vizualizirati tudi razlike med dvema proračunoma. Tako bi lahko primerjali 3.3.2 Tehnična izvedba. Za implementacijo Sankeyevih diagra- proračune dveh različnih let ali pa osnovni proračun z njegovim mov smo uporabili Pythonovo knižnico Plotly [6], ki ponuja rebalansom. številne interaktivne grafične prikaze in delo z njimi precej po- enostavi. Plotly zahteva podatke o kategorijah in tokovih med ZAHVALA njimi in iz njih avtomatično zgradi Sankeyev diagram. Spletno aplikacijo smo zgradili z ogrodjem Dash [1] in jo Delo je nastalo v okviru raziskovalnega programa št. P2-0209, ki objavili preko platforme Heroku [2]. Trenutno je na naslovu ga sofinancira Javna agencija za raziskovalno dejavnost Repu- http://proracun.herokuapp.com na voljo verzija 0.3. blike Slovenije iz državnega proračuna. 3.3.3 Oblikovalske odločitve. Ob oblikovanju diagramov smo LITERATURA morali sprejeti nekaj odločitev, ki so vplivale na uporabo in iz- [1] Dash. 2020. Dash user guide. Dostopano 1. 9. 2020. https: gled diagramov. V prvi vrsti smo se odločali za funkcionalnost //dash.plotly.com. interakcij (glej razdelek 3.2). Pri spremembi pogleda se tako v [2] Heroku. 2020. Heroku. Dostopano 1. 9. 2020. https://www. primeru posebnega dela proračuna pokažejo tudi nadrejene kate- heroku.com/home. gorije, ker to nudi več konteksta, ki v splošnem delu proračuna [3] Alex B. W. Kennedy in H. Riall Sankey. 1898. The thermal ni tako pomemben. efficiency of steam engines. Minutes of the Proceedings of Ime kategorije se pokaže, če je znesek kategorije vsaj 5 % vsote the Institution of Civil Engineers, 134, 278–312. vseh kategorij v istem stolpcu. Podobno prikazujemo le prvih 30 [4] Andy Kirk. 2016. Data Visualization: A Handbook for Data znakov imena, celotno ime pa le ob interakciji. Obe meji (5 % in Driven Design. SAGE. 30 znakov) smo določili empirično. [5] Tamara Munzner. 2015. Visualization Analysis and Design. Vse kategorije so obarvane enako (svetlo sivo), razen bilanc, ki AK Peters Visualization Series. CRC Press. so temnejše, da bolj izstopajo. Tokovi so različnih barv, ki so dolo- [6] Plotly. 2020. Plotly Python open source graphing library. čene tako, da so kategorije z istimi imeni vedno enako obarvane. Dostopano 1. 9. 2020. https://plotly.com/python/. To olajša razumevanje in primerjavo med različnimi leti prora- [7] Edward R. Tufte. 2001. The Visual Display of Qunatitative čuna. Z napisi na dnu prikaza, ki pojasnjujejo klasifikacijo, smo Information. Graphics Press. vnesli kontekst, ki pomaga pri orientaciji med spreminjanjem [8] Ministrstvo za finance Republike Slovenije. 2020. Državni pogledov. proračun. Dostopano 1. 9. 2020. https : / / www. gov. si / podrocja/finance-in-davki/drzavni-proracun/. 3.4 Razprava [9] Ministrstvo za finance Republike Slovenije. 2020. Državni Po začetnem testiranju uporabe, ki pa še ne vključuje prave upo- proračun 2020, Infografika. Dostopano 1. 9. 2020. https:// rabniške študije, lahko rečemo, da je Sankeyev diagram dober www.gov.si/assets/ministrstva/MF/Proracun-direktorat/ način za raziskovanje proračuna. Eden glavnih uvidov pri upo- Drzavni - proracun / Sprejeti - proracun / Sprejeti - 2020 / rabi orodja je bil, da je servisiranje javnega dolga večja postavka Infografika_PRORACUN_2020.pdf. od pričakovane (ker je poleg bilance odhodkov vsebovana tudi v [10] Ministrstvo za finance Republike Slovenije. 2020. Fiskalna računu financiranja, na preostalih vizualizacijah ne nastopa tako in javnofinančna politika. Dostopano 1. 9. 2020. https : izstopajoče). //www.gov.si/teme/fiskalna-in-javnofinancna-politika/. Interakcija omogoča “sprehajanje” po diagramu na različnih [11] Ministrstvo za finance Republike Slovenije. 2020. Proračun ravneh podrobnosti in v uporabniku zbudi željo po dodatnih Republike Slovenije. Dostopano 1. 9. 2020. https://podatki. informacijah, ki trenutno v vizualizacijo niso zajete. Te so na gov.si/dataset/proracun-republike-slovenije. voljo le v obrazložitvah proračuna v datotečnem formatu PDF, [12] Ministrstvo za finance Republike Slovenije. 2020. Proračun kar otežuje njihovo morebitno dodajanje v aplikacijo. Republike Slovenije, Aplikacija APPrA. Dostopano 1. 9. Verjetno največja prednost takšnega prikaza je primerjava med 2020. https://proracun.gov.si/. posameznimi kategorijami in tokovi, ki je precej bolj intuitivna od [13] Ministrstvo za finance Republike Slovenije. 2020. Vlada po- obstoječih vizualizacij proračuna. Slabost je odzivnost, za katero trdila predlog rebalansa letošnjega državnega proračuna. bi si želeli, da bi bila boljša. Žal je to lastnost, ki se je ne da dovolj Dostopano 1. 9. 2020. https://www.gov.si/novice/2020- dobro predvideti in se izkaže šele v zadnjih fazah implementacije 08 - 30 - vlada - potrdila - predlog - rebalansa - letosnjega - takšne aplikacije. drzavnega-proracuna/. Uporaba knjižnice Plotly je zelo olajšala delo in zmanjšala čas, potreben za razvoj takšne aplikcaije. Vendar ima ta enostavnost 750 MightyFields Voice: Voice-based Mobile Application Interaction Jernej Zupančič Miha Štravs Miha Mlakar Jožef Stefan Institute Faculty of Mathematics and Physics Jožef Stefan Institute Ljubljana, Slovenia Ljubljana, Slovenia Jamova cesta 39 Jožef Stefan International Faculty of Computer and Ljubljana, Slovenia Postgraduate School Information Science miha.mlakar@ijs.si Ljubljana, Slovenia Ljubljana, Slovenia jernej.zupancic@ijs.si miha.stravs996@gmail.com ABSTRACT feature cannot be specialized and has to work satisfactory in We present MightyFileds Voice (MFVoice), a service and an exten- general setting. Three steps are performed to enable voice in- sion of the MightyFields application that enables voice interaction teraction. First, speech is transformed into text by using Google with a mobile application. The user can issue voice commands speech-to-text (STT) engine [2]. Second, approach from [5] is for transitioning between application views and filling out the utilized to extract intent keywords. The full intended command forms. Google speech-to-text engine is used to obtain text, which is then inferred based on what the user is currently seeing on is then fed into the developed MFVoice service together with the screen and from the rest of the spoken words. Third, the the structured application view representation. MFVoice service recognized action is performed within the application itself. then returns appropriate action to take, which is executed by In Section 2, an architecture of our service is presented. In the Mighty Fields application extension. The MFVoice natural Section 3, we present our MFVoice natural language understand- language understanding service was tested in real-life use cases, ing (NLU) service and show its implementation. We then explain achieving 93% intent recognition accuracy, 88% entity recogni- the tests conducted on the service and their results in Section tion success when the system was used as intended. When no 4 and discuss them in section 5. We conclude the paper with a training to the user was provided, intent and entity recognition summary in Section 6. achieved 68% and 52% accuracy, respectively. Note that in case of no training provided, the users assumed general knowledge 2 MFVOICE ARCHITECTURE of the language semantics, which is out-of-scope for the current MFVoice comprises several parts (Figure 1) that enable voice state-of-the-art research in natural language. interaction: (1) MF application itself: this is the main MightyFields appli- KEYWORDS cation. voice assistant, voice interaction, natural language understanding (2) MF agent: the program that enables programmatic access to the application view - reading and interacting. 1 INTRODUCTION (3) STT: a service that transforms spoken commands into Interaction with devices by voice has become quite common in text. recent times. More known examples of applications allowing (4) MFVoice NLU service: the service that parses free text and voice commands are voice assistants like Cortana [4] and Siri [1]. returns structured information about recognized intent Voice interaction is attractive to users as it offers a hands-free and entities. application interaction and is therefore a desired feature in many applications. This feature is useful for people with spelling diffi- 3 THE MFVOICE NLU SERVICE culties. It can also help those with physical disabilities who often The MFVoice NLU comprises the following steps (Figure 2): find typing difficult. The proposed service is not used for two- (1) Application view context processing way conversation, as in platforms such as the one from Rasa [3]. (2) Intent recognition However, the part of the service used to recognize user’s com- (3) Entity recognition mand, is very similar to the ones from other virtual assistants. When the application context and transcription of the voice The modifications applied take into account the specifics of the command are provided to the NLU application programming task at hand. interface (API), the service first identifies possible actions to take, In this paper we focus on the task of filling out custom forms given the context, then it processes the context content, which through the voice interaction. Here, a custom form is a small in turn enables recognition of the intent and, finally, the entities. information gathering application, made for specific purpose, The so-obtained structured action data is then forwarded back e.g., electric grid inspection form, or police report regarding an to the MF agent, which can execute appropriate actions. In this incident. Since the domain is open ended, i.e., each individual section we will describe each of the MFVoice NLU parts in more can make his or her own custom forms, the voice understanding details. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or 3.1 Application View Context Processing distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this The application view context provides structured data on the work must be honored. For all other uses, contact the owner/author(s). elements that are visible on the screen. This includes field labels, Information society ’20, October 5–9, 2020, Ljubljana, Slovenia field IDs, possible values of fields (where applicable), interaction © 2020 Copyright held by the owner/author(s). options, and available tabs for multi-page forms. Upon the API 751 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Novak, et al. (4) “Tap” the field or graphical element. This is used to interact with buttons and navigate the application. Due to non-existent training data, keyword-based intent recog- nition was utilized. For each intent a set of intent “key-phrases” were defined: (1) “Choose”: choose, pick, select, is (2) “Write”: is, write, input (3) “Clear”: clear, delete, remove (4) “Tap”: choose, go to, tab, click, pick In the intent inference step, the score for each of the “key- phrases” is computed. If the highest score exceeds the predefined threshold, the corresponding intent is chosen [5]. To simplify the NLU pipeline only one intent and one field per utterance is allowed. This is especially problematic in voice assistants, since the users naturally communicate differently when talking than when writing. To resolve the disambiguation of one “key-phrase” being associated with multiple intents, the following order of intents is taken into account: “Choose”, “Write”, “Clear”, “Tap”. Further, since not every intent is possible with every field, the intent list is first filtered and only the intents that make sense in the current context are kept and iterated over. For instance, Figure 1: The MFVoice architecture overview if the context comprises only of the input fields and navigation tabs, “Choose” does not make sense. The “key-phrases” used for inferring the intent are tagged with Voice com- Application the intent tag (IT), which is later used in the entity recognition mand (text) context step. Preprocess 3.3 Entity Recognition context. There are two types of entities present in our use-cases: “label Recognize entities” (e.g., name in “The name is John.” ) and “value entities” intents. (e.g., John in “The name is John.” ). Label entities are the labels of the fields in the user generated Recognize form. Since they are user generated, their value is not restricted. entities. Their semantic meaning is sometimes harder to grasp automat- ically, since not much additional info is usually provided (for instance description). In general, the recognition of label entities Structured cannot be learning-based, since the users are not expected to action data provide examples. Value entities can further be divided into known value entities Figure 2: The MFVoice service processing pipeline (button labels, the items in the drop-down lists or checkbox lists and similar) or unknown value entities (text input fields). The call, the application context is pre-processed. The text visible to reasoning for known value entities is the same as for the label the user is normalized and transformed into search friendly form entities – they are user generated and cannot be learned in gen- that is used in intent and entity recognition. eral. For the unknown value entities, the value corresponding to The transformation is cached to speed-up its future use in a certain label should be recognized from the free text, generated subsequent steps. Least recently used cache is used, since user from the STT service. The unknown value entities can comprise interacts with one application view as long as he or she does not one or several words. fill-out the form in short time period. Score, related to the probability of the entity appearing in the text, is used to recognize the label entities and known value 3.2 Intent Recognition entities, while a heuristic is used to recognize the unknown value entities. Intent defines what the user wants the application to do. In the case of form filling, the following intents were identified: 3.3.1 Label and Known Value Entities Recognition. These enti- (1) “Choose” an element from a list of elements. This is often ties are the ones set by the user in the form creation phase. To used to pick the element from a dropdown or checklist recognize the entities from free text, text similarity scores are elements. applied and evaluated for each possible label or known value (2) “Write” some text into a field. This is used for input or entity [5]. Only the entities with scores that exceed threshold are text-area elements. recognized and can be used in the next pipeline steps. (3) “Clear” the value of a field to delete a wrong value entry In some instances, the MFVoice NLU has to modify the text for any kind of element. received by the STT engine. Common examples for this are: 752 MightyFields Voice: Voice-based Mobile Application Interaction Information society ’20, October 5–9, 2020, Ljubljana, Slovenia (1) Letter-by-letter dictation transformation, e.g. in transcribed (2) If IT tag is present in the text, then begin tagging word to command “the form ID is 1 2 3 4 5 a” the empty spaces in the left or to the right of LE-tagged word with OTHR tag. the form ID have to be deleted so “12345a” is obtained. Stop if text-end or IT-tagged word are reached. Check if (2) Zero padded numbers transformation, e.g. in transcribed there is any remaining word: command “the house number is 23”, sometimes the drop- (a) If there are remaining words, tag those with UVE tag. down values include only known value entity “023”. There- fore, the preceding zeros have to be dropped when com- his name really is John Doe puting the text similarity. OTHR LE OTHR IT UVE (3) Numbers in text transformation, e.g. in transcribed com- mand “pick option three”, the number “3” is transcribed (b) If there are no remaining words, re-tag all the words to as “three”. In those cases, the textual representation has the right of LE tag with UVE tags. to be transformed into a number. insert the name John Doe The words that correspond to the highly-scored entities are IT OTHR LE UVE tagged with the label entity (LE) or known value entity tag (KVE), to be later used in the unknown value entity recognition. The previous steps capture the majority of the unknown value Some examples of label entity and known value entity recog- entity recognition cases. However, there are still commands that nition are: would not be understood by the MFVoice NLU service: (1) (1) form number 123456 John Doe the name is ̸= John Doe the name is LE KVE OTHR LE IT UVE OTHR LE IT (2) (2) female KVE John Doe really is his name Note that when the user speaks command “female”, the MFVoice UVE IT OTHR LE NLU service recognizes the known value entity that belongs to ̸= John Doe really is his name the field with label “sex”. Additionally, even without specifying the intent keyword, the application logic infers that the user UVE OTHR IT OTHR LE wants to pick the option “female” in the field “sex”. 4 TESTING Since the text similarity metrics are used for scoring the labeled and known value entities, in some cases the entities are not The MFVoice NLU service was tested in two ways: laboratory recognized correctly: testing and real-world testing. For laboratory testing, the text was entered into the service directly, bypassing the STT ser- (1) Multi-word synonyms are not recognized, e.g. “city” ∼ vice. This way, the STT performance issues were ignored and “place of living” only the recognition capability of the MFVoice NLU service was clear the place of living tested. The examples, however, were still obtained from the final MFVoice users. The test user was presented with an application IT OTHR screen and told to fill the form using only his or hers voice. While the systems supports synonyms, they have to be For the real-world testing, the users were given written in- manually entered by the form creator and are therefore structions on how to use the app, however, no instruction on less practical. how to actually voice commands were given. First, the form was (2) Multiple occurrences of the same or very similar label filled out using screen and keyboard interactions. Second, the entities or known value entities cannot be properly dis- field that a user wants for fill with a voice command was marked. ambiguated. Consider, for example, a form that comprises Third, voice interaction was activated and the command was house number field with possible value “4”, and household spoken. Fourth, the transcribed voice command, the context, and size field also with possible value “4”. User usually fills the the marked item were stored for future analysis. We did not pro- form in a linear way, top to bottom. When the user encoun- vide any examples on how to use MFVoice. This allowed us to ters the first of the mentioned field, he or she may voice research what the users actually expect from the system. command “four”. In this case, NLU service will provide The forms used in testing included six free-text input field wid- two possible actions: “house number is 4” and “household gets (name, surname, age, settlement, street, house number), one size is 4”. radio widget with two options (gender: male, female), one check- box field with five options (language: Slovene, Slovak, Spanish, 3.3.2 Unknown Value Entity Recognition. The unknown value entity recognition is computed only when the intent “Write” is Swedish, Sumerian), and four dropdown fields (country, settle- considered, since this is the only type of the“open” form field ment, street, and house number). that allows for unknown values. The following heuristic is used to tag the unknown value entity (UVE): 4.1 Laboratory Testing Set-up and Results (1) If IT tag is not present in the text, every word not tagged We have gathered 70 and 69 commands for application interaction with LE is tagged with UVE. in Slovenian and English languages, respectively. Laboratory testing is performed upon each git push to the code repository and age 31 is run within the continuous integration pipeline. This enables LE UVE us to track the performance of the MFVoice NLU pipeline. 753 Information society ’20, October 5–9, 2020, Ljubljana, Slovenia Novak, et al. Table 1: Intent confusion matrix for commands in Slove- 5 DISCUSSION nian According to the results, the intent recognition process performs very good, despite the fact that it is only based on keyword write choose clear tap missing recognition and the context processing. We do not think that any write 22 0 0 0 2 additional work would benefit the performance in this regard, choose 0 21 0 0 0 with the exception of adding additional intent keywords, which clear 0 0 2 0 0 will be obtained during the application usage. tap 0 0 0 20 3 After the user familiarizes with the way the MFVoice appli- cation works, also the named entity recognition performs well. Most of the errors were actually a result of a user expecting the system to be too advanced. All 43 incorrectly recognized entities 4.1.1 Intent Recognition. After each continuous integration were the result of MFVoice not being able to reason that, for pipeline run, the intent confusion matrix is computed. Table 1 is instance, “John” is a person name. While this could be done for an example of the intent confusion matrix for voice commands certain special cases, e.g. person names and geographic names, in Slovenian for the last version of MFVoice. According to the at the moment this cannot be solved in general. This is a result matrix, the accuracy of intent recognition is above 90%. The only of letting the users to create their own forms, which are often errors were the ones, where the system was not able to deter- very domain specific. In the future we will perform the testing mine the item to be interacted with, which was labeled with the of the system after users are given some basic training on how “missing” classification label. to use MFVoice. This should greatly improve the percentage of 4.1.2 Entity Recognition. For each command also the field labels properly labeled instances and also help us uncover additional and values recognized by the NLU service and the ground truth edge cases to be addressed by the entity recognition pipeline. labels and values are compared. Examples where the NLU fails The MFVoice NLU was designed in a way to easily support to recognize the label or value correctly are: multiple languages. In the current form, to support a new lan- guage, the translations of the intent keywords and language (1) “Age 26 years.” Expected value: “26”, got “26 years” word vectors have to added. For certain languages the module (2) “She is 26 years old.” Expected label: “age”, got nothing. for unknown value entity has to be adjusted, since the sentence (3) “She lives in Ljubljana.” Expected label: “Place”, got noth- syntax can be different. This enabled us to quickly add support ing. for English, after Slovenian voice interaction performed well. 4.2 Real-life Testing Set-up and Results 6 CONCLUSION We have gathered 172 spoken voice commands in the real-life In this paper we presented our service that is used for filling forms setting in Slovenian. Unfortunately, there were only 86 commands with voice commands in a mobile application. While some oper- that were labeled correctly by the test users and STT performed ating system do include voice interaction, e.g., Cortana [4] and well there. STT issues occurred in 42 out of 172 cases (24%). These Siri [1]), their use in a dedicated application is limited. MFVoice could either be result of too much background noise, command enables more advanced voice interaction. MFVoice application not being recorded properly, or just the problem with the STT first gets the text which was converted from speech by using service used for the Slovenian language. Incorrect user labeling the Google STT engine [2]. Then, the MFVoice NLU service occurred in 42 out of 172 cases (24%). The most common mistakes uses keyword recognition and context preprocessing to infer the in those cases were: the user forgot to set the ground truth either command the user intended. Because of the simplicity of the by entering the value or choosing the item, the user obviously implementation, the service is less accurate when commands picked the wrong item (e.g., for command “the name is John” an are voiced in the form of long and complex sentence. However, item with label age was selected). this simplicity does make the service more robust and accurate Out of 86 valid commands, 45 were recognized correctly and 41 with commands voiced in concise form. We believe that users incorrectly. For 23 cases the label value was completely missing should have a comfortable user experience, after they get used and could not be inferred from the surrounding text (e.g., “John”, to forming commands in a more concise manner. “45”, “Ljubljana”). For 18 cases the label value could be inferred from the surrounding text (e.g., “he is 23 years old”, “she lives in ACKNOWLEDGMENTS Ljubljana”). In some cases (12) this would require some general Comland d.o.o. funded the research presented in this paper. reasoning about the words and their relations and in other the unknown value entity included additional text, e.g. “his name REFERENCES miki”, was not recognized because of minor STT-engine mistakes (1), or the known value entity score was not high enough to be [1] Apple. 2020. Siri. https://www.apple.com/siri/. (2020). included (5). This results in 88% accuracy for entity recognition [2] Google. 2020. Speech-to-text: automatic speech recognition. when the system was used as intended, 72% when the synonyms https://cloud.google.com/speech-to-text/. (2020). were assumed, and 52% when general knowledge of the language [3] Rasa Technologies Inc. 2020. Rasa. https://rasa.com/. (2020). semantics was assumed. [4] Microsoft. 2020. Cortana - your personal productivity as- Note that the testing was performed without some planned sistant. https://www.microsoft.com/en-us/cortana/. (2020). features implemented. The Zero padded numbers transformation [5] Miha Štravs and Jernej Zupančič. 2019. Named entity recog- and Numbers in text transformation steps were missing. The accu- nition using gazetteer of hierarchical entities. In Interna- racy percentages should improve to 94%, 76%, and 56% for uses as tional Conference on Industrial, Engineering and Other Ap- intended, assuming synonyms, and assuming general knowledge plications of Applied Intelligent Systems. Springer, 768–776. of language semantics, respectively. 754 eBralec 4: hibridni sintetizator slovenskega govora Jerneja Žganec Gros Miro Romih Tomaž Šef Alpineon d.o.o. Amebis d.o.o. Institut “Jožef Stefan” Ulica Iga Grudna 15 Bakovnik 3 Jamova cesta 39 1000 Ljubljana, Slovenija 1241 Kamnik, Slovenija 1000 Ljubljana, Slovenija jerneja.gros@alpineon.si miro.romih@amebis.si tomaz.sef@ijs.si POVZETEK snemanju je manj uporabna za uporabo v mobilnih aplikacijah ob hrupnem akustičnem ozadju. V članku predstavljamo nov sintetizator slovenskega govora Zato smo velik del analize posvetili možnim izboljšavam pri eBralec4 (https://ebralec.si/). Razvit je bil povsem nov ženski glas » gradnji nove govorne zbirke, ki omogoča boljše delovanje Nadja eBralec«, ki je razumljivejši in zveni bolj naravno od akustičnega modula. To še posebej velja za ženski glas, ki ga je predhodnega ženskega glasu. Opisujemo zgradbo sintetizatorja zaradi fizikalne narave tudi sicer težje kvalitetno sintetizirati. govora, njegove module, jezikovne vire uporabljene pri razvoju ter Nova potek izgradnje govorne zbirke za nov ženski glas. govorna zbirka za glas » Nadja eBralec« je bila posneta z branim govorom. To ustreza najpogostejšim oblikam rabe sintetizatorjev KLJUČNE BESEDE govora, lažje je izdelati transkripcijo, snemanje je bolj nadzorovano in predvidljivo. Pri spontanem govoru je namreč govorno zbirko sinteza slovenskega govora, govorna zbirka, postopek sinteze težko fonetično in prozodično uravnotežiti. slovenskega govora Na osnovi analize delovanja izhodiščnega jezikovnega modula smo izboljšali pomensko analizo povedi in na novo razvili 1 samodejno določanje vrste povedi, ki ima še posebej veliko težo Uvod tudi v postopku gradnje govorne baze. V članku predstavljamo nov sintetizator slovenskega govora Izpostavljene so bile tudi težave eBralca pri sintetiziranju eBralec4 (https://ebralec.si/). Pri razvoju smo izhajali iz obstoječe kratkih besedilnih segmentov in posameznih simbolov, kar se kot tehnologije, sintetizatorja govora za slovenski jezik eBralec [1], ki najbolj moteče pokaže pri črkovanju, ki je bilo mestoma slabo je bil razvit v okviru projekta Knjižnica slepih in slabovidnih, in je nerazumljivo. Težavo smo rešili z uvedbo hibridnega pristopa k prvenstveno namenjen slepim in slabovidnim uporabnikom ter akustičnemu modeliranju govornega signala, kjer kratke segmente osebam z motnjami branja. sintetiziramo z visoko razumljivo difonsko konkatenacijo govornih V okviru projekta CityVOICE smo identificirali več priložnosti segmentov, daljše segmente pa z naravno zvenečimi za izboljšavo in nadgradnje eBralca, tako glede naravnosti kot tudi parametričnimi reprezentacijami govornega signala s pomočjo razumljivosti. V sodelovanju s skupino končnih uporabnikov smo prikritih Markovovih modelov. pregledali in raziskali pomanjkljivosti obstoječega sintetizatorja Obstoječima glasovoma eBralca, moškemu glasu » Renato govora ter zbrali dodatne želje končnih uporabnikov za izboljšave eBralec« in ženskemu glasu » Maja eBralec«, se je v novem sintetizatorja govora, kar je rezultiralo v novem produktu eBralec4. produktu eBralec4 pridružil novi in opazno bolj naravno zveneči Kot poglavitna pomanjkljivost se je izkazala prvotna govorna ženski glas » Nadja eBralec«. zbirka, na kateri sloni delovanje izhodiščnega sintetizatorja govora. V članku opisujemo zgradbo sintetizatorja govora, njegove Ni zasnovana dovolj konsistentno (deloma neustrezni in module, jezikovne vire, ki so bili uporabljeni pri njegovem razvoju, spremenljivi snemalni pogoji) in robustno – v smislu zajema potek izgradnje nove govorne zbirke za ženski glas » Nadja raznovrstnosti ciljnega besedišča, kar povzroča slabšo razumljivost eBralec« in postopek hibridnega akustičnega modela za generiranje sintetičnega govora ob črkovanju in izgovarjavi posebnih govornega signala. Opisujemo tudi izboljšave pri jezikovni analizi simbolov. vhodnega besedila. Identificirana je bila tudi spremenljiva kakovost sintetiziranega govora, ki izhaja iz sejne spremenljivosti ob snemanju izvorne govorne zbirke. Zaradi neustreznega dinamičnega obsega pri 2 Zgradba sintetizatorja Permission to make digital or hard copies of part or all of this work for personal or Naloga jedra sintetizatorja govora eBralec oziroma povezovalnega classroom use is granted without fee provided that copies are not made or distributed cevovoda je povezovanje sestavnih modulov sintetizatorja govora for profit or commercial advantage and that copies bear this notice and the full citation v enoten proces. Jedro sintetizatorja govora usklajuje delo on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). posameznih delov sintetizatorja tako, da v ustreznem vrstnem redu Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia vključuje oziroma kliče module sintetizatorja govora. Posamezni © 2020 Copyright held by the owner/author(s). moduli pretvorbe zaradi pohitritve in večje paralelizacije procesov lahko hkrati delujejo v ločenih nitih. 755 Zasnova jedra sintetizatorja govora eBralec je prikazana na sliki vsebovane vse potrebne informacije o izgovarjavi besed glede na 1. Moduli, ki jih vključuje jedro eBralca, so: jezikovni analizator, njihovo pozicijo in pomen v vhodnem stavku oziroma povedi. besednik, modul za grafemsko-fonemsko pretvorbo in modul za Modul besednik v odvisnosti od vhodnih nastavitev poskrbi za sintezo govornega signala [1]. Na vhodu in izhodu se jedro pretvorbo simbolov in števil v besede. Ti elementi so namreč zelo sintetizatorja govora lahko poveže z ustreznim vmesnikom, npr. pogost sestavni del besedil, zato je njihovo pravilno izgovarjanje SAPI 5, s pomočjo katerega vhodno besedilo z morebitnimi pomembno za razumljivost govora. Modul »grafemsko-fonemska dodatnimi ukazi spreminja v ustrezen govorni signal. pretvorba« poskrbi za pretvorbo v fonemski zapis. Vhodno besedilo sprva obdela jezikovni analizator, ki poskrbi Modul za »sintezo govornega signala« je zadolžen za za ustrezno predobdelavo vhodnega besedila ter razdvoumljanje oblikovanje prozodije in tvorjenje izhodnega govornega signala. izgovornih različic. Rezultat modula je zapis, v katerem so Slika 1: Shema jedra sintetizatorja govora. računalniško predstavitev leksikalnih jezikovnih virov, ki jih razvijamo v okviru projekta OptiLEX. Pri tem rešujemo vrsto 3 Jezikovna analiza besedila problemov, kot so: zahteva po delovanju v realnem času, zahteva Jezikovna analiza uporablja podatke iz Amebisove jezikovne baze po kompaktnem zapisu jezikovnih virov ter zahteva po majhnem Ases [2]. Ta za slovenščino v tem trenutku vsebuje več kot 257.000 odtisu zapisa jezikovnih virov v delovnem pomnilniku [4]. lem, ki vsebujejo 8,1 milijona oblik, od katerih je 5,7 milijona oblik dodatno opremljenih s podatki o izgovarjavi. Dodatno je za 3.1 Samodejno določanje vrste povedi slovenščino v bazi še 36.000 zvez in 8.000 glagolskih predlog. Pri izbiri optimalnih fonetično in drugače uravnoteženih besedilnih Glagolske predloge podajajo informacije o vezljivosti glagola. predlog za govorno bazo smo se posvetili izboljšanemu Jezikovni analizator mora narediti razrez besedila na povedi, označevanju povedi, predvsem označevanju in določanju vrste stavke in besede, potem pa za vsako besedo določiti še ustrezno povedi, kjer smo poleg klasične metode s pomočjo pravil analizirali lemo in oblikoskladenjsko oznako. Ases ločuje leme, ki se različno tudi možnost določanja vrste povedi s pomočjo različnih metod izgovarjajo, npr. »téma« in »temà« predstavljata dve ločeni lemi. strojnega učenja. Razviti postopek smo uporabili tudi v izboljšani Jezikovni analizator deluje na podlagi pravil in podatkov iz različici jezikovnega analizatorja. jezikovne baze Ases, pri čemer so osnova glagolske predloge. Za potrebe določanja vrste povedi, predvsem večstavčnih, smo Na izboljšano delovanje sintetizatorja govora lahko jezikovno definirali ustrezne zapise. Osnovni zapis, prilagojen zdajšnjemu procesiranje vpliva predvsem s še boljšo analizo besedila, ki jo zapisu analize povedi, je kompleksen. Poved je zapisana v lahko uporabimo tako v postopku gradnje govorne baze kot tudi pri posebnem meta jeziku, ki vsebuje vse informacije, ki jih lahko analizi besedila v fazi sintetiziranja govora izluščimo iz povedi na osnovi avtomatske stavčne analize. Na podlagi identificiranih težav delovanja jezikovnega modula Tak zapis omogoča združen zapis večstavčnih povedi, v obstoječega sintetizatorja smo veliko pozornosti posvetili možnim katerem nastopajo tudi vse stavčne odvisnosti. Stavki v povedi izboljšavam jezikovnega analizatorja. Posebej pomembni med namreč lahko nastopajo kot priredja, soredja ali podredja. V njimi sta izboljšanje pomenske analize povedi in določanje vrste primeru podredja pa je navzoča tudi informacija glede njihove povedi, ki ima še posebej veliko težo tudi v postopku gradnje odvisnosti, torej ali gre za prilastkov, osebkov, predmetni, prislovni govorne baze, gl. poglavje 4. ali kateri drugi odvisnik. Raziskali smo tudi možnost pohitritve odzivnosti oz. latence jezikovnega analizatorja s pomočjo postopkov za učinkovito 756 Poleg tega daljšega zapisa smo definirali tudi skrajšan, Snemanje govornega gradiva je potekalo ob prisotnosti poenostavljeni zapis, ki podaja informacijo o vrsti povedi, ki smo izkušenega snemalnega operaterja z namenom, da se je preprečilo ga uporabili pri izbiri končne množice izbranih povedi. neustrezne izgovarjave besedilnih predlog in napake pri snemanju Ker izboljšani stavčni analizator svojo analizo zapiše v daljšem govora, gl. sliko 2. zapisu, smo razvili pretvornik iz tega zapisa v poenostavljeni zapis, ki ohrani le najbolj pomembne podatke o tipu strukture povedi. Primer tega zapisa za poved " Miha, ki je bil lačen, je pojedel malico." je " [[-gp|[[-r-|]]]]" . S pomočjo pretvornika smo vhodni množici povedi dodali informacijo o vrsti povedi, ta pa je v postopku izbire povedi služila kot eden izmed parametrov pri izbiri in uravnoteženju ciljnega števila povedi. Analizator, ki zapiše analizo povedi z informacijo o vrsti povedi v daljši zapis, smo realizirali s pomočjo pravil in z metodami strojnega učenja. V analizator smo vgradili rešitev, ki je ob evalvaciji dala najboljše rezultate [5]. 4 Govorna zbirka CITYVOICE V osrednjem delu analize smo izhajali predvsem iz zaznanih pomanjkljivosti obstoječega sintetizatorja govora, eBralca, ki bi jih bilo mogoče izboljšati, ter zbranih uporabniških zahtev ter identificirali priložnosti za razvoj izboljšanega produkta. Sem Slika 2: Govorka med snemanjem oz. branjem pripravljenega vsekakor sodijo težave zaradi neoptimalne govorne baze, zato smo gradiva v tonskem studiu. V ozadju tonski tehnik, ki med velik del analize posvetili možnim izboljšavam pri gradnji nove snemanjem na zaslonu spremlja tako signal laringografa Lx govorne baze, ki pomembno vpliva na izboljšano delovanje kot tudi mikrofonski signal Sp. akustičnega modula sintetizatorja govora. Izbira velikosti govorne zbirke je posledica kompromisa med Govorcu smo pred snemalnimi sejami podali ustrezna navodila želenim številom variacij glasov oz. njihovim pokritjem na eni in ga zaprosili, da povedi prebira razločno in enakomerno hitro. strani ter časom in stroški, vezanimi na razvoj, na drugi strani. Med branjem besedila so imeli govorci nameščene elektrode Upoštevali smo tudi čas za kasnejše preiskovanje govorne zbirke in laringografa, s katerimi smo spremljali nihanje njihovih glasilk potreben prostor za njeno hranjenje. Najpomembnejši preostali zaradi lažjega kasnejšega označevanja osnovnih period govornega dejavniki, ki smo jih upoštevali pri snovanju nove govorne zbirke signala, gl. sliki 1 in 2. Uporabili smo tri nivoje anotacij oz. za sintezo govora, so: izbira vsebine posnetkov, izbira govorcev, prepisov govorjenega besedila: grafemski prepis, fonetični prepis postopek snemanja in označevanje posnetkov. in prozodijske oznake (slika 3). Izbor povedi za govorno bazo poteka na osnovi večjega števila kriterijev, med katerimi so pokritost osnovnih govornih enot, uravnoteženost dolžin, tipov in vrst povedi, pravilna fonetična transkripcija itd [6]. Med njimi bi posebej omenili vrsto povedi. Ta omogoča bolj natančno modeliranje prozodije, ki je pomembna za naravnost sintetičnega govora. Ena od glavnih težav starega postopka je bila v tem, da nismo imeli orodja za avtomatsko določanje vrste povedi, kar bi lahko bistveno pohitrilo in izboljšalo izbiro povedi. Pri izbiri optimalnih fonetično in drugače uravnoteženih vsebin (povedi) smo se zato v veliki meri posvetili izboljšanemu označevanju povedi, predvsem označevanju in določanju vrste povedi, kjer smo poleg klasične metode s pomočjo pravil analizirali tudi možnost določanja vrste povedi s pomočjo različnih metod strojnega učenja, kot je to opisano v poglavju 3.1. Za razliko od avtomatskega določanja tipa povedi, ki je v večini primerov odvisna od končnega ločila (trdilni, vprašalni, velelni) je določanje vrste povedi precej bolj zapleteno. Če je poved Slika 3: Primer govornega signala z označenimi osnovnimi enostavčna, težav ni. Če pa je poved večstavčna, je potrebna periodami. Zgoraj je govorni signal posnet z mikrofonom, sledi zahtevna analiza povedi in vseh njenih stavkov za določitev njihove signal laringografa Lx in spektralna prikaza obeh signalov. odvisnosti. Ti lahko nastopajo kot priredja, soredja ali podredja. Navpične črte predstavljajo oznake period govornega signala. 757 Uporabili smo tri nivoje anotacij oz. prepisov govorjenega 6 Zaključek besedila: grafemski prepis, fonetični prepis in prozodijske oznake V prispevku smo predstavili zasnovo in izvedbo novega (slika 3). visokokakovostnega sintetizatorja govora za slovenski jezik, eBralec4. Za samodejno tvorjenje govora smo uporabili 5 Akustično modeliranje govora s hibridnim optimizacijo postopka pridobivanja govornih jezikovnih virov v kombinaciji z napredno parametrično predstavitvijo govora z postopkom modeliranjem govora s pomočjo prikritih Markovih modelov ter Specifikacije končnih uporabnikov so narekovale hitro odzivnost difonsko konkatenacijsko sintezo govora za sintezo krajših sintetizatorja govora ter kompaktno velikost pomnilniškega govornih segmentov, predvsem pri črkovanju. prostora, potrebnega za namestitev ter delovanje sintetizatorja Izdelali smo govorno zbirko za nov ženski glas, » Nadja govora. eBralec«. Pri izdelavi govorne zbirke smo posebno pozornost To je ponovno narekovalo izvedbeno različico končnega namenili določanju optimalnih pogojev za snemanje ter določanju sintetizatorja govora, ki, podobno kot pri eBralcu, temelji na optimalnih fonetično in drugače uravnoteženih besedilnih vsebin, parametrični predstavitvi zakonitosti govora v slovenskem jeziku pri čemer smo dodali raznovrstnost povedi glede na novo razviti [1] z uporabo prikritih Markovovih modelov PMM [7,8]. Teh postopek samodejnega določanja zvrsti povedi. zakonitosti se sintetizator govora nauči samodejno na podlagi obsežnega učnega govornega korpusa, ki je bil posebej posnet v te namene, in ki vključuje relevantne akustične ter prozodijske Zahvala fenomene, ki so značilni za govorjeno slovenščino. Razvojno raziskovalno delo je bilo delno financirano v okviru Sinteza govora z uporabo prikritih modelov Markova (PMM) projekta CityVOICE s strani Republike Slovenije in Evropske unije ima v primerjavi z bolj klasičnimi postopki tvorbe govora, pri iz Evropskega sklada za regionalni razvoj, in sicer v okviru katerih govor tvorimo z »lepljenjem« krajših ali daljših govornih »Operativnega programa za izvajanje evropske kohezijske politike izsekov, nekaj privlačnih prednost, saj za zadovoljivo kakovost v obdobju 2014-2020«. Raziskave učinkovitega zapisa jezikovnih govora potrebujemo razmeroma majhno govorno zbirko (zadošča virov je delno sofinancirala Javna agencija za raziskovalno že ura ali več posnetega govora). Nadalje omogoča enovito, dejavnost Republike Slovenije v sklopu aplikativnega kakovostno in sočasno modeliranje akustičnih in prozodičnih raziskovalnega projekta OptiLEX (L7-9406). značilnosti govora. Omogoča tudi zgoščen zapis akustičnega in prozodijskega modela govora, saj za tvorbo govora ni treba hraniti LITERATURA IN VIRI celotne izvorne govorne zbirke. [1] Jerneja Žganec Gros, Boštjan Vesnicer, Simon Rozman, Peter Holozan, Tomaž Po drugi strani pa imajo sistemi PMM tudi nekatere slabosti. Šef, 2016. Sintetizator govora za slovenščino eBralec. Konferenca Jezikovne Govor je lahko na trenutke nekoliko manj razumljiv. Govor ima tehnologije in digitalna humanistika, Ljubljana. lahko ponekod značilen »robotski« prizvok, ki je posledica [2] Špela Arhar in Peter Holozan. 2009. ASES – leksikalna podatkovna zbirka za razvoj slovenskih jezikovnih tehnologij. V Mikolič (ur.). Jezikovni korpusi v parametrizacije govornega signala. medkulturni komunikaciji. Koper: Založba Annales. Podrobna analiza uporabniške izkušnje slepih in slabovidnih [3] Peter Holozan. 2004. Uporaba glagolskih predlog pri strojnem prevajanju. V: uporabnikov eBralca je pokazala, da je še posebej slabo razumljiva Zborniku Konference JEZIKOVNE TEHNOLOGIJE 2004, uredila T. Erjavec in J. Žganec Gros, str. 128. Ljubljana. sinteza govora krajših besednih enot, kot je denimo črkovanje, ki [4] Žiga Golob, Jerneja Žganec Gros, Mario Žganec, Boštjan Vesnicer, " FST-based ga ta skupine končnih uporabnikov zelo pogosto uporablja. Slepi in pronunciation lexicon compression for speech engines" International Journal of slabovidni uporabniki namreč za uspešno uporabo računalnika Advanced Robotic Systems, zv. 9, 2011.. uporabljajo t. i. bralnike zaslona, programe, ki s pomočjo [5] P. Holozan, M. Romih, S. Rozman, 2019, R2.2 – Zasnova govorne zbirke, projektno poročilo CityVoice – govorne tehnologije z naprednimi jezikovnimi sintetizatorja govora uporabnikom sporočajo informacije o tem, kaj viri. se prikazuje na ekranu. [6] Tomaž Šef, Miro Romih, Jerneja Žganec Gros, 2019. Izdelava govorne zbirke Za točno sliko ekrana zelo pogosto uporabijo branje v načinu za sintezo slovenskega govora, Informacijska družba IS 2019. črkovanja [7] T. Toda in K. Tokuda. 2007. A speech parameter generation algorithm , ki besede bere črko po črko, oz. znak po znak. Pri tem considering global variance for HMM-based speech synthesis. IEICE je potrebna velika hitrost branja oz. izgovarjanja, pri čemer metoda Transactions Inf. Syst. PMM ni najbolj uporabna, ker je premalo odzivna ter rezultira v [8] H. Zen in H. Sak. 2015. Unidirectional long short-term memory recurrent neural network with recurrent output layer for low-latency speech synthesis. V: manj razumljivih kratkih izoliranih segmentih. Proceedings of the ICASSP, str. 4470–4474. Ker je postopek sinteze s pomočjo PMM manj primeren za [9] Jerneja Žganec Gros in Mario Žganec. 2008. An efficient unit-selection method uspešno sintezo kratkih govornih segmentov, smo se odločili za for concatenative text-to-speech synthesis systems. CIT, zvezek. 16, št. 1, str. 69-78. razvoj unikatnega hibridnega akustičnega modela, ki omogoča [10] C. Hamon, E. Moulines, F. Charpentier, (1989), “A Diphone System Based on kakovostno sintezo govora kratkih govornih segmentov s pomočjo Time-Domain Prosodic Modifications of Speech”, Proceedings of the difonskega sintetizatorja govora z uporabo konkatenacije osnovnih International Conference on Acoustics, Speech, and Signal Processing ICASSP 89, S5.7, str. 238–241. govornih segmentov z metodo TD-PSOLA [9,10], daljši govorni segmenti pa so generirani z uporabo pristopa s pomočjo prikritih Markovovih modelov PMM. 758 Sound 2121: The Future of Music Jordan Aiko Deja Nuwan Attygale jordan.deja@famnit.upr.si nuwan.attygalle@upr.si University of Primorska University of Primorska UP FAMNIT UP FAMNIT Koper, Slovenia Koper, Slovenia Klen Čopič Pucihar Matjaž Kljun klen.copic@famnit.upr.si matjaz.kljun@famnit.upr.si University of Primorska University of Primorska UP FAMNIT UP FAMNIT Koper, Slovenia Koper, Slovenia Fakulteta za Informacijske Študije Fakulteta za Informacijske Študije Novo mesto, Slovenija Novo mesto, Slovenija Figure 1: Concept: We see a future where we no longer need tangible interfaces. Rather humans would let go of these interfaces to give way to a more seamless music interface. ABSTRACT really is music? What is the future of music? How will we Music has always been an integral part of our society since consume music a hundred years from now?” In this paper, the prehistoric times. For the past five centuries, music in- we shortly present how music has been consumed through- struments have been perfected and the industry is nowadays out history and how we imagine it a century from now. We worth billions of dollars. With recent innovations in com- make a wild speculation about the future of music and its puter interfaces, music information retrieval and artificial interface, while encouraging the discussion regarding these intelligence, playing music is not in the sole domain of hu- visions. mans anymore. Thus we are faced with the questions: “What KEYWORDS Permission to make digital or hard copies of part or all of this work for music, interface, interaction design, sound, future personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third- 1 INTRODUCTION party components of this work must be honored. For all other uses, contact the owner/author(s). Music is considered to be culturally universal [2, 17] and present across all parts of the globe, reshaping the ways Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). human live, express themselves and convey emotions [9, 13]. Humans have been expressing themselves through music 759 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Jordan Aiko Deja, Nuwan Attygale, Klen Čopič Pucihar, and Matjaž Kljun for a very long time. It is believed that music originated consumption might look like. Lastly, we present questions from naturally occurring sounds and rhythms that humans and challenges that provoke discussions involving usability, echoed by merging them in patterns, making repetitions security, intellectual property and many other relevant key while changing tonality using their voice, hands clapping topics on music. [11], and smacking stones, sticks and other objects around them [12]. For example, one of such ambient sound is rain, 2 RE-IMAGINING MUSIC AND THE MUSIC that has a calming and a relaxing effect, even now since INTERFACE early humans felt safe during the rain while predators do not Humans create and consume music for four different pur- hunt [1]. Music has also helped humans in terms of survival, poses: (1) dancing as a social exercise, (2) providing a com- forging a sense of group identity and mutual trust [4]. mon form of personal or community entertainment, (3) com- The voice box, which allowed humans to sing, first emerged municating ideas and emotions and (4) having and celebrat- about a million years [13] ago and they learned how to use ing rituals and other activities [13]. While these purposes it around 530,000 years ago [14]. The voice box is considered come in handy for a variety of music activities, this position the first music instrument. Besides voice and hands, the ear- paper is focusing on music listening only. This is present in lier instruments were the objects found in the environment (1) where listening is a shared experience, as well as in (2) such as sticks and stones. Some authors argue that since the and (4) where listening can be a shared and also a personal oldest instruments found are so sophisticated (such as over experience. 40 thousand year-old bone flutes [4, 8, 19]) there must have When looking at how music listening has evolved in his- been less sophisticated instruments used by humans before tory, we can envision human tribes gathered around the fire [4, 14]. Nevertheless, the instruments the humans made and where one or several members performed a music piece. This used have rapidly evolved together with the complexity of type of music listening has been present for a long period of music compositions in the last couple of centuries. In this time and even nowadays people gather in live concerts to lis- period a variety of string, brass, percussion and woodwind ten to music. With recordings, music has moved to people’s instruments have evolved from earlier less sophisticated ones homes and the group has been reduced to family members [3]. and friends and listening become more personal. The head- As newer technologies are introduced, other ways of cre- phones enabled users to experience music individually and ating, producing, interacting with and even sharing music the Walkman enabled us to do it on-the-go. Smartphones and [18] are also taking place. MIDI interfaces, electric guitars internet have expanded the instant availability of music but and synthesizers are just some of the devices made of cir- the consumption remained mainly personal. The advances cuits that imitate traditional music instruments, and can be in virtually reality (VR) and augmented reality (AR) have connected to the computer. Novel algorithms, music infor- made personal music listening an immersive experience with mation retrieval (MIR) [5, 6] and artificial intelligence (AI) lights and visualisations augmenting music. Looking at how techniques allow us to work with and create new music con- listening to music has moved closer and closer to us with tent. With the advent of social platforms, sharing music on in-ear headphones that we even try to insert as close as pos- a grand scale has become a norm. sible to our body, it is not far-fetched if our vision is that Throughout this evolution one of the main components listening to music will move inside our heads. of music is expressing and generating emotions. Changes in Music is not just about sounds as it is also about rhythmic vocal parameters occurring during speech as well as singing vibrations; for example, it has been noted that the part of the have been shown to effect our state of emotions [10]. It brain responsible for hearing, works perfectly in deaf people has been also confirmed that sadness, happiness and other as well [16]. In order to feel music, we do not need to hear emotions can be communicated to listeners by music com- it but rather receive the vibrations to the hearing region of posers. As such, music is considered as a popular and easily- the brain. Because of this, we envision a future where we do applicable means for triggering emotions [10] and is globally not need external devices (such as headphones or speakers) consumed by everyone. We listen to music in order to make to be able to hear music, enjoy concerts, etc. Rather we will us happy, sad, to reminisce or reflect on our emotions. be listening to music within our brain in a seamless way. This paper attempts to share the authors’ visions on how Currently, researchers are already experimenting with micro- humans will consume and interact with music in the fu- controllers plugged into the brain and we envision having ture. We present our position based on the trends in how similar devices plugged into the hearing part of our brain. music instruments and music consumption have evolved Sound signals will be delivered straight into our auditory throughout the history. These visions have also emerged cortex. People will no longer have to depend on their ears from shared ideas in our small crowd-sourcing study we con- to listen and hear things. As such, people could enjoy music ducted online. We present two scenarios of how future music even while spacewalking, diving, skiing or surfing. 760 Sound 2121: The Future of Music Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia believe that through this interface, humans will be able to lis- ten and consume music, various melodies and sounds while being able to perform their daily tasks at the same time. As humans are connected to the global highway of infor- mation, unobtrusive sensors no longer need to detect and distinguish the current affect that they feel. Because of their neurological connection to the world, their emotions are eas- ily read and “felt” by the objects around them. Similar to how empathetic spaces that are context and emotion aware, ob- jects nearby will be act as local producers of music to either amplify or address the emotions that humans are feeling. 3 DESIGN SCENARIOS To better explain how we re-imagined this music interface, we describe two design scenarios with our vision in different contexts. Figure 2: Concept: Humans do not need tablets, mobile de- vices, or digital walls. Ideas and concepts are conceived in and are played into our brains from the surrounding objects. At the same time, we envision a future where biological and artificial objects around us will be connected to the cloud [15] where they will have access to a superb computing power. These objects will be equipped with for example nano-chips that will allow them to be part of the global link of information and capable of moving it depending on the needs. This is partly also a vision of IoT [20], which we are expanding to music listening. These technologies will allow Figure 3: Concept: Listening to music while surfing in the humans and objects to telepathically communicate. wide ocean will no longer require waterproof music gear. In the future humans will be able to amplify their emotions Rather, natural elements that are interlinked together cre- by the music naturally produced by the objects surrounding ate vibrations that humans can hear. Humans can finally them (see Fig 2. Traditionally, there are two ways on how achieve a non-obtrusive way of listening music while enjoy- music becomes a gateway for our emotions. If we feel sad, ing their wet hobbies. we wish to hear music so we can reflect, dive deeper and understand the sadness that we feel [emotions going in]. This Surfing. It is a lovely sunny and windy day. Cuauthli de- experience gives us lessons on how to manage our emotions, cides that these are perfect conditions to go surfing (as seen and how to grow stronger. At times, we may feel sad so we in Fig 3). While doing it he likes to feel the adrenaline rush wish to hear music in order to improve our mood [emotions with the sound of rock music. In 2020 Cuauthli would have to going out] and spend the better part of our days. In our wear water-proof in-ear headphones tightly plugged into his envisioned interface, humans can create gateways for their ears to prevent them from falling off. This would prevent him emotions with music. to hear the surroundings. However, when surfing he also has Algorithms will design and produce rhythms in on-the-fly to hear the surroundings for his safety. In order to do this, and have them played via vibration by these nearby objects he would have to balance spatial awareness and enjoy at the (moving on their own). Humans will simply need to think of same time, which takes a lot of effort [7]. In 2121 he will not their emotions and sounds, and the objects near them will have this problem anymore since, not only can he hear his seamlessly produce the vibrations recreating these sounds. preferred rock music, but the music blends with the sound of Objects around us, will produce a unique rhythm, providing the environment around him. In addition, if Cuauthli wants a new definition of audio augmented reality. Humans will to listen to the environment, the algorithm understands this get to enjoy their favorite sounds and rhythms through this and can mute the music just through his thoughts. This can seamless interface and played directly in their minds. We be done using two approaches. First, Cuauthli can listen to 761 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Jordan Aiko Deja, Nuwan Attygale, Klen Čopič Pucihar, and Matjaž Kljun his favorite track in full volume and when he wants to listen [3] Nicholas J Conard. 2009. A female figurine from the basal Aurignacian to the background noise, a chip inside his head can under- of Hohle Fels Cave in southwestern Germany. Nature 459, 7244 (2009), stand this and allows the environment sound to be heard. 248–252. Second, the noise of the environment around him can be [4] Nicholas J Conard, Maria Malina, and Susanne C Münzel. 2009. New flutes document the earliest musical tradition in southwestern Ger- used as an input and then be used to create a new sound that many. Nature 460, 7256 (2009), 737–740. blends with his taste and with the noise around him. These [5] J Stephen Downie. 2003. Music information retrieval. Annual review can be based on Cuauthli’s favorite tunes and algorithms of information science and technology 37, 1 (2003), 295–340. produce a specific tune that fits his current preferences and [6] J Stephen Downie. 2008. The music information retrieval evaluation allows him to not lose the connection with the environment exchange (2005–2007): A window into music information retrieval research. Acoustical Science and Technology 29, 4 (2008), 247–255. around him. [7] Dominik Fuchs. 2018. Dancing with Gravity—Why the Sense of Balance Amplifying emotions at the blink of an eye. It is a rainy Is (the) Fundamental. Behavioral Sciences 8, 1 (2018), 7. day and Cuauthli is sitting by the window, thinking about [8] Thomas Higham, Laura Basell, Roger Jacobi, Rachel Wood, Christo- his loved one. Since he is in Germany on a research visit, pher Bronk Ramsey, and Nicholas J Conard. 2012. Testing models for he misses her dearly. Cuauthli would love to get lost in his the beginnings of the Aurignacian and the advent of figurative art and music: The radiocarbon chronology of Geißenklösterle. Journal thinking about her. He then decides to listen to a song, which of human evolution 62, 6 (2012), 664–676. helps him reflect on his feelings for her and on his current [9] Patrik N Juslin and John A Sloboda. 2001. Music and emotion: Theory mood. The music helps him bringing back the the memories. and research. Oxford University Press. This is done by reducing other background noise as inputs [10] Mattes B Kappert, Alexandra Wuttke-Linnemann, Wolff Schlotz, and and allows him to focus on the memories that are in his brain. Urs M Nater. 2019. The Aim Justifies the Means—Differences Among Musical and Nonmusical Means of Relaxation or Activation Induction After a while, the rain stops falling and Cuauthli needs to go in Daily Life. Frontiers in Human Neuroscience 13 (2019), 36. back to work, but is feeling somewhat depressed. He thinks [11] Jamie C Kassler. 1987. The dancing chimpanzee: A study of the origin of a happy and exciting song, which starts playing and helps of music in relation to the vocalising and rhythmic action of apes. him to focus on his work as well as changes his mood. The Musicology Australia 10, 1 (1987), 79–81. algorithms and his neurological link take care of processing [12] Jeremy Montagu. 2014. Horns and Trumpets of the World: An Illustrated Guide. Rowman & Littlefield. his thoughts and produce the sounds that he needs to hear. [13] Jeremy Montagu. 2017. How music and instruments began: a brief overview of the origin and entire development of music, from its 4 CONCLUSION earliest stages. Frontiers in Sociology 2 (2017), 8. The visions and scenarios we presented come with their [14] Iain Morley. 2013. The prehistory of music: human evolution, archaeol- respective issues and challenges in implementation and in ogy, and the origins of musicality. Oxford University Press. [15] Elon Musk et al. 2019. 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International Journal of Music Education 1 (1997), 32–39. 762 Ohranjanje kulturne dediščine s pomočjo navidezne in obogatene resničnosti Cultural heritage preservation through virtual and augmented reality Marko Plankelj Niko Lukač Selma Rizvić Univerza v Mariboru, Univerza v Mariboru, Univerza v Sarajevu, Fakulteta za elektrotehniko, Fakulteta za elektrotehniko, Fakulteta za elektrotehniko računalništvo in informatiko računalništvo in informatiko Sarajevo, Zmaja od Bosne, bb., Maribor, Slovenija Maribor, Slovenija Bosna in Hercegovina marko.plankelj@student.um.si niko.lukac@um.si selma.rizvic@etf.unsa.ba Simon Kolmanič Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko Maribor, Slovenija simon.kolmanic@um.si of Microsoft HoloLens glasses and Unity game engine. For that purpose, we created an application that enables the interaction Permission to make digital or hard copies of part or all of this work for personal between user and six artefacts from Roman era, found in four or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and different sites through the Balkan. In this article the advantages the full citation on the first page. Copyrights for third-party components of this and disadvantages of such a presentation are presented and the work must be honored. For all other uses, contact the owner/author(s). CHI 2020 Extended Abstracts, April 25–30, 2020, Honolulu, HI, USA. possibility of its use for cultural heritage preservation. © 2020 Copyright is held by the owner/author(s). ACM ISBN 978-1-4503-6819-3/20/04. DOI: https://doi.org/10.1145/3334480.23 Keywords Cultural heritage, mixed reality, virtual reality, augmented Povzetek reality, Microsoft HoloLens Kulturna dediščina izginja zaradi različnih dejavnikov in pri njenem ohranjanju si v zadnjih letih vse pogosteje pomagamo s sodobnimi tehnologijami, ki omogočajo njeno digitalizacijo. Kot 1 Uvod primer dobre prakse predstavimo uporabo navidezne in obogatene resničnosti. Vedno pogosteje se uporablja tudi mešana resničnost, Kulturna dediščina je podedovana zapuščina, ohranjena v ki združuje virtualne objekte in resnično okolje. V članku predstavljamo možnost virtualne razstave muzejskih sedanjosti. V osnovi jo delimo na materialno in nematerialno. Z eksponatov s pomočjo očal Microsoft HoloLens in igralnega ohranjanjem kulturne dediščine se ukvarja UNESCO, agencija pogona Unity. V ta namen smo v okviru diplomske naloge znotraj organizacije Združenih narodov, ki je na seznam kulturne ustvarili aplikacijo, ki omogoča dediščine uvrstila 1121 območij [ interakcijo s šestimi artefakti iz 1]. Od tega jih je kar 53 časov Rimljanov, najdenih ogroženih zaradi naravnih katastrof, vremenskih sprememb, vojn na štirih različnih nahajališčih na Balkanu. V članku predstavljamo prednosti in slabosti, ki jih taka in človeške malomarnosti. Zaradi razvoja in priljubljenosti sodobnih tehnologij, so njihovo vrednost prepoznali tudi pri predstavitev nudi uporabniku in kako lahko le-to uporabimo za ohranjanje kulturne dediščine ohranjanju kulturne dediščine. Več milijonov turistov, ki . vsakoletno obiskujejo znamenitosti po svetu, bi lahko namesto Ključne besede dolgih potovanj in visokih stroškov iz udobja domačega fotelja doživeli cenejšo, ampak še vedno zadovoljivo izkušnjo, hkrati pa Kulturna dediščina, mešana resničnost, obogatena resničnost, s tem tudi te znamenitosti razbremenili in tako pripomogli pri navidezna resničnost, Microsoft HoloLens ohranjanju kulturne dediščine tudi za prihodnje generacije. Abstract Problem izginjanja kulturne dediščine in priložnost njenega Cultural heritage is disappearing due to various factors. In recent ohranjanja za prihodnje generacije s pomočjo sodobnih years, we have increasingly used modern technologies together tehnologij smo želeli preveriti tudi v praksi. Izdelali smo with its digitalization in order to preserve it. As an example of aplikacijo za prikazovanje artefaktov iz časov Rimljanov, ki good practice, we present the use of virtual and augmented deluje na »pametnih« očalih za prikazovanje mešane resničnosti, reality. Increasingly, mixed reality is also used combining virtual Microsoft HoloLens in uporabniku omogoča osnovno interakcijo objects and a real environment. In this article, we present the z artefakti ter njihov nemoten ogled iz vseh smeri. possibility of virtual exhibition of museum artefacts with the help 763 Članek sestavlja pet razdelkov. V drugem razdelku predstavimo dediščine Kočevja in Črnomlja. Na podoben način deluje tudi obstoječe aplikacije obogatene in mešane resničnosti, ki se aplikacija AR Kranj6, s pomočjo katere lahko spoznamo mesto uporabljajo pri ohranjanju kulturne dediščine. Naslednji Kranj in njegovo zgodovino. Kulturno dediščino lahko s razdelek, to je tretji, nas seznani z načrtovanjem in izdelavo pomočjo obogatene resničnosti spoznamo tudi v nekdanjem aplikacije. V četrtem razdelku predstavimo delovanje aplikacije. samostanu Žička Kartuzija, ki je danes v ruševinah, kjer s Zadnji, peti razdelek je namenjen predstavitvi doseženih pomočjo pametnih očal in avdio vodnikov skozi rezultatov. tridimenzionalne modele vidimo, kako je samostan izgledal v vsej svoji veličini. 2 Pregled področja Kontinuum virtualnosti, katerega avtorja sta Paul Milgram in Fumio Kishino se osredotoča na definicijo Čeprav sodobne tehnologije v javnosti pogosto označujejo kot mešane resničnosti. Po njuni definiciji mešano resničnost sestavljata obogatena grožnjo, ki lahko privede v odvisnost, socialno izolacijo in resničnost, kjer virtualni zmanjša ustvarjalnost [ elementi obogatijo resnični svet, ter 2], so ravno te tehnološke inovacije pogosto ključne pri ohranjanju kulturne dediščine za prihodne obogatena virtualnost, kjer elementi resničnega sveta obogatijo virtualni svet. Tako lahko mešano resničnost predstavimo tudi generacije. V zadnjih letih med najbolj priljubljene tehnologije kot nadmnožico obogatene in navidezne resničnosti. za ohranjanje kulturne dediščine štejemo navidezno, obogateno in mešano resničnost. Aplikacije mešane resničnosti se za ohranjanje kulturne dediščine v času pisanja tega članka uporabljajo zgolj v manjšem S stališča računalništva štejemo pod pojem navidezna resničnost področje, katerega cilj je ustvariti virtualni svet, ki omogoča obsegu [5]. Možna razloga za to sta lahko visoka cena in relativno nova tehnologija. interakcijo z uporabnikom, medtem ko uporablja posebne naprave za simulacijo okolja, ki skrbijo za čim bolj realno izkušnjo. Obogatena resničnost se z HoloTour7 je produkt podjetja Microsoft, ki nam omogoča ogled a razliko od navidezne osredotoča na dopolnitev resničnega sveta s pomočjo dodajanja zgodovine Rima in skrivnosti Machu Picchua na napravi za prikazovanje mešane resničnost plasti virtualnih objektov ali dodatnih informacij v resnično i, Microsoft HoloLens. Z aplikacijo upravljamo s pomočjo gest in glasovnih ukazov. okolje. Mešano resničnost vse pogosteje vključujejo tudi v muzeje, kjer Priljubljenost obogatene resničnosti z leti eksponentno narašča, lahko izpostavimo aplikaciji HoloMuse8 in Holomuseum9 (obe sta namenjeni za uporabo na napravi Microsoft HoloLens), ki vendar so v raziskavi ohranjanja kulturne dediščine na uporabniku omogočata spoznavanje arheoloških zbirk evropskem območju [3] ugotovili, da trenutno obstaja zelo malo artefaktov, s katerimi lahko poljubno manipuliramo, česar v aplikacij, ki jih večinoma razvijajo muzeji oziroma ustanove za pravem muzeju ne moremo doseči. ohranjanje kulturne dediščine [ 4]. Aplikacije se večinoma aktivirajo na podlagi sprožilca (npr. simbol, označb a, predmet, lokacija naprave), v manjši meri pa tudi na podlagi pogleda. 3 Načrtovanje in izdelava aplikacije Mobilna aplikacija England Originals 1 ter funkcija Pocket Gallery 2 znotraj aplikacije Google Arts&Culture 3 delujeta na Pri snovanju aplikacije, nastajala je v času diplomskega dela, podoben način – ob zaznavi ravne površine prikažeta smo se zgledovali po obstoječih aplikacijah za prikazovanje tridimenzionalni model v resničnem okolju. Manipulacija z mešane resničnosti. Pri tem pa smo se srečali s težavo, da gre pri modelom je mogoča s premikanjem telefona ter upravljanjem očalih HoloLens za dokaj novo napravo, ki je cenovno težje preko zaslona. Tudi mobilna aplikacija Civilisations AR4 deluje dostopna. Ob tem je potrebno poudariti, da se knjižnice z novimi na enak način, vendar v tem primeru virtualni model našega funkcionalnostmi še vedno razvijajo, zato je ustrezne literature planeta lebdi v zraku, na njem pa so označena najdišča dokaj malo, oziroma v njej avtorji opisujejo starejše verzije artefaktov, ki si jih lahko s klikom na zaslon mobilne naprave knjižnic, ki se več ne uporabljajo. Zato smo si zamislili tudi bolj natančno ogledamo ter nad njimi izvajamo osnovne enostavno, ampak še vedno vabljivo aplikacijo, skozi katero so geometrijske transformacije. predstavljene različne možnosti uporabe mešane resničnosti s pomočjo očal HoloLens. Aplikacije za ohranjanje kulturne dediščine s pomočjo obogatene resničnosti zelo uspešno vključujejo v turistično ponudbo tudi v Predstavljena aplikacija spada pod obogateno resničnost, ki pa bi Sloveniji, kjer lahko izpostavimo tri aplikacije. Travel AR lahko postala aplikacija mešane resničnosti v primeru, da bi se Slovenia 5 sproži obogatitev okolice na prenosni napravi ob pojavila potreba po tem, tako da bi uporabljenim objektom dodali zaznavi markerja obogatene resničnosti in nam ob avdio vodenju zavedanje okolice. Aplikacija namreč deluje na napravi za omogoča ogled tridimenzionalnih rekonstrukcij kulturne 1 http://www.heritagecities.com/stories/explore [09. 09. 2020]. 8 https://www.researchgate.net/publication/315472858_HoloMuse_Enhancing_En 2 https://artsandculture.google.com/story/5QWhvYU1kBJfgw [09. 09. 2020]. gagement_with_Archaeological_Artifacts_through_Gesture- 3 https://about.artsandculture.google.com/ [09. 09. 2020]. Based_Interaction_with_Holograms [09. 09. 2020]. 4 https://www.bbc.com/news/technology-42966371 [09. 09. 2020]. 9 https://www.researchgate.net/publication/326713622_HOLOMUSEUM_A_HOL 5 http://www.travel-ar.si/sl/ [09. 09. 2020]. OLENS_APPLICATION_FOR_CREATING_EXTENSIBLE_AND_CUSTOMI 6 https://www.visitkranj.com/sl/obogatena-resnicnost-v-kranju [09. 09. 2020]. ZABLE_HOLOGRAPHIC_EXHIBITIONS [09. 09. 2020]. 7 https://docs.microsoft.com/en-us/windows/mixed-reality/case-study-capturing- and-creating-content-for-holotour [09. 09. 2020]. 764 prikazovanje mešane resničnosti, Microsoft HoloLens, ki to v osnovi omogoča. Tabela 1: Število mnogokotnikov pred in po decimaciji Število Število Objekt mnogokotnikov mnogokotnikov po pred decimacijo decimaciji Artefakt 1 3.268.685 490.301 Artefakt 2 448.881 44.877 Artefakt 3 422.978 42.282 Artefakt 4 124.764 43.666 Artefakt 5 146.228 29.244 Artefakt 6 97.762 9.437 Za večjo atraktivnost aplikacije, smo dodatno zmodelirali še steber v slogu rimske arhitekture, na katere smo v predstavitvi nato postavili artefakte. Vse objekte smo nato izvozili v grafični pogon Unity. V igralnem pogonu Unity smo ustvarili nov projekt ter namestili Slika 1: Shematski prikaz delovanja aplikacije in konfigurirali orodje, ki omogoča razvoj aplikacij mešane in obogatene resničnosti, imenovano »Mixed Reality Toolkit«, oziroma krajše MRTK. Aplikacijo smo razdelili na posamezne dele imenovane scene, ki smo jih uporabili kot samostojne enote. V vsako izmed scen smo dodali izbrane objekte ter jim dodali interaktivne komponente, ki so nam omogočile interakcijo z artefakti. Interakcija s HoloLens je možna na tri osnovne načine: s pogledom, kretnjo ali glasovnim upravljanjem. Vse tri načine smo implementirali v našo aplikacijo. 4 Predstavitev rezultatov Aplikacijo za ohranjanje kulturne dediščine s pomočjo navidezne in obogatene resničnosti smo razvili skozi različne stopnje, ki skupaj sestavljajo celoto; delujočo aplikacijo na napravi za Slika 2: Osnovna načina interakcije z HoloLens, ki smo jih prikaz mešane resničnosti Microsoft HoloLens, skozi katero uporabili v aplikaciji (geste in glasovno upravljanje) lahko spoznamo artefakte iz časov Rimljanov. Aplikacijo smo razdelili na različne scene, kot prikazuje slika 1, Ob njenem zagonu se nam prikaže glavna scena, ki prikazuje šest med katerimi se lahko premikamo z uporabo osnovnih načinov stebrov, kot prikazuje slika 3. Na vsakega izmed stebrov je interakcije s HoloLens, kot prikazuje slika 2. postavljen po en artefakt iz rimske dobe. Za izboljšano uporabniško izkušnjo izleta v preteklost, se v ozadju predvaja glasba s časa Rimskega imperija, kot si jo danes predstavljajo 3.1 Izdelava aplikacije muzikologi. Prvi korak pri izdelavi aplikacije za razstavo muzejskih eksponatov s pomočjo mešane resničnosti, je priprava objektov. Osredje mesto na razstavi so zasedali eksponati s štirih nekdanjih rimskih naselbin: Viminacium in Municipium v Srbiji, Aquae v Bosni in Hercegovini ter Dyrrachium v Albaniji, ki smo jih dobili v elektronski obliki, vendar jih je bilo potrebno pred uporabo v naši aplikaciji obdelati. V ta namen smo uporabili animacijski paket Blender, v katerem smo zmanjšali število točk in Slika 3: Glavna scena s šestimi artefakti, ki so postavljeni na mnogokotnikov, kot prikazuje tabela 1. Število točk je bilo različno visoke stebre potrebno zmanjšati zaradi procesorske moči in velikosti pomnilnika na napravi HoloLens. Artefaktov pa si ni možno ogledovati zgolj od daleč, ampak si jih lahko ogledamo tudi natančneje. Za dostop do scene 765 posameznega artefakta usmerimo pogled v artefakt ter z gesto, ki časov Rimljanov s pomočjo naprave za prikazovanje mešane ponazarja klik, preidemo na novo sceno, kot prikazuje slika 4. resničnosti Microsoft HoloLens. Čeprav smo uspešno razvili aplikacijo, kot smo si jo zamislili, smo mnenja, da imata tako aplikacija kot tehnologija mešane ter obogatene resničnosti veliko možnost nadgradnje v prihodnosti. Največjo omejitev pri razvoju trenutno predstavlja naprava HoloLens in njene tehnične zmogljivosti, kot je npr. slabša ločljivost in majhno vidno polje na vizirju. Druga generacija Microsoftove naprave bi naj izboljšala vse slabosti naprave prejšnje generacije in omogočila bolj naravno interakcijo s hologrami. Slika 4: Prikaz posamezne scene enega izmed artefaktov Če smo v preteklosti razmišljali, kako prilagoditi objekte, da bodo lahko sprejeli več obiskovalcev, bomo v prihodnosti morali Na tej sceni lahko nad artefaktom izvajamo osnovne več pozornosti nameniti uporabi sodobnih tehnologij na različnih geometrijske transformacije (spreminjanje velikosti, rotiranje in področjih, tudi ohranjanju kulturne dediščine. Obogatena in premikanje) s pomočjo prijemanja ročajev ob straneh artefakta. mešana resničnost sta vsekakor tehnologiji, ki ju lahko Na takšen način lahko artefakt pogledamo iz vseh smeri, česar v uporabimo na kateremkoli področju. Potrebujemo zgolj realnem muzeju ne moremo doseči. Ob straneh artefakta se tridimenzionalne modele in zgodbo, ki bo pritegnila uporabnike, prikažeta dve ploščici, na katerih sta zapisani zanimivosti o zgodbo, ki je sestavni del naše preteklosti, preteklosti, ki jo življenju Rimljanov. Po želji jih lahko z usmeritvijo pogleda in želimo ohraniti za prihodnje generacije. gesto, ki ponazarja klik, zapremo in vso pozornost usmerimo v artefakt. Zahvala Na sceni, ki prikazuje artefakte posamezno, se bo nad njimi Avtorji izjavljamo, da je raziskavo finančno podprla Javna pojavila nadzorna plošča, ki omogoča prekinitev predvajanja agencija za raziskovalno dejavnost Republike Slovenija v okviru glasbe, vrnitev v glavno sceno; po želji pa lahko kontrolno ploščo projekta BI-BA/19-20-003. tudi zapremo. Vse naštete ukaze izvedemo z usmeritvijo pogleda v izbrano akcijo (gumb) in gesto, ki ponazarja klik. Ob usmeritvi pogleda v želeni gumb se nam pod njim izpiše ključna beseda, s 6 Viri in literatura katero lahko izvedemo ukaz. Sceno, ki prikazuje posamezen artefakt, lahko upravljamo tudi s štirimi glasovnimi ukazi. Prvi ukaz s ključno besedo »Menu« se [1] Unesco. World Heritage List. Dostopno na: uporablja v primeru, da smo pred tem nadzorno ploščo zaprli. https://whc.unesco.org/en/list/ [26.2.2020]. Nadzorna plošča se bo ob zaznavi ukaza ponovno prikazala. [2] Al-Zoubi, S., Younes, M. A. B. The Impact of Drugi ukaz s ključno besedo »Sound« se uporablja v primeru, ko Technologies on Society: A Review . International Organization smo pred tem predvajanje glasbe ustavili. Ob zaznavi ukaza se of Scientific Research Journal of Humanities and Social Science, bo glasba predvajala naprej. Tretji ukaz s ključno besedo »Close« 20, (2015), 2(5), str. 82-86. se uporablja kot nadomestilo klika na gumb Close in nam ob [3] Luna, U., Rivero, P., Vicent, N. Augmented Reality in zaznavi ukaza zapre nadzorno ploščo. Zadnji, četrti ukaz, s Heritage Apps : Current Trends in Europe. Applied Sciences, 9, ključno besedo »Back«, se uporablja kot nadomestek klika na (2019), 13, 2756. gumb Back in nam ob zaznavi ukaza ponovno prikaže glavno [4] Hammady, R., Ma, M., Strathearn, C. User experience sceno. design for mixed reality: a case study of HoloLens in museum. International Journal of Technology Marketing, 13, (2019), 3/4, Aplikacijo smo želeli tudi testirati na testnih uporabnikih in str. 354-375. pridobiti njihov odziv, vendar to zaradi epidemiološke situacije [5] Kassahun-Bekele M., Pierdicca, R., Frontoni, E., glede COVID-19 ni bilo mogoče. Pričakujemo, da bi bili rezultati Malinverni, E. S., Gain, J. A Survey of Augmented, Virtual, and podobni rezultatom, predstavljenim v članku [6], saj avtorji tam Mixed Reality for Cultural Heritage. Association for Computing med drugim opisujejo uporabniške izkušnje s podobno aplikacijo Machinery Journal on Computing and Cultural Heritage, 11, kot je naša. (2018), 2, str. 1-36. [6] Kolmanič, S., Marksel, M., Mongus, D., Žalik, B. 5 Zaključek Tehnologije navidezne in obogatene resničnosti, kot orodje za predstavitev novih idej in produktov na sejmih : primer Mahepa. Uporabna informatika. [Tiskana izd.]. 2020, letn. 28, V tem projektu smo izpostavili problem izginjanja kulturne št. 2, str. 85-93. ISSN 1318-1882. dediščine, ki je posledica različnih dejavnikov (naravnih in človeških) ter želeli preveriti možnosti ohranjanja naše preteklosti s pomočjo sodobne tehnologije, mešane resničnosti. Razvili smo aplikacijo, ki nam omogoča ogled artefaktov iz 766 Predmetnik: oprijemljiv uporabniški vmesnik za informiranje turistov Gregor Sotlar Peter Roglej 89172027@student.upr.si peter.rogelj@upr.si Univerza na Primorskem, UP FAMNIT Univerza na Primorskem, UP FAMNIT Koper, Slovenija Koper, Slovenija Klen Čopič Pucihar Matjaž Kljun klen.copic@famnit.upr.si matjaz.kljun@famnit.upr.si Univerza na Primorskem, UP FAMNIT Univerza na Primorskem, UP FAMNIT Koper, Slovenija Koper, Slovenija Fakulteta za Informacijske Študije Fakulteta za Informacijske Študije Novo mesto, Slovenija Novo mesto, Slovenija Slika 1: Vmesnik Predmetnika. POVZETEK ponudbo. Ob dvigu predmeta uporabnik sproži prikaz vse- Namen dela je zasnovati in raziskati možne vloge oprijemlji- bine na zaslonu. Opravljena uporabniška študija je pokazala, vega uporabniškega vmesnika za informiranje turistov, ki da je lahko Predmetnik prva točka informiranja v turistično bi dopolnjeval obstoječe oblike informiranja v turistično in- informacijskih centrih, njegova prednost pa je v tem, da na formacijskih centrih, nadomestil njihove pomanjkljivosti, a enostaven in preprost način v kratkem času podaja informa- hkrati uporabil njihove prednosti. Vmesnik smo zasnovali cije o doživetju posamezne turistične ponudbe. na podlagi predhodnih raziskav in lastnih izkušenj ter ga poimenovali Predmetnik. Uporabniški vmesnik vsebuje posa- KEYWORDS mezne enote - predmete, ki predstavljajo določeno turistično oprijemljivi uporabniški vmesnik, turizem, informiranje tu- ristov, turistični informacijski center, TIC Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies 1 UVOD bear this notice and the full citation on the first page. Copyrights for third- Informiranje turistov v turistično informacijskih centrih party components of this work must be honored. For all other uses, contact the owner/author(s). (TIC) je omejeno na nekaj medijev ali virov, kot so turistični informator, tiskovine (letaki, prospekti, zemljevidi, brošure Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). in zgibanke), zasloni, ki predvajajo videoposnetke, in raču- nalniki (npr. zasloni na dotik). Težave tiskanih medijev so 767 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Gregor Sotlar, Peter Roglej, Klen Čopič Pucihar, and Matjaž Kljun enosmerna komunikacija, težko posodabljanje, različna gra- na po mestu postavljenih kiosk računalnikih, ki so žetone fična razporeditev, poleg tega težko omogočajo nadaljnje prepoznali, vodil do želenih ciljev. Tangible user Interface iskanje informacij (npr. preko URL naslovov, ki jih je po- within Projector-based Mixed Reality je s sledenjem figure, ki trebno prepisati v brskalnik). Tiskovine imajo tudi prednosti, jo je uporabnik premikal po zemljevidu, na zaslonu prika- saj ne potrebujejo dodatne energije in so zelo prenosljive. zoval pripadajoči 3D prizor [27]. Pri drugi izvedbi je fizično Težave zaslonov na dotik so zahtevano znanje za uporabo, figuro zamenjal uporabnik sam, ki je s premikanjem po na čas, ki ga porabimo pri iskanju informacij, potrebno napa- tleh projicirani maketi parka, upravljal prikaz lokacije. Opri- janje z energijo in nezmožnost odnesti informacije s seboj. jemljivi vmesniki so pogosto dostopni v muzejih. Na primer Podobno kot tiskani mediji tudi neinteraktivni zasloni (angl. v [25] je oprijemljiv vmesnik za pridobitev informacij o do- public displays) omogočajo povečini enosmerno komunika- ločenem geološkem vzorcu kar vzorec sam, ki ob rokovanju cijo s predvajanjem videoposnetkov turistične ponudbe. Ti poda zvočne in vizualne informacije o njem na projekciji. so zelo dobrodošli za prvi vtis o ponudbi, vendar teh infor- Vzorec je hkrati tudi bogat vir informacij o barvi, teži, trdoti macij obiskovalec ne more upravljati in lahko le čaka, da se in teksturi. vse informacije predvajajo. Dosedanje raziskave so se osredotočale na prikaz poti do Za raziskavo informiranja o turistični ponudbi smo zasno- želene turistične znamenitosti, prikaz pokrajine glede na vali in izdelali oprijemljiv uporabniški vmesnik, imenovan položaj in rokovanje s predmeti za prikaz podrobnejših (vi- Predmetnik. Sistem odpravlja težavno interakcijo z zasloni na deo) vsebin. Nobena nam znana raziskava se ni ukvarjala s dotik in nezmožnost interakcije z javnimi zasloni. Vmesnik je podajanjem predstave o turističnih doživetjih preko različ- sestavljen iz predmetov, s katerimi lahko uporabnik rokuje in nih predmetov kot so spominki, lokalni pridelki ali izdelki preko tega upravlja večpredstavnostne vsebine o določenem in predmeti, ki predstavljajo turistične aktivnosti (pohodi, turističnem cilju, aktivnosti ali ponudbi na povezanem za- kolesarjenje, ipd.) Osnovna ideja je tako omogočiti upravlja- slonu. Za predmete našega vmesnika lahko izberemo lokalne nje in izbiro aktivnosti ali ciljev potovanja iz predhodnega izdelke, pridelke, spominke in različne predmete, ki so pove- nabora fizičnih predmetov, ki predstavljajo asociacijo na do- zani z aktivnostmi. Predmeti, s katerimi uporabnik rokuje, ločeno turistično izkušnjo, s tem pa omogočiti pridobitev preko zaslona predstavljajo določeno zgodbo, ki obogati turi- možnega doživetja turistične ponudbe preko večpredstavno- stično izkušnjo. Predmeti s tem postanejo “vstopna točka” in stnih vsebin, ki so drugače dosegljive le na spletu in javnih preko podanih zgodb spodbudijo željo po iskanju nadaljnjih zaslonih. Naše raziskovalno vprašanje se tako glasi: Ali je informacij, ki so na voljo v TIC-u, kot na primer, kako priti fizični vmesnik Predmetnik primeren kot vstopna točka za do želene posamezne ponudbe ali cilja, zgodovino, ipd. Vse informiranje o turističnih doživetjih oziroma o ponudbi v dodatne informacije so torej dosegljive preko tiskovin, spleta turistično informacijskih centrih? in turističnih informatirjev, ki so že na voljo v TIC-u. 3 OPIS SISTEMA 2 PREGLED PODROČJA Predmetnik je sestavljen iz treh delov (Slika 2): uporabni- Skupnost je že pred tremi desetletji izpostavila, da računal- škega vmesnika, mikroračunalnika (Raspberry Pi 3B) kot niki preprečujejo stik z okoljem [26], kar je spodbudilo ideje računske enote in naprave za predvajanje zvočnih in video za uporavljanje digitalnih vsebin s pomočjo fizičnih predme- vsebin (zaslon ali projektor). Komunikacija poteka v smeri tov [7]. Nekateri raziskovalci so šli še dlje in predstavili vizijo od oprijemljivega vmesnika preko senzorjev do mikrora- uporabe fizičnega sveta kot vmesnika za povezovanje objek- čunalnika, ki prejme informacijo o dvignjenem predmetu, tov in površin z digitalnimi vsebinami [12]. Na osnovi teh predvaja temu primerno vsebino in preko svetlobnih signa- del so oprijemljivi uporabniški vmesniki postali nova oblika lov podaja informacije o aktivnih in neaktivnih predmetih interakcije [18], ki se uporablja na vse več področijih in za ra- vmesnika (če so vsi predmeti odloženi, pri vseh gori lučka; znovrstne naloge [21], kot so: (i) shranjevanje, pridobivanje če je pa posamezen predmet dvignjen, gori lučka le pri tem). in rokovanje s podatki [1, 5, 19, 22], (ii) vizualizacija informa- Polica predmetnika ima za posamezen predmet izrezan relief cij preko oprijemljivih uporabniških vmesnikov [10, 23, 24], v obliki predmeta, kar omogoča (poleg svetlobnega signala) (iii) modeliranje in simulacije [2–4, 8, 11], (iv) upravljanje lažje odlaganje. Če noben predmet ni aktiven (se z njim ne sistemov, kontrola in konfiguracija [3, 5, 14, 15, 22] in (v) rokuje), se na zaslonu predvaja kratek video posnetek, ki izobraževanje, zabava in programski sistemi [3, 9, 13, 16, 17]. prikazuje rokovanje s Predmetnikom in vabi uporabnika, da Tudi na področju turizma so že bile narejene raziskave, ki dvigne enega od njih. Podrobnejši opis uporabljene strojne so za informiranje turistov uporabile koncepte oprijemljivih in programke opreme je na voljo v [20]. uporabniških vmesnikov. Sistem Mementos [6] je uporabnike Sistem zbira naslednje podatke: število rokovanj z določe- preko žetonov (spominkov), ki so predtsavljali turistične zna- nim predmetom, čas rokovanja s posameznim predmetom menitosti ali infrastrukturo (restavracije, javni prevoz, ipd.), in čas predvajanja posameznega posnetka s čimer beležimo, 768 Predmetnik: oprijemljiv uporabniški vmesnik za informiranje turistov Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia sodelovalo devet udeležencev v razponu od devet do 66 let, od tega je bilo sedem žensk in dva moška. Po privolitvi smo jim predstavili potek raziskave: (i) iz- polnjevanje pred-vprašalnika, (ii) opravljanje dveh nalog (iskanje informacij o kolesarjenju in pregled ostalih možnih doživetij) brez časovnih omejitev, kjer so imeli na voljo ti- skovine, zaslon na dotik in Predmetnik ter (iii) izpolnjevanje Slika 2: Prikaz sheme sistema: a) uporabnik, b) uporabniški drugega dela vprašalnika. Vrstni red opravljanja nalog ni bil vmesnik s predmeti, c) računska enota in d) zaslon, ki pred- naključen, saj smo najprej želeli videti rokovanje za točno vaja večpredstavnostne vsebine. določen namen (najti informacije o kolesarjenju) in nato opazovati splošno rokovanje (pregled možnih doživetij). koliko je bila posamezna ponudba zanimiva in koliko je bil Med raziskovanjem smo opazovali interakcijo z vsako določen predmet vmesnika informativen ali zanimiv za inte- od oblik informiranja (obračanje, tipanje ...) Opazovali smo rakcijo. tudi vrstni red interakcije med raznimi oblikami oziroma predmeti informiranja, porabljen čas na posameznem viru 4 RAZISKAVA interakcije, čas gledanja pri video predstavitvah in skupen V raziskavi smo izvedli nadzorovano uporabniško študijo čas iskanja informacij. (angl. controlled user study). Opazovalne študije (angl. ob- 5 REZULTATI IN RAZPRAVA servational study) nismo mogli izvesti zaradi epidemije. Na TIC-u v Izoli so vse predmete odmaknili, saj jih turisti za- V povprečju so udeleženci prvo nalogo reševali osem minut radi možnosti okužbe ne smejo prijemati; lahko jih dobijo le, in 16 sekund, drugo pa pet minut in 31 sekund, čeprav je če vprašajo zaposlenega informatorja. Zaradi tega tudi niso slednja od njih zahtevala pregled več informacij. Tiskovinam dovolili postaviti Predmetnik v njihove prostore. so pri drugi nalogi v povprečju namenili dobro minuto in pol manj časa v primerjavi s prvo nalogo, posamezna tiskovina pa se je v povprečju gledala enako dolgo, čeprav niso vsi iz prve naloge po tiskovinah posegli tudi v drugi. Pri tablici se je število uporabnikov pri drugi nalogi v primerjavi s prvo zmanjšalo, predvsem zaradi začetne slabe izkušnje z njenim rokovanjem. Ravno tako se je zmanjšal čas povprečne porabe za skoraj dve minuti. Le pri Predmetniku se je čas uporabe podaljšal iz 32 sekund na 53 sekund. To je bilo za pričakovati, saj so imeli možnost pogledati še tri preostale posnetke. Čas se je podaljašal tudi za ogled posameznega videoposnetka v povprečju za tri sekunde, vendar k temu prispeva tudi dejstvo, da so drugi trije videi za nekaj sekund daljši od videa, predvidenega za prvo nalogo. Povečalo se je zanimanje za Slika 3: Simulacija TIC-a: zaslon na dotik, Predmetnik in ti- Predmetnik, saj ga je po tem, ko so ga v prvi nalogi šele skovine. spoznali, v drugi nalogi kot prvo obliko informiranja izbralo več uporabnikov. Vrstni red nalog je deloma tudi vplival na Študijo smo izvedli v simuliranem TIC-u (Slika 3). Na vo- čas opravljanja: slabe izkušnje iz prve naloge so vplivale ljo so bile tri oblike informacij, ki so predstavljale turistično na neuporabo tablice, domačnost s Predmetnikom pa na ponudbo slovenske Istre: tiskovine, zaslon na dotik (tablica opustitev uvodnega videa. s spletno stranjo I Feel Slovenia: Mediterranean & Karst Slo- Poleg tega se je v drugi nalogi v primerjavi s prvo povečalo venia1) in Predmetnik (s štirimi predmeti – pedal, vponka, število uporabnikov, ki so si začeli ogledovati predmete ali sol in kamen s pohodniško markacijo), ki je prikazoval video se z njimi igrati, vendar je bilo število manjše od pričakova- vsebine s spletnih strani turističnih zavodov Kopra, Izole in nega. Previdevamo, da imajo tiskovine in tablica prednost, Pirana. Video vsebine so bile dolge med 12 in 19 sekund. ker so jih udeleženci že poznali ali vsaj vedeli, kakšna je nji- Udeležence smo pridobili s priročnim vzorčenjem (angl. hova funkcionalnost. Prišlo je tudi do določenih sprememb convenience sampling). V danem trenutku in položaju je bila pri izvajanju obeh nalog, kot je povečanje prehajanja med to edina možnost pridobitve uporabnikov. Pri testiranju je oblikami informiranja oziroma vračanja k že obiskani obliki 1https://www.slovenia.info/en/places-to-go/regions/mediterranean-karst- znotraj iste naloge. Še posebno pri prvi nalogi smo opazili, da slovenia so udeleženci najprej uporabili tisto obliko informiranja, ki 769 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Gregor Sotlar, Peter Roglej, Klen Čopič Pucihar, and Matjaž Kljun jim je bila fizično najbližje. Tako so pri prvi nalogi večinoma [5] Jonathan Cohen, Meg Withgott, and Philippe Piernot. 1999. Logjam: a začeli z uporabo tiskovin, ki so bile prva oblika informiranja tangible multi-person interface for video logging. , 128–135 pages. glede na smer prihoda v prostor. Pri drugi nalogi pa je to že [6] Augusto Esteves and Ian Oakley. 2010. 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Tangible interaction+ graphical 283-284 pages. interpretation: a new approach to 3D modeling. , 393–402 pages. 770 Razvoj in Ocenjevanje Prototipa Mobilne Aplikacije z Elementi Igrifikacije in Mešane Resničnosti Development and Assessment of the Mobile Application Prototype with Elements of Gamification and Mixed Reality Monika Zorko† Matjaž Debevc Ines Kožuh Fakulteta za elektrotehniko, Fakulteta za elektrotehniko, Fakulteta za elektrotehniko, računalništvo in informatiko računalništvo in informatiko računalništvo in informatiko Univerza v Mariboru Univerza v Mariboru Univerza v Mariboru Slovenija Slovenija Slovenija monika.zorko1@student.um.si matjaz.debevc@um.si ines.kozuh@um.si ABSTRACT / POVZETEK prototype and the usability of the user interface. We used the SUS and UEQ method. 80 people were included in the survey by Učinkovito oglaševanje je eden od ključnih ciljev snovalcev random sampling. Statistical analysis revealed three key findings. oglasov in njihovih naročnikov. Prav zato si prizadevajo, da An ad that contains mixed reality and gamification stands out njihovi oglasi izstopajo od konkurence, pogosto pa je pri tem slightly from the rest of the advertising method. This type of ad spregledan vidik uporabnika. V raziskovalni študiji smo tako can also increase the level of intent to purchase the advertised izdelali prototip aplikacije, ki vključuje elemente igrifikacije in product. Lastly, the analysis revealed that there is no association mešane resničnosti. Zaradi omejitev osebnih stikov v času between users' age and the understanding of the application. Our pandemije COVID-19 smo izdelali video posnetke, ki so results can serve both advertisers and researchers in the use of modern technologies and advertising. prikazovali uporabo prototipa. Nato smo ocenjevali uporabniško izkušnjo prototipa in uporabnost uporabniškega vmesnika. OPTIONAL: KEYWORDS Uporabili smo SUS in UEQ metodo. S priložnostnim vzorčenjem smo v raziskavo vključili 80 oseb. Statistična analiza je razkrila User experience, usability, advertising, gamification, mixed tri ključne ugotovitve. Oglas, ki vsebuje mešano resničnost in reality igrifikacijo, nekoliko izstopa od ostalega načina oglaševanja. Prav tako lahko taka vrsta oglasa poveča stopnjo namena nakupa 1 UVOD oglaševanega izdelka. Kot zadnje se je pokazalo, da ni povezave med starostjo uporabnika in razumevanjem aplikacije. Naši Vsakodnevno smo izpostavljeni številnim oglasom, kar vodi rezultati lahko služijo tako oglaševalcem, kot tudi raziskovalcem oglaševalce v vse večja vlaganja v zagotavljanje učinkovitosti na področju uporabe sodobnih tehnologij in oglaševanja. oglaševanja in razlikovanja od konkurence. Sodobna tehnologija daje oglaševalcem številne možnosti za inovativne pristope v komuniciranju s ciljnimi javnostmi. Primera takih pristopov sta vpeljava igrifikacije in mešane resničnosti v oglaševanje. Oboje KEYWORDS / KLJUČNE BESEDE se je izkazalo kot pozitiven dejavnik v priklicu blagovne znamke uporabniška izkušnja, uporabnost, oglaševanje, igrifikacija, s strani potrošnika [1]. mešana resničnost Namen pričujoče študije je tako raziskati neizkoriščen potencial, ki ga prinaša oglaševanje s pomočjo kombinacije OPTIONAL: ABSTRACT igrifikacije in mešane resničnosti. Natančneje, zanima nas zaznana stopnja vidljivosti oglasa, ki vpeljuje igrifikacijo in Effective advertising is one of the key goals of ad creators and their target groups. This is why they strive to make their ads stand mešano resničnost v zgodbo komuniciranja s potrošnikom. Prav out from the competition, while the user aspect is regularly tako raziskujemo vplive na odločitve za nakup s tovrstnimi oglasi overlooked. In the current study, we thus produced a prototype oglaševanih izdelkov. Ker se v procesu oblikovanja tovrstnih application that includes elements of gamification and mixed oglasov pojavljajo tudi izzivi v smislu zagotavljanja ustrezne reality. Due to the limitations of personal contact during the uporabniške izkušnje in uporabnosti uporabniškega vmesnika, je COVID-19 pandemic, we produced videos showing the use of predmet te študije raziskati tudi to. the prototype. We then evaluated the user experience of the ∗Article Title Footnote needs to be captured as Title Note †Author Footnote to be captured as Author Note 2 IGRIFIKACIJA, RAZŠIRJENA Permission to make digital or hard copies of part or all of this work for personal or RESNIČNOST IN OGLAŠEVANJE classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full Pri igrifikaciji gre za uporabo izkušnje zabave, ki »z notranjo citation on the first page. Copyrights for third-party components of this work must motivacijo in sistemom nagrajevanja uporabnike privlači in jih be honored. For all other uses, contact the owner/author(s). vključi v različne aktivnosti« [2]. Tipični elementi igrifikacije so Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). 771 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia M. Zorko et al. točke, značke, lestvice, grafi uspešnosti, zgodbe s pomenom, 4.2 Razvoj prototipa aplikacije in avatarji in soigralci [4]. predstavitvenih video posnetkov Mešana resničnost je del razširjene resničnosti, kamor jo uvrščamo skupaj z navidezno resničnostjo in obogateno Prototip smo izdelali s pomočjo programa Adobe XD. Na resničnostjo. Mešano resničnost lahko opišemo kot tehnologijo osnovi izdelanega prototipa smo ustvarili tri videoposnetke, ki so med povsem resničnim okoljem in povsem navideznim okoljem prikazovali vsak po en scenarij primera uporabe aplikacije. Prvi [5]. Gre za okolje, kjer sta navidezni in resnični svet v enem video posnetek je prikazoval osnovno delovanje aplikacije in samem zaslonu. Za njeno delovanje se uporablja dovolj prvi primer uporabe – nakupovanje v nakupovalnem centru in zmogljiva tehnologija, kar zajema ustrezen senzor, procesor in ujetje željenega popusta. Drugi videoposnetek je prikazoval zaslon. prejem potisnega sporočila, ki ga uporabnik dobi ob novem popustu za izdelek, ki si ga želi. Tretji videoposnetek pa je prikazoval primer časovno omejenega popusta, ki ga uporabnik 3 PREGLED SORODNIH DEL mora ujeti v določenem časovnem obdobju ter ga shrani med svoje popuste ter unovči kadar je naslednjič v izbrani Obstoječe raziskave se intenzivno ukvarjajo z vprašanjem poslovalnici. Slika 1 prikazuje zaslonski posnetek iz učinkovitosti vpeljave igrifikacije kot inovativnega orodja v predstavitvenega video posnetka omenjenega primera. oglaševanje [6]-[8]. In sicer, Nobre in Ferreira [6] v svoji študiji ugotavljata, da je s pomočjo igrifikacije mogoče na inovativen način soustvarjati blagovno znamko, vplivati na vpletenost uporabnika in občutek povezanosti z blagovno znamko. Teotónio in Reis [7] ugotavljata, da porabniki iščejo zabavo, nagrade, rivalstvo, socialno vključenost – vse, kar jim ponuja igrifikacija. Prav tako se številni raziskovalci [9][10] ukvarjajo z elementi obogatene resničnosti v oglaševanju. Tako ugotavljajo, da se z uporabo tovrstne aplikacije poveča interakcija kupca in prodajalca, zviša ugled podjetja ter nenazadnje poviša tudi prodaja izdelkov [3],[10]. 4 METODOLOGIJA Slika 1: Slika zaslona predstavitvenega video posnetka. 4.1 Raziskovalna vprašanja Raziskovalna vprašanja smo oblikovali na osnovi pregleda 4.3 Vzorčenje in udeleženci raziskave obstoječe literature. Pogoji za vključitev udeležencev v raziskavo so bili naslednji: RV1: Kakšna je zaznana stopnja vidljivosti oglasa s hkratno  osebe so starejše od 18. leta, vpeljavo igrifikacije in mešane resničnosti v mobilno aplikacijo  osebe, ki (vsaj enkrat na mesec) nakupujejo v vsaj za oglaševanje? eni trgovski verigi, Prvo raziskovalno vprašanje smo zastavili, saj se je vpeljava  osebe, ki imajo v lasti pametni mobilni telefon, interaktivne igre v oglaševanje izkazala kot učinkovita in za uporabnika zanimiva metoda oglaševanja [8]. Za vključitev potencialnih udeležencev v raziskavo smo RV2: Kakšna je zaznana stopnja odločitve za nakup izdelka uporabili priložnostno vzorčenje. V raziskavi je sodelovalo 33 ob hkratni vpeljavi igrifikacije in mešane resničnosti v mobilno udeležencev. aplikacijo za oglaševanje? Drugo raziskovalno vprašanje smo zastavili, saj so pretekle 4.4 Merski instrument raziskave pokazale, da se z uporabo mešane resničnosti lahko Merski instrument, ki smo ga uporabili, je bil spletni anketni poveča stopnja prenosa informacij, sodelovanja ter pospeši vprašalnik. Sestavljen je bil iz treh delov. Prvi del je bil splošnejši odločanje [9]. Prav tako raziskave kažejo, da se z uporabo in je zajemal vprašanja o sami aplikaciji ter zajemal po eno aplikacije, ki vsebuje obogateno resničnost, poveča interakcija vprašanje, ki se je navezovalo na eno izmed raziskovalnih kupca in prodajalca, zviša ugled podjetja in tudi poveča prodaja vprašanj. Pri RV3 smo navezujoče se vprašanje povezali z izdelkov [10]. demografskim vprašanjem o starosti uporabnika. Drugi del RV3: Ali starost uporabnika vpliva na razumevanje uporabe vprašalnika je meril uporabniško izkušnjo – uporabili smo User mobilne aplikacije za oglaševanje, ki vključuje igrifikacijo in Experience Questionnaire (UEQ) [12]. Tretji del vprašalnika je mešano resničnost? meril uporabnost uporabniškega vmesnika – uporabili smo Zadnje raziskovalno vprašanje smo zastavili, saj so v eni od System Usability Scale (SUS) [13]. študij [11] ugotovili, da obstaja razlika v razumevanju aplikacij z obogateno resničnostjo med šolarji višjih razredov in študenti. 4.5 Postopek raziskave Glavna razlika se je pokazala v načinu razmišljanja, izkušnjah in načinu reševanja problemov. Pri načrtovanju in izvedbi raziskave smo sledili Evropskemu kodeksu ravnanja za ohranjanje raziskovalne poštenosti, s čimer smo se zavezali načelu spoštovanja udeležencev raziskave [14]. Prav tako smo upoštevali načela Kodeksa etike in integritete za 772 Razvoj in Ocenjevanje Prototipa Mobilne Aplikacije z Elementi Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Igrifikacije in Mešane Resničnosti raziskovalce na Univerzi v Mariboru (Univerza v Mariboru, uporabniško izkušnjo s pomočjo 26 nasprotujočih si lastnosti. 2014 - 2020), kodeksa Ameriškega združenja psihologov in Tabela 1 prikazuje rezultate UEQ lestvice. Razpon lestvice je kodeksa združenja spletnih raziskovalcev. Spoštovali pa smo med -3 in 3, kar označuje izjemno dobro aplikacijo. tudi Zakon o varstvu osebnih podatkov [15]. Testiranje prototipa je zaradi omejitev osebnih stikov v času pandemije COVID-19 potekalo na daljavo. Udeležencem Tabela 1: Rezultati UEQ lestvice raziskave smo poslali elektronsko pošto z navodili za izvedbo testiranja. Udeleženci so si v vnaprej določenem zaporedju Lastnosti Povprečje Varianca ogledali tri videoposnetke in na koncu izpolnili tri spletne Atraktivnost 1,482 0,93 vprašalnike. Preglednost 1,508 1,18 Učinkovitost 1,076 0,78 4.6 Statistična obdelava podatkov Vodljivost 0,765 0,65 Stimulativnost 0,886 0,84 Za analizo zbranih podatkov o udeležencih raziskave smo Originalnost 1,326 0,86 uporabili opisno statistiko, med tem ko smo za analizo podatkov, s pomočjo katerih smo želeli odgovoriti na raziskovalna vprašanja, uporabili tako opisno, kot tudi inferenčno statistiko. Kot zadnje smo ocenili še uporabnost uporabniškega Natančneje, odgovore na prvi dve raziskovalni vprašanji smo vmesnika z metodo SUS. Faktor SUS se prikaže na lestvici od 0 iskali z opisno statistiko, odgovor na zadnje raziskovalno do 100. V našem primeru smo izračunali kot povprečno SUS vprašanje pa z neparametričnim statističnim testom Kruskal- oceno vrednost 71,52. Udeleženci so uporabniški vmesnik Wallis H Testom. Podatke smo analizirali s programom IBM prototipa tako ocenili kot dobrega. Slika 2 prikazuje rezultate SPSS Statistics. SUS ocenjevanja. 4.7 Rezultati 100,0 Prvo raziskovalno vprašanje je spraševalo, kakšna je zaznana 80,0 stopnja vidljivosti oglasa s hkratno vpeljavo igrifikacije in mešane resničnosti v mobilno aplikacijo za oglaševanje. 60,0 Rezultati deskriptivne statistike so pokazali, da 51,5 % vseh 40,0 S rezultat udeležencev meni, da bi oglas nekoliko izstopal, 27,3 % SU udeležencev pa meni, da bi oglas zelo izstopal. Več kot polovica 20,0 udeležencev raziskave tako meni, da bi oglas, ki je pripravljen na 0,0 način kot so ga videli v videoposnetkih, nekoliko izstopal od 0 10 20 30 40 ostalih načinov oglaševanja. Številka udeleženca Drugo raziskovalno vprašanje je spraševalo, kakšna je zaznana stopnja odločitve za nakup izdelka ob hkratni vpeljavi igrifikacije in mešane resničnosti v mobilno aplikacijo za oglaševanje. Udeležence smo spraševali, kako ocenjujejo, da bi Slika 2: Rezultati SUS ocenjevanja. jih prikazana aplikacija motivirala k nakupu določenega oglaševanega izdelka [3]. Udeleženci raziskave so lahko izbirali 5 DISKUSIJA IN ZAKLJUČEK med petimi različnimi odgovori (1 – uporaba bi me zelo motivirala k nakupu, 5 – uporaba me nikakor ne bi motivirala). Izsledki pričujoče študije se ujemajo z ugotovitvami preteklih 57,6 % udeležencev meni, da bi jih uporaba aplikacije nekoliko raziskav. Tako na primer naši rezultati podpirajo rezultate motivirala k nakupu, 30,3 % pa jih pravi, da jih uporaba ne bi niti pretekle študije [8], kjer avtorji ugotavljajo, da je takšen način bolj, niti manj motivirala [3]. Več kot polovica udeležencev promocije zanimiv za uporabnika. Prav tako naši rezultati raziskave tako meni, da bi jih uporaba aplikacije nekoliko podpirajo rezultate drugih študij [9][10]. V omenjenih študijah motivirala k nakupu. namreč ugotavljajo, da se z uporabo mešane ali obogatene Tretje raziskovalno vprašanje je spraševalo, ali starost resničnosti dviga stopnja zanimanja za nakup iz strani uporabnika vpliva na razumevanje uporabe mobilne aplikacije za uporabnika. oglaševanje, ki vključuje igrifikacijo in mešano resničnost. Omejitve pričujoče raziskovalne študije so v izvedbi Uporabnike smo razvrstili v štiri starostne skupine: 1 – od 18 do testiranja prototipa. Le-ta namreč ni bil testiran na eni lokaciji z 29 let (19 uporabnikov), 2 – od 30 do 49 let (8 uporabnikov), 3 – več udeleženci. od 50 do 64 let (6 uporabnikov), 4 - več kot 65 let (1 uporabnik). Glede na zastopanost v vsaki starostni skupini, smo v analizo ACKNOWLEDGMENTS / ZAHVALA vključili prve tri starostne skupine. Rezultati Kruskal-Wallis H Zahvaljujemo se vsem udeležencem raziskave, brez katerih testa so pokazali statistično neznačilen rezultat, p > .05. S tem raziskave ne bi bilo mogoče izvesti. lahko sklepamo, da starost uporabnika ne vpliva na razumevanje aplikacije, ki vsebuje igrifikacijo in mešano resničnost [3]. REFERENCES Ocenjevali smo tudi uporabniško izkušnjo razvitega prototipa [1] Javornik A. Classifications of Augmented Reality Uses in Marketing. IEEE z UEQ vprašalnikom, kjer so udeleženci ocenjevali svojo International Symposium on Mixed and Augmented Reality 2014 Media, 773 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia M. Zorko et al. Art, Social Science, Humanities and Design Proceedings. 10 - 12 September [9] Whiskard, H., Jones, D., Voller, S., Snider, C., Gopsill, J., Hicks, B. Mixed 2014, Munich, Germany, (2014). Reality Tools as an Enabler for Improving Operation and Maintenance in [2] Deterding S., Sicart M., Nacke L., O’Hara K., Dixon D. Gamification. Using Small and Medium Enterprises. IFIP Advances in Information and game-design elements in non-gaming contexts. 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Lecture Notes in Computer Science, (2018), 164–174. 774 StreetGamez: detection of feet movements on the projected gaming surface on the floor Peter Škrlj Mark Lochrie peter.skrlj@student.upr.si mlochrie@uclan.ac.uk Univerza na Primorskem, UP FAMNIT Media Innovation Studio, University of Central Lancashire Koper, Slovenija Preston, UK Matjaž Kljun Klen Čopič Pucihar matjaz.kljun@famnit.upr.si klen.copic@famnit.upr.si Univerza na Primorskem, UP FAMNIT Univerza na Primorskem, UP FAMNIT Koper, Slovenija Koper, Slovenija Fakulteta za Informacijske Študije Fakulteta za Informacijske Študije Novo mesto, Slovenija Novo mesto, Slovenija ABSTRACT We implemented a software solution for a video game plat- form that is capable of detecting movement of players’ feet on the floor. The solution is a part of a wider project of using a drone as a platform that could project the game board on the floor as well as track movements and scores of differ- ent players. The whole system is composed of three parts: a drone, a mini projector, a depth camera and a computational device for running the software. For the latter two we used Google Tango to run spatial recognition, detect 3D shapes Figure 1: Complete detection system with projection. and obtain the device’s orientation in space. The system was implemented to the point where it can detect the player’s of novel street and chalk games. In this paper we present feet, transform the detected feet to a gaming surface and the software solution for a proposed game platform that is correct the projection distortion. capable of detecting movement of players’ feet on the floor. KEYWORDS 2 SYSTEM DESIGN exergaming, human-drone interaction, drones, pervasive The minimal set of functional requirements was: (i) Track computing player’s feet on a projected grid where each grid unit mea- sures 30x30 cm to support games such as “whack the mall”. A 1 INTRODUCTION particular unit activates when player steps on it. (ii) Provide Exercise games or exergames can be divided into three cate- quick feedback whilst correctly detecting fast movements, gories: location based games (e.g. [5]), games with motion which is vital for an exregaming platform. (iii) The projected tracking (e.g. [6]) and projection based games (e.g. [3]). In [4] surface should be always mapped as a rectangle. To avoid we proposed a new gaming concept that combines projection accidents, the drone should hover on the side of the pro- based games with drones and user tracking creating a novel jected surface, which would in this case be distorted and gaming platform that is (i) independent of location and (ii) should be corrected. (iv) The platform should support multi- offers a new gaming abilities that can facilitate various types ple players to increase motivation – an important element Permission to make digital or hard copies of part or all of this work for of exergaming. personal or classroom use is granted without fee provided that copies are We decided to use the Google Tango device, which is ca- not made or distributed for profit or commercial advantage and that copies pable of detecting player’s movement and control the projec- bear this notice and the full citation on the first page. Copyrights for third- tion. A variety of other devices could be used to achieve the party components of this work must be honored. For all other uses, contact same. However, at the time when the implementation begun the owner/author(s). Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia (2016), this was one of the rare devices with such functionali- © 2020 Copyright held by the owner/author(s). ties and light enough for drone carrying. For implementation and testing of the software solution we planned to use the 775 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Peter Škrlj, Mark Lochrie, Matjaž Kljun, and Klen Čopič Pucihar device in a static environment, placed 2m high of the floor Point cloud processing facing the playing field under an angle of 45-70 degrees. Once we know the position of the ground plane, we move Google Tango integrates three main functionalities. Mo- to Point cloud processing, which starts by obtaining point tion tracking of the device by using visual features of its cloud data. Then a simple min max filter on the Y axis can surroundings in combination with the accelerometer and be applied to isolate 3D points that are likely to be feet. We gyroscope. Area learning by recording the visual features set the filtering threshold to 20 cm distance from the ground and the measuring the distances. Depth perception by scan- plane. Points that fall out of this threshold are discarded. The ning and building a point cloud image of the room. From results of the filtering can be seen in Figure 2. this point cloud, a room meshes can be made and used as 3D models for further processing. This feature is of particular interest to us, as we planed to utilise the depth cloud in order to detect players movement over the ground plane. To appeal to a wider community of game developers, we decided to use Unity together with Google Tango’s SDK to obtain the callback calls and events from the C library used for processing signals in the Tango device itself. For projection we used the 200 lumens ASUS S3 connected Figure 2: Left — green coloured points are on the floor level, to Google Tango via mini HDMI port. S3 has a wide projec- orange points are objects that are within the 20 cm thresh- tion angle capable to project a large playing area from rela- old; Right — filtered image after min max filtering. tively short distance. The image projected has a trapezoidal distortion called keystone distortion caused by the projector After filtering, the remaining points are grouped into projecting at an angle to the projection surface. spherical geometric shapes. This is done by processing every point and trying to fit it into a nearby sphere. The radius of 3 PROTOTYPE IMPLEMENTATION the sphere was manually set to the default diameter of 30 The software is built of four (4) components: (i) floor plane cm. To simplify the grouping process, we ignore the Y coor- detection — detecting the ground plane and initialisation; (ii) dinate of the feedback mapping placing all feedback points point cloud processing and player detection — searching for to a single plane. Using a 2D image, we can generate distinct players feet position using information from depth camera; groups by using a simple grouping algorithm. Our algorithm (iii) RGB optimization — player identification and optimisa- starts the grouping process by randomly selecting a feedback tion of tracking performance; and (iv) rendering — projec- point. Then we check if there is any group defined within tor alignment correction — removing perspective distortions the threshold proximity of this point. If not, we create a new from the projection. point group, set its rank to 1 and set the location of the group to this point. If the point is found in the diameter of an exist- Floor plane detection ing group, it is added to the nearest one. The group position is then updated by weighted average as such: There are three common methods for generating depth in- formation: Stereo method using two cameras, Time of Flight N casting rays into the space and timing the bounces, and Struc- GroupPos = items × GroupPos + FeedbackPosition N tured Light. Tango uses the latter using IR projector, which i tems + 1 beams a grid pattern of dots where each sample group of the After processing all the points, the transformation from dots is uniquely identified. This way the IR projector and 2D group coordinates back to 3D coordinates occurs by av- IR camera are able to determine the exact position of the eraging the Y coordinate of group points. At this stage we detected point group. remove groups which consist of insufficient number of de- The first step of tracking players is to estimate where tected points. This value can be changed though game engine ground plane lies. This is done by floor plane detection algo- configuration. The result of this step is an averaged group rithm. After obtaining point cloud data, we start by mapping of strong feedbacks (Figure 3). points into buckets where the Y axis is kept in small deviation groups. At each new point cloud frame the points are added RGB optimization into group and once the threshold is reached, the algorithm Since the Tango depth camera has a relatively low refresh marks that Y coordinate as a ground plane. Since the Tango rate of 10Hz, we planned a fine grain tracking by analysing device can localise itself in the space, the ground plane needs captured images from RGB camera. To obtain data from the to be detected only once at the initialization stage. camera the SDK callbacks varied across different versions of 776 StreetGamez: detection of feet movements on the projected gaming surface on the floor Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia with intrinsic camera parameters. These are defined through camera calibration process done by the developer of the de- vice resulting in the coordinate system of the depth camera almost perfectly aligned with the device screen. As such we can ignore extrinsic camera parameters. After we receive 2D points, we clip the point groups into detection masks for the next step we call “Use the circles as masks to fine track Colour image”. In practice we map a 3D vector to camera view port by using Unity WorldToView- PortPoint method call. To proceed, we need to map colour image to the mask by scaling the 2D point so that it corre- Figure 3: Groups are being rendered back to the scene in sponds with the captured image. We are then able to cut the form of spheres that cover a certain area in the virtual world. detection area from the colour image. To enable adjusting the performance of the detection, the size of the detection square is possible to be manipulated via GUI. Tango Core. In Ikariotikos (Version 1.54, June 2017), an event needs to be registered that signals when a new camera image has been rendered to the buffer and is available for reading. Unfortunately, we were not able to obtain the RGB stream whilst depth camera was in operation. The reason for this is still not fully understood and the lack of documentation made it impossible to find the solution within the timeframe of this project. Nevertheless, we present the intended approach for optimising player tracking using color detection. Figure 5: Concept sketch of detecting player feets in RGB image with higher refresh rate. Using the mask the segments of detection image are cropped out (Figure 5) and the colour group detection is ran over us- ing OpenCV contours finding method, allowing us to filter the colour groups and detect centre and radius [1]. After detecting 2D point groups, we apply Unity methods to trans- form 2D location on the image to the world coordinates. Figure 4: Pinhole camera model showing how 3D pint is transformed to 2D image. Since our 3D point detection is also detecting the playing plane, it is possible to calculate the correct point of contact. We planned to perform the colour based tracking within Mapping the detected centres of the feedback back to the the regions detected by the depth camera whilst waiting for detected floor is an easy task. The points are transformed its next frame. The first step was to perform a transforma- with an inverse of the mapping of 3D point to the 2D screen tion of detected 3D points from the depth cloud to the screen space. We simply raycast the screen coordinate of the point coordinate system in the step we call “Transformation of to the floor and obtain the group position. points to view port frame”. This would allow us to create Rendering a mask with regions of interest. Such transformation can be done using a pinhole camera model (Figure 4) [2]. The Projector alignment correction. Projecting an image to a non projection of 3D point cloud to the screen can be therefore perpendicular surface in respect to the light source will pro- formulated as [xz] duce a distorted image commonly called a keystone effect. pixel = K × [X ZY ]3DPoint where (i) x, y is location of point in image coordinate system, (ii) X, Y, Z This distortion can be approximated by cos(ε − α /2)/cos(ε + α is location of points in world coordinate system in which /2), where ε is the angle of the surface being projected the data is provided, and (iii) K is a matrix of intrinsic cam- on, and α is the width of the focus. Because the projector Fx 0 Fx is mounted in the same space as the Tango device, and the era parameters 0 Fz Fy . To obtain the pixel coordinates device is spatially aware of its orientation in respect to the 0 0 1 within the view port frame, we need to multiply the 3D point ground plane, we can calculate the required adjustments to 777 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Peter Škrlj, Mark Lochrie, Matjaž Kljun, and Klen Čopič Pucihar the projected image and project the proper square to the are being calculated by the point cloud detection algorithm. floor. Two rotations that cause the keystone effect are ro- When a square is overlapped with the sphere it becomes tation Rz and Rx. Since the depth camera will be pointed active. at the players, the drone will need to be equipped with a gimbal maintaining the rotation Rx. To successfully correct 4 PROTOTYPE GAME the distortion caused by Rz we need to know the parameters Implementing the above, a simple game was created. The of the projector’s field of view (FOV), lense parameters and detection runs at 10-15 FPS with some lag spikes that addi- Rz in relation to the ground surface. tionally occur because of point cloud detection instability. We created a virtual scene with a single texture we call a Once the system is initialised (the ground plane is recognised) Render Texture and a virtual camera to which we assign FOV it starts tracking feet. Where these are tracked green spheres and aspect ratio that matches our projector. We place the are rendered and segments of the checker box pattern that virtual camera at a fixed distance and rotate the plane around intersect with the spares are coloured in green (see Figure 1). the z-axis in the opposite direction of tilt detected by the The playing area in the figure is of size 1,7x1,7 m, meaning Tango tracking system. In this way we render graphics where that the projected squares were approximately 27x27 cm. perspective distortions from rotation around the z-axis are The area could be increased by putting the projector and removed as seen in Figure 6. Tango further away. Because the playing field was relatively small, only 2 players could be on it at the same time. The player tracking would fail if there would be more players because of the excessive density of the detected points. 5 CONCLUSIONS It is important to note that the system is currently limited to projections on horizontal planar surfaces. The optimi- sation utilising colour tracking of players feet needs to be implemented. Thus, in order to support multiplayer games a unique footwear colour is required for each player. Despite these limitations and the fact that the Tango platform has Figure 6: Example of perspective mapping of square onto a flat surface. The internal camera mimics projectors field of been deprecated and integrated into Google ARCore, the view and inverts the projection angle. concepts presented can be utilised for a solution using an- other platform. More information on the system is available in [7]. This solution only corrects for one rotation, but as Tango device is capable of 6 DOF camera pose tracking, the rotation REFERENCES around x could be accounted for. We could also use tracking [1] Pablo Arbelaez, Michael Maire, Charless Fowlkes, and Jitendra Malik. information to fix the playing field onto a position in the real 2010. Contour detection and hierarchical image segmentation. IEEE world. The playing field would thus stay at the same place transactions on pattern analysis and machine intelligence 33, 5 (2010), regardless of the position and orientation of the drone. A 898–916. more advanced solution would be to use inverse transforma- [2] A Kaehler and G Bradsk. 2013. Computer Vision in C++ with the OpenCV Library. O’Relly (2013). tion using game shaders or other transformations possible [3] Raine Kajastila, Leo Holsti, and Perttu Hämäläinen. 2016. The aug- in Unity. A possible approach would be to apply the correct mented climbing wall: High-exertion proximity interaction on a wall- inverse trapezoid transformation to the image received from sized interactive surface. In CHI ’16. 758–769. Unity. [4] Matjaž Kljun, Klen Čopič Pucihar, Mark Lochrie, and Paul Egglestone. 2015. Streetgamez: A moving projector platform for projected street Mapping feedbacks to a 6x6 playing plane. In the initialization games. In CHI in Play ’17. 589–594. step, a ray is casted from the centre of the camera to the [5] Kate Lund, Paul Coulton, and Andrew Wilson. 2011. Free All Monsters! detected floor plane. The intersection of the ray and the a context-aware location based game. In MobileHCI ’13. 675–678. [6] Emily CS Murphy, Linda Carson, William Neal, Christine Baylis, David plane represents the centre of the detection matrix. Its centre Donley, and Rachel Yeater. 2009. Effects of an exercise intervention point is used for syncing the display grid with the detection using Dance Dance Revolution on endothelial function and other risk grid. The latter is defined in the engine with default values factors in overweight children. Internat. Jour. of Pediatric Obesity 4, 4 of 6 columns and 6 rows. This setting can be additionally (2009), 205–214. adjusted to allow more precise feedbacks. However, this may [7] Peter Škrlj. 2017. StreetGamez, a moving projector platform for games. Master’s thesis. University of Primorska, 6000 Koper. cause performance issues. After the grid is initialised, its fields are updated according to the sphere positions that 778 Anamorfična projekcija na poljubno neravno površino Anamorphic projection on an arbitrary uneven surface Rok Cej Franc Solina rokcej1997@gmail.com franc.solina@fri.uni- lj.si Laboratorij za računalniški vid Fakulteta za računalništvo in informatiko, Univerza v Ljubljani, Večna pot 113 1000 Ljubljana, Slovenia POVZETEK anamorfoze, je ta smer pogleda lahko bolj ali manj natančno določena. Razvili smo metodo, ki omogoča anamorfično projekcijo na ne- ravno, razbrazdano površino. Sliko, ki jo projeciramo v tem pri- meru, ni dovolj le v celoti perspektivno deformirati. Neravna po- 1.1 Vrste anamorfoz vršina je namreč sestavljena iz velikega števila majhnih ploskev Anamorfozo so odkrili v času renesanse, ko so umetniki in znan- različnih orientacij in za vsako od teh ploskev bi morali izraču- stveniki odkrivali zakone perspektive [2, 3]. Prva vrsta anamor- nati ustrezno perspektivno deformacijo. To najlažje storimo tako, foze, ki so jo uporabljali, je bila perspektivna anamorfoza. Per- da za vsak slikovni element projecirane slike izračunamo ustre- spektivno deformirana podoba je naslikana na ravno ploskev. Da zno deformacijo. To pa zahteva, da imamo 3D model površine, bi se ta anamorfična podoba razkrila, jo je potrebno pogledati z na katero se slika projecira, kar pridobimo s pomočjo senzorja določenega zornega kota, običajno je to dokaj oster kot glede na “Kinect”. ravnino, ki nosi deformirano podobo (Slika 1). Katoprične ali zrcalne anamorfoze za razkritje prave po- KLJUČNE BESEDE dobe potrebujejo ogledalo, običajno cilindrične ali konične oblike. Anamorfoza, Kinect, globinski senzor, optična iluzija Če tako ogledalo postavimo na pravo mesto, se deformirana po- doba razkrije kot odsev v ogledalu (Slika 2). ABSTRACT Med anamorfične upodobitve štejemo tudi iluzionistično sli- karstvo, kjer lahko na predvidenem mestu opazovanja prido- This report describes the creation of a distorted image or video bimo izrazit občutek prostorske dimenzije. V umetnostni zgodo- that looks perfect when projected onto a given uneven surface vini so znane predvsem poslikave stropov, kjer se nam dozdeva, and viewed from a predetermined angle. It utilizes the depth da se prostor odpira proti nebu (Slika 3), danes pa podoben pro- sensor Kinect and a projector. The program is written in C++ storski učinek uporabljajo potujoči umetniki, ki s kredo rišejo and it starts off by recreating the projection surface in 3D. It then podobe na ulicah (Slika 4). uses the surface model to create an anamorphic projection. If Sodobni umetniki, kot je npr. švicarski slikar Felice Varini [11], the Kinect and the projector are properly aligned, the projected anamorfozo uporabljajo pri poslikavi notranjih prostorov ali celih image or video creates an anamorphic illusion in real life. urbanih scen tako, da se z določenega zornega kota razkrije nek KEYWORDS pravilen geometrijski vzorec, kot da bi lebdel v prostoru (Slika 5). Anamorfični princip se uporablja tudi pri slikanju prometnih Anamorphosis, Kinect, depth sensor, optical illusion označb na cestišča, da bi bila bolj jasno berljiva in razločna pod ostrim kotom opazovanja, kot ga imajo vozniki in drugi ude- 1 UVOD leženci v prometu. Tudi razni reklamni napisi, ki jih pravilno vidimo v zrcalih ali pod določenim kotom opazovanja sodijo v Ljudje lahko dokaj zanesljivo interpretiramo slike, ki jih ne gle- kategorijo anamorfičnih poslikav. damo frontalno, ampak pod določenim kotom, saj zna naš za- S pojavom multimedijske tehnologije se je pojavila možnost, znavni sistem podzavestno razstaviti informacijo na vsebino slike da za prikaz anamorfičnih upodobitev uporabimo video projek- in na njeno perspektivno deformacijo. Še posebej dobro ta princip cijo. Na primer, reklamne napise je možno perspektivno deformi- deluje, če lahko zanesljivo zaznamo, kako je slikovna ploskev rati, tako da njihova projekcija iz notranjosti trgovin na pločnik orientirana v prostoru. Pri tem igra pomembno vlogo tudi kohe- pred trgovino ni deformirana in je zato lažje berljiva. renca med premikanjem opazovalca in perspektivno deforma- V Laboratoriju za računalniški vid smo celo razvili princip di- cijo. Majhen premik opazovalca povzroči le majhno spremembo namične anamorfoze, ki perspektivno deformacijo projecirane perspektivne deformacije. Pri anamorfičnih slikah pa ta kohe- slike stalno stalno prilagajajo poziciji opazovalca, tako da je z renca ne obstaja. Anamorfična podoba se tipično razkrije le iz opazovalčevega zornega kota slika stalno izgleda nedeformirana točno določene smeri opazovalčevega pogleda. Odvisno od vrste oziroma tako, kot če bi jo gledali frontalno [8]. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or 2 MOTIVACIJA distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this Če uporabljamo video projektor, je projecirana slika brez vsakr- work must be honored. For all other uses, contact the owner /author(s). šne perspektivne deformacije le, če jo gledamo natanko iz točke Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia projeciranja. Ker ima projektor svoje fizične dimenzije, to v praksi © 2020 Copyright held by the owner/author(s). seveda ni možno in zato je projecirana slika, ki jo gledamo vedno 779 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Rok Cej and Franc Solina Slika 1: Ena od najbolj znanih slik iz zgodovine umetnosti, ki upodablja perspektivno anamorfozo, sta Ambasadorja Hansa Holbeina iz leta 1533. Lobanja, ki se v frontalnem pogledu (levo) vidi kot eliptičen madež na sredini slike spodaj, pa se v pogledu od desno zgoraj (v sredini), razkrije kot lobanja (desno). Umetniki so tako ekstremno popačenje običajno uporabili, da bi skrili določene kontroverzne elemente na sliki (vir: Wikimedia Commons). Slika 2: Zrcalna anamorfoza: popačena 3D skulptura se v odsevu cilindričnega zrcala razkrije kot žaba (avtor: Jonty Slika 4: Uporaba perspektivne anamorfoze v uličnem sli- Hurwitz, vir: Wikimedia Commons). karstvu (avtor: Julian Beever, 1990-ta). Na levi se vidi iz- razit prostorski učinek, gledano z nasprotne strani, pa se vidi kako popačena je na tlaku dejanska podoba, še pose- bej izrazito noga kopalke, ki v 3D iluziji sega najdlje iz sli- kovne ploskve (vir: Wikimedia Commons). Slika 3: Primer iluzionistične poslikave stropa je v celjski Stari grofiji, ki ga umeščajo na prehod iz renesanse v zgo- dnji barok (vir: Wikimedia Commons). Slika 5: Ploskovna grafika superponirana na razgibano ur- nekoliko deformirana. Kot smo že v uvodu razložili, to običajno bano sceno, se v celoti razkrije le s točno določenega zor- ni problem, saj človeška zaznava z lahkoto loči med informacijo nega kota: Felice Varini, Port de St-Nazaire, Francija, za na sliki in zmerno perspektivno deformacijo te iste slike. Če pa je razstavo “Estuaire 2007” (vir: Wikimedia Commons). kot med osjo projekcije in smerjo našega pogleda zelo velik, pa že lahko nastopijo težave pri interpretaciji slike. Pri anamorfozi pa na ta način pravzaprav želimo skriti pravi pomen slike ali vsaj drugimi besedami, kako lahko izračunamo inverzno anamorfično dela slike. Še večji problem pri interpretaciji slike nastane, če deformacijo slike, da bo izgledala pravilno na poljubni neravni projekcijska površina ni ravna. Zato je naš raziskovalni motiv površini? naslednji – ali lahko projecirano sliko vnaprej deformiramo tako, Že pri običajni perspektivni anamorfozi moramo vedeti, kako da bo izgledala nedeformirano iz vnaprej določenega zornega kota, je slikovna ploskev orientirana v prostoru. Če pa želimo sliko pro- neglede na to, kakšna je površina, na katero projeciramo sliko? Z jecirati na poljubno neravno površino, moramo imeti 3D model 780 Anamorfična projekcija na poljubno neravno površino Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia te površine. Sodobna tehnika ima za odčitavanje 3D oblik številne vrednosti predstavlja razdaljo izraženo v milimetrih. Če te vre- odgovore. Cenovno ugodna in za naše potrebe je smiselna upo- dnosti preslikamo v sivinsko sliko, dobimo globinsko sliko, kjer raba senzorja Microsoft Kinect. Kinect smo v našem laboratoriju so v našem primeru svetle točke bolj oddaljene od senzorja. Kjer že uporabili za odčitavanje 3D površine v sorodnem projektu Kinect ni mogel zajeti globine, so točke črne barve. Svetlobni vodnjak [9], kjer smo klasični kamniti skulpturi dodali Aproksimacija manjkajočih globinskih podatkov. Ker Kinect ne še virtualno dimenzijo v obliki polzečih vodnih kapljic, ki smo more zajeti globine v vsaki točki bodisi zato, ker je bodisi točka jih z video projektorjem projecirali v obliki svetlobnih pik [10]. preveč oddaljena, ker se infrardeča svetloba, ki jo Kinect upora- blja, odbije od površine ali zaradi šuma. Manjkajoče vrednosti 3 SORODNA DELA določimo z aproksimacijo na osnovi sosednih točk. Na prvi pogled je naš cilj najbolj podoben tehnikam, ki s pomočjo Konverzija globinske slike v oblak 3D točk. Vrednosti posame- video projekcije na 3D predmete (angl. projection mapping [12]) znih slikovnih točk v globinski sliki spremenimo v koordinate ustvarijo obogateno resničnost in tako omogočijo povsem novo 3D točk z naslednjo enačbo: in dodatno dimenzijo dojemanja tudi gibajočih se predmetov, npr. [4]. Vendar se naš problem razlikuje od zgoraj opisanega v f ovx  ( 2x − 1) ∗ tan( )   width−1 2  dveh bistvenih elementih: pos⃗ition = depth  f ov  ∗  2y y −  (1)  ( heiдht 1) ∗ tan ( ) −  1 2 (1) Nam ni potrebno video projekcije poravnati z neko vnaprej      1  določeno 3D obliko oziroma predmetom. Zato kompleksna   geometrijska kalibracija med 3D površino, na katero se kjer je: depth = globina projecira in katere obliko zajema globinski senzor, ter vi- x,y deo projekcijo ni potrebna [5]. = indeks točke v globinski sliki (2) V večini sistemov za video obogateno resničnost je smer width, heiдht = resolucija senzorja v hor. in vert. smeri gledanja uporabnika v grobem poravnana s smerjo video f ovx , f ovy = zorni kot Kinecta v hor. in vert. smeri v radianih projekcije in zato do potrebe ali pojava perspektivne ana- morfoze niti ne pride, čeprav s sledenjem položaja uporab- Ker ima Kinect tudi barvno kamero, lahko poveže globinske točke nika nekateri sistemi tudi ustrezno korigirajo pespektivno s ustreznimi barvnimi vrednostmi iz barvne kamere. Zato lahko deformacijo v video projekciji [6]. te barve pripišemo tudi 3D točkam. Na sliki 6 je pogled na oblak 3D pobarvanih točk z različnih zornih kotov. V komercialnih sistemih za video obogateno resničnost, npr. [7], so tudi integrirani globinski senzorji, vendar ti služijo predvsem avtomatični segmentaciji scene na osnovi oddaljenost od projek- torja, da zamudna ročna segmentacija slike ni več potrebna. Zato smo se odločili za razvoj lastnega sistema za anamorfno projek- cijo na neravno površino, ki je namenjen opazovanju projekcije iz nekega vnaprej določenega zornega kota. 4 OPREMA Za anamorfično projekcijo na poljubno neravno površino potre- bujemo dve zunanji napravi: Microsoft Kinect in video projektor. Kinect meri razdalje med 0,5m in 4,5m, kar narekuje tudi naš delovni prostor za projekcijo anamorfoze. Programsko opremo za deformacijo slike smo zaradi hitrosti Slika 6: Pogled na oblak točk z različnih zornih kotov. izvajanja razvili v jeziku C++, čeprav bi po funkcionalnosti bila primerna tudi visokonivojska jezika kot sta Processing in Python. Uporabili smo naslednje knjižnice: Virtualna anamorfoza. Najprej bomo izračunali virtualno ana- • OpenGL morfozo v virtualnem prostoru, preden to naredimo v realnem : Aplikacijski programski vmesnik (API) za gra- prostoru. Najprej predpostavimo, da imamo virtualnega opazo- fiko – GLFW valca, ki gleda v smeri pravokotno na smer projekcijskega snopa. : kreiranje okolja OpenGL – GLEW Nato si predstavljajmo, da ta opazovalec projecira sliko na razgi- : nalaganje razširitev OpenGL – GLM bano projekcijsko površino. Ta slika bo za opazovalca izgledala : matrične in vektorske aplikacije • Kinect SDK povsem pravilno, toda iz smeri projektorja bo popačena. Za vsako : API za Kinect • FFmpeg točko v oblaku 3D točk, ki predstavlja projekcijsko površino, iz- : dekodiranje video zapisov • stb_image računamo smer med opazovalcem in to točko in ugotovimo, kje : branje slikovnih datotek ta premica prebada projecirano sliko. Na ta način določimo ko- 5 PERSPEKTIVNA ANAMORFOZA NA respondenco med vsako točko v oblaku 3D točk in ustreznim pikslom projecirane slike. Ko 3D točkam pripišemo korespon- NERAVNO POVRŠINO denčno teksturo iz slike, se v oblaku 3D točk pojavi popačena Postopek za inverzijo anamorfične deformacije slike smo razdelil slika, vendar če na oblak pogledamo iz smeri virtualnega opazo- na več korakov. valca, dobimo nepopačeno sliko (slika 7). Pridobivanje globinske slike. Globinske slike, ki jih pridobiva Prava anamorfoza. Da bi dosegli isti učinek tudi v realnem Kinect imajo dimenzijo 512 × 424, slikovne pike pa imajo celo- svetu, moramo sedaj izračunati sliko, ki naj jo projecira pro- številske vrednosti, ki so predstavljene s 16 biti. Vsaka od teh jektor, da bi opazovalec videl nepopačeno sliko. Za vsak piksel 781 Information Society 2020, 5–9 October 2020, Ljubljana, Slovenia Rok Cej and Franc Solina Slika 9: Levo: originalna slika; Sredina: projecirana slika na nagnjeno, neravno površino; Desno: pogled na projeci- rano sliko navpično navzdol. Slika 7: Virtualna anamorfoza: pogled iz smeri projektorja (levo) in pogled iz smeri virtualnega opazovalca (desno). natančnim globinskim senzorjem. Vseeno pa je tak način video projekcije na poljubno neravno površino možno uporabiti za šte- projecirane slike izračunamo smer v katero se ta piksel proje- vilne aplikacije. Če bi v živo zajemali globinsko sliko, kar Kinect cira v 3D prostoru. Zanima nas, kje je presečišče med to smerjo nenazadnje omogoča, bi bilo možno projecirati nedeformirane in projekcijsko površino, ki pa je predstavljena kot oblak 3D slike in video tudi na gibajoče se tarče. točk. Dodaten problem povzroča še različna resolucija projeci- rane slike, ki je veliko višja od resolucije globinskega senzorja ZAHVALA (Kinecta), ki definira oblak 3D točk. Zato večina pikslov proje- Raziskovalni program Računalniški vid št. P2-0214 (B) je sofi- cirane slike ni imela direktne korespondenčne 3D točke, ampak nancirala Javna agencija za raziskovalno dejavnost Republike smo morali iz štirih najbližjih 3D točk izračunati približek prese- Slovenije iz državnega proračuna. čišča. Za vsako presečiščno točko smo nato, upoštevaje pozicijo virtualnega opazovalca, lahko povezali piksle projecirane slike z LITERATURA ustreznim pikslom na sliki. [1] Rok Cej. Demonstracija anamorfoze na neravno površino Ker je ta postopek dokaj zamuden, smo uporabili večnitno (video). 2020. url: http://youtu.be/_eypZlZTRcM (prido- procesiranje, saj je določanje vrednosti posameznih pikslov v bljeno 10. 9. 2020). projecirani sliki, neodvisno drug od drugega. Primer tako izraču- [2] Daniel L Collins. “Anamorphosis and the Eccentric Obser- nane projecirane slike je na sliki 8. ver: History, Technique, and Current Practice”. V: Leonardo 25.2 (1992), str. 179–187. [3] Daniel L Collins. “Anamorphosis and the Eccentric Obser- ver: Inverted Perspective and Construction of the Gaze”. V: Leonardo 25.1 (1992), str. 72–82. [4] Creators. Box. 2013. url: https://youtu.be/lX6JcybgDFo (pridobljeno 24. 9. 2020). [5] Anselm Grundhöfer in Daisuke Iwai. “Recent advances in projection mapping algorithms, hardware and applicati- ons”. V: Computer Graphics Forum. Zv. 37. 2. Wiley Online Library. 2018, str. 653–675. [6] Brett Jones in sod. “RoomAlive: Magical Experiences Ena- Slika 8: Anamorfoza v oblaku 3D točk (levo) in projecirana bled by Scalable, Adaptive Projector-Camera Units”. V: anamorfično deformirana slika (desno). Proceedings of the 27th Annual ACM Symposium on User Interface Software and Technology. 2014, str. 637–644. [7] Lightform, Design Tools for Projection. 2020. url: http:// Kalibracija. Preden posnamemo 3D model površine za projeci- lightform.com (pridobljeno 10. 9. 2020). ranje ga moramo kalibrirati z video projektorjem. Implementirali [8] Robert Ravnik in sod. “Dynamic anamorphosis as a special, smo funkcijo, ki na oblak 3D točk nariše rdeč pravokotnik, ki computer-generated user interface”. V: Interacting with computers predstavlja področje, za katerega Kinect pričakuje, da bo nanj 26.1 (2014), str. 46–62. projecirana slika. Uporabnik mora nato ročno poravnati pozi- [9] Franc Solina in Blaž Meden. “Light fountain–a virtually cijo Kinecta ali video projektorja tako, da se rdeči pravokotnik enhanced stone sculpture”. V: Digital Creativity 28.2 (2017), poravna s projecirano sliko. str. 89–102. [10] Solina, Franc. Light Fountain 2 - Galaxy. 2018. url: http: 6 REZULTATI IN ZAKLJUČEK //youtu.be/y6NAiXlNm20 (pridobljeno 10. 9. 2020). [11] Wikipedia contributors. Felice Varini — Wikipedia, The Free Slika 9 prikazuje projekcijo fotografije v horizontalni smeri na na- Encyclopedia. 2020. url: http://en.wikipedia.org/w/index. gnjeno razbrazdano kamnito površino in pogled na to projekcijo php?title=Felice_Varini&oldid=953793776 (pridobljeno navpično navzdol, kjer se anamorfoza razkrije — proporci slike 10. 9. 2020). so enaki kot na originalni fotografiji. Program na zmogljivem [12] Wikipedia contributors. Projection mapping — Wikipedia, osebnem računalniku teče dovolj hitro, da lahko v realnem času The Free Encyclopedia. 2020. url: https://en.wikipedia.org/ procesiramo tudi video [1]. wiki/Projection_mapping (pridobljeno 10. 9. 2020). Zaradi nenatančnosti pri zajemu globinske slike je v anamor- fični sliki še nekaj nenatančnosti, kar bi bilo možno preseči z bolj 782 Učinkovita predstavitev slovarskih jezikovnih virov pri govornih tehnologijah Jerneja Žganec Gros Žiga Golob Simon Dobrišek Alpineon d.o.o. Alpineon d.o.o. Univerza v Ljubljani, FE Ulica Iga Grudna 15 Ulica Iga Grudna 15 Tržaška cesta 25 1000 Ljubljana, Slovenija 1000 Ljubljana, Slovenija 1000 Ljubljana, Slovenija jerneja.gros@alpineon.si ziga.golob@alpineon.si simon.dobrisek@fe.uni-lj.si POVZETEK Pregled znanstvene literature pokaže, da pri izgradnji govornih tehnologij za jezike z velikim številom pregibnih oblik uporaba Končni pretvorniki predstavljajo kompakten način za predstavitev postopkov, ki so bili razviti za angleški jezik, ni učinkovita (Golob, slovarjev izgovarjav, ki jih potrebujemo pri sintezi ali prepoznavi 2012). Zaradi velikega števila pregibnih oblik besed pri istem govora. V članku je predstavljena nadgradnja končnih številu leksemov se obsežnost prepoznavalnika slovenskega pretvornikov, t.i. končni super pretvorniki, s katerimi lahko govora v primerjavi s primerljivim prepoznavalnikom angleškega razširjeni slovar izgovarjav predstavimo z manjšim številom stanj govora vsaj podeseteri. Zato je potrebno posebno pozornost in prehodov kot s pomočjo minimalnega determinističnega posvetiti prav optimizaciji uporabljenih modelov in njihovi končnega pretvornika. Končni super pretvornik ohranja adaptaciji na morfološke posebnosti pregibno bogatih jezikov. determinističnost, poleg besed iz slovarja lahko dodatno sprejme Pomemben del govorno tehnološke aplikacije, kot je denimo tudi nekatere druge, neznane besede. Pri tem so lahko oddani sintetizator govora, predstavlja sistem za pretvorbo grafemskega izhodni alofonski prepisi za določene neznane besede napačni, zapisa besed v alofonski prepis. Samodejno določanje alofonskega vendar se izkaže, da je napaka primerljiva s trenutno najboljšimi prepisa v slovenščini temelji na množici kontekstno odvisnih metodami za določanje grafemsko-alofonske pretvorbe. pravil, pri čemer moramo poznati besedni naglas (Gros in Mihelič, KLJUČNE BESEDE 1999). Samodejno določanje besednega naglasa slovenskih besed zaradi nepredvidljivosti naglasnega mesta predstavlja zahtevno govorne tehnologije, jezikovni viri, sinteza govora, slovarji nalogo (Golob, 2009), zato je za kvalitetno sintezo slovenskega izgovarjav govora nujna uporaba obsežnih slovarjev izgovarjav. Slovar izgovarjav predstavlja preslikavo grafemskih zapisov besed v alofonske prepise. Pri pregibno bogatih jezikih, kot je 1 Uvod slovenščina, lahko slovarji vsebujejo več milijonov slovarskih Govorno podprti uporabniški vmesniki omogočajo uporabniško vnosov, zaradi česar je lahko njihova uporaba v pomnilniško manj prijazno interaktivno komunikacijo, še posebej v okolju mobilnih zmogljivih sistemih, kot so npr. vgrajeni sistemi, problematična. V komunikacij. Sodobni koncepti sistemov govorne komunikacije se teh primerih je nujna uporaba postopkov, ki omogočajo v praksi prenašajo na majhne prenosne naprave, ki so zasnovane na pomnilniško učinkovito predstavitev slovarjev. vgrajenih sistemih (angl. embedded systems), za katere sta značilna Zato smo želeli poiskati in preizkusiti učinkovite postopke za omejena procesorska moč ter pomnilniška zmogljivost. Za uspešen zmanjševanje odvečnosti pri predstavitvi in računalniškem zapisu razvoj in uporabo govorno podprtih aplikacij na prenosnih jezikovnih virov za pregibno bogate jezikovne skupine, ki bodo napravah je potrebno zagotoviti učinkovite in visoko kakovostne omogočali hitro, pomnilniško čim manj zahtevno ter komponente sistema govornega dialoga, to je uspešnost visokokakovostno pretvorbo grafemskega zapisa besed v fonetični avtomatskega razpoznavanja govora in kakovostno, razumljivo in prepis in obratno. naravno zvenečo sintezo govora. V literaturi je mogoče zaslediti predvsem tri metode, ki Implementacija predstavitve leksikalnih jezikovnih virov v omogočajo pomnilniško učinkovito predstavitev slovarjev celovitih sistemih za prepoznavanje ali sintezo govora na vgrajenih izgovarjav, in sicer s pomočjo oštevilčenih končnih avtomatov platformah predstavlja netrivialen problem, ki ga še dodatno (Lucchesi in Kowaltowski, 1993; Daciuk in Piskorski, 2011), otežujejo omejitve zaradi uporabljene strojne opreme. dreves predpon (Ristov, 2005) ter končnih pretvornikov (odslej kratko KP) (Mohri, 1994; Golob at al., 2012). V tem delu bomo Permission to make digital or hard copies of part or all of this work for personal or predstavili nov način predstavitve s pomočjo končnih super classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation pretvornikov (odslej kratko KSP), ki predstavljajo nadgradnjo KP. on the first page. Copyrights for third-party components of this work must be honored. Poleg manjše predstavitve slovarjev v primerjavi s KP, lahko s KSP For all other uses, contact the owner/author(s). Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia z visoko točnostjo določimo alofonski prepis tudi nekaterim © 2020 Copyright held by the owner/author(s). neznanim besedam oz. besedam, ki niso vsebovane v izvirnem slovarju izgovarjav. 783 V članku bomo najprej na kratko predstavili KP ter prikazali, 3 Vpliv velikosti slovarja izgovarjav na velikost kako lahko z njimi predstavimo slovar izgovarjav. Nadalje bomo končnega pretvornika KP pokazali, da zastopanost pregibnih oblik v slovarju močno vpliva na velikost KP. Sledi predstavitev KSP, ki predstavljajo nov način V tem eksperimentu smo želeli preveriti odvisnost velikosti KP od velikosti slovarja, ki ga želimo predstaviti. Na voljo smo imeli predstavitve slovarjev. Rezultate bomo predstavili na jezikovnih slovar SI-PRON za slovenski jezik, ki vsebuje več kot milijon virih, ki so bili nadgrajeni v okviru projekta OptiLEX. različnih slovarskih vnosov (Žganec-Gros et al., 2006). Slovar smo razširili z dodatnimi leksikalnimi enotami, ki smo jih razvili v 2 Končni pretvorniki (KP) ter predstavitev okviru projekta OptiLEX. slovarjev izgovarjav Z naključnim izbiranjem slovarskih vnosov smo zgradili več pod-slovarjev različnih velikosti in za vse pod-slovarje zgradili KP sestavljajo stanja ter prehodi med stanji. Vsak prehod ima MDKP. vhodno in izhodno oznako. Ko se na vhodu KP pojavi določen Velikost MDKP, je podobno kot v eksperimentu, izvedenemu vhodni niz, se ta nahaja v začetnem stanju. KP nato po vrsti na manj obsežnih jezikovnih virih (Golob et al., 2012), dosegla vrh sprejema vhodne simbole. Pri vsakem sprejetju vhodnega simbola pri 78% do 83% velikosti prvotnega slovarja. To pomeni, da začne odda izhodni niz simbolov, ki ga določa izhodna oznaka velikost MDKP pri določeni velikosti z dodajanjem novih besed oz. pripadajočega prehoda, ter se premakne v naslednje stanje. Če za slovarskih vnosov iz slovarja upadati. To opažanje je bilo poljuben vhodni simbol v trenutnem stanju ne obstaja prehod, ki motivacija za razvoj nove vrste končnih pretvornikov, ki jim ima vhodno oznako enako temu simbolu, pravimo, da KP vhodnega pravimo končni super pretvorniki., in jih opisujemo v naslednjem niza ne sprejema. Če se KP po prejetju vseh simbolov vhodnega razdelku. niza nahaja v končnem stanju, pravimo, da vhodni niz sprejema, pri tem pa postane oddan izhodni niz veljaven. Omenimo še to, da je lahko vhodna ali/in izhodna oznaka enaka praznemu simbolu oziroma nizu. KP, ki imajo v poljubnem stanju največ en prehod z določeno vhodno oznako, pravimo deterministični KP. Za takšne KP je Slika 2: MDKP za izmišljen slovar, katerega ključi so hitrost pretvorbe vhodnega niza v izhodni niz zelo hitra in ob sestavljeni iz vseh možnih izborov dveh črk od treh možnih – a, primerni izvedbi odvisna samo od dolžine vhodnega niza. Druga b in c. Pri tem so vrednosti enake ključem. prednost determinističnih KP je ta, da obstajajo učinkoviti algoritmi za njihovo minimizacijo. Tako dobimo minimalni KP, ki Da bi si ta pojav lahko lažje predstavljali, poglejmo minimalni ima najmanjše število prehodov in stanj med vsemi ekvivalentnimi primer, ki prikazuje mehanizem tega zmanjšanja velikosti MDKP. KP (Mohri, 1997), torej KP, ki za poljuben sprejet vhodni niz Slovarski vnosi so sestavljeni iz para ključ, vrednost. Pri slovarju oddajo enak izhodni niz. izgovarjav tako grafemski zapis predstavlja ključ, alofonski prepis pa vrednost. Kot primer vzemimo vzorčni slovar, katerega ključi so sestavljeni iz vseh možnih izborov dveh črk od treh možnih, npr. črk a, b in c. Na ta način dobimo 9 različnih ključev, in sicer: aa, ab, ac, ba, bb… Zaradi enostavnosti naj bodo pripadajoče vrednosti enake ključem. MDKP za ta slovar prikazuje slika 2. Slika 1: Primer KP, ki predstavlja slovar izgovarjav za štiri slovenske besede: hiš, hiša, hiter in hitra. Krogi predstavljajo stanja, puščice pa prehode med stanji. Vsak prehod je označen z vhodno in izhodno oznako, ki sta ločeni z dvopičjem. Začetno stanje je označeno z odebeljenim krogom, končna stanja pa z Slika 3: MDKP za enak slovar, kot ga predstavlja MDKP na dvojnim krogom. sliki 2, pri čemer mu manjka slovarski vnos cc : cc. Vseh KP ni mogoče determinizirati, saj imajo deterministični KP manjšo izrazno moč kot nedeterministični (Hellis, 2004). KP, Sedaj iz omenjenega slovarja odstranimo slovarski vnos cc : cc ki predstavlja slovar izgovarjav, lahko vedno determiniziramo, če ter ponovno zgradimo MDKP. Rezultat prikazuje slika 3. Opazimo iz slovarja odstranimo enakopisnice. Slika 1 prikazuje primer lahko, da se je pri odstranitvi slovarskega vnosa iz slovarja minimiziranega in determiniziranega KP (odslej kratko MDKP), ki kompleksnost MDKP povečala, saj je za predstavitev slovarja predstavlja slovar za štiri slovenske besede. potrebno eno dodatno stanje ter dva dodatna prehoda. V (Golob et al., 2012) in (Golob et al., 2016) smo podrobneje raziskali vzroke, 784 ki vplivajo na zmanjšanje MDKP pri predstavitvi slovarja pri pregibne oblike, saj si lahko v tem primeru leme, ki se enako dodajanju novih slovarskih vnosov. pregibajo, del končnega pretvornika, ki pretvarja končnice, v celoti delijo. Kompleksnost pri tem še vedno povečujejo besede oz. leme besed, ki imajo med pregibnimi oblikami kakšno izjemo, ki se 3.1 Vpliv množičnosti pregibnih oblik na pregiba nekoliko drugače. V našem izmišljenem slovarju je to lema velikost slovarja izgovarjav zasp, katere dve pregibni obliki imata nekoliko drugačno končnico, Preverili smo vpliv množičnosti pregibnih oblik lem besed iz in sicer končnico al ter ali namesto il ter ili. slovarja na velikost MDKP. Pri tem z množičnostjo pregibnih oblik mislimo na število različnih pregibnih oblik za določeno lemo. Za primer smo vzeli besedo skopati ter v slovarju poiskali vse slovarske vnose, katerih grafemski zapisi predstavljajo pregibne oblike leme izbrane besede. Dobili smo 27 različnih slovarskih vnosov, iz katerih smo s pomočjo naključnega izbiranja vnosov tvorili še štiri različno velike pod-slovarje. Za vsak pod-slovar smo zgradili MDKP. Iz rezultatov je razvidno, da hitrost naraščanja velikosti MDKP z večanjem slovarja rahlo pada, vendar pa ni opaziti obrata trenda povečevanja MDKP (Golob et al., 2012). 3.2 Vpliv množičnosti pregibnih oblik na velikost slovarja izgovarjav Poglejmo sedaj, kako na velikost MDKP vpliva zastopanost pregibnih oblik v slovarju, sestavljenem iz večih besed, ki se podobno pregibajo. Iz slovarja SI-PRON smo izbrali 28 grafemskih zapisov besed, katerih pregibne oblike imajo 9 različnih končnic ter pripadajo štirim različnim lemam - potop, osmod, zasp, natoč. Slika 4: Del MDKP, ki predstavlja celoten slovar z vsemi 28 Izbrane leme ter pripadajoče končnice so prikazane v tabeli 1. vnosi. Prikazan je le del, ki pretvarja končnice vnosov. Lema zasp pri tem predstavlja izjemo, ki se pregiba nekoliko drugače kot ostale tri. MDKP sprejme samo vnose, ki so vsebovani v slovarju. Če za določeno aplikacijo tako stroga zahteva ni potrebna in je dovolj, da Tabela 1: Tabela prikazuje postopek za tvorjenje vseh besed, MDKP sprejme vse vnose iz slovarja, ga lahko naprej ki so vsebovane v slovarju. V levem stolpcu so navedene leme poenostavimo. Še enostavnejšo obliko bi namreč dobili, če bi za besed, v desnem pa možne končnice. vse štiri leme iz slovarja obstajale pregibne oblike za vseh 9 možnih končnic. V slovar lahko tako dodamo dodatne vnose in sicer vnose MOŽNE LEME MOŽNE KONČNICE z lemami potop, osmod, natoč ter končnicama al ter ali, ter vnosa z potop, osmod, zasp, natoč iš,im,imo,ite,ijo lemo zasp in končnicama il ter ili. Pridobljeni slovar ima tako 36 potop, osmod,natoč vnosov, MDKP pa se poenostavi na 23 stanj in 30 prehodov. i+l,i+li zasp a+l, a+li 4 Končni super pretvornik (KSP) Iz teh besed smo nato tvorili slovar, pri čemer smo zaradi V prejšnjem razdelku smo pokazali, da lahko s pomočjo dodatnih, enostavnosti vrednosti ključev izenačili s ključi. Nato smo z izbranih slovarskih vnosov v slovar zmanjšamo kompleksnost naključnim izbiranjem iz tega slovarja tvorili še štiri različno velike MDKP. Problem predstavlja iskanje takšnih slovarskih vnosov, ki pod-slovarje. Za vse tako zgrajene slovarje smo zgradili MDKP. bi zmanjšali kompleksnost, še posebej v primeru realnih slovarjev, Velikost MDKP, ki predstavlja vseh 28 vnosov slovarja, manjša kot so npr. slovarji izgovarjav, ki so prvič večji, drugič pa se ključ od MDKP, ki predstavljata slovarja s 23 in 17 vnosi, število stanj in vrednost posameznih slovarskih vnosov razlikujeta, s čimer je pa je večje celo pri MDKP, ki predstavlja slovar z 9 vnosi. Rezultati iskanje primernih slovarskih vnosov težja naloga. nakazujejo, da zastopanost pregibnih oblik močno vpliva na Problema smo se zato lotili na drugačen način, in sicer tako, da smo kompleksnost pridobljenega MDKP ter lahko vpliva na obrat združevali določena stanja, pri čemer smo želeli zadostiti trenda rasti velikosti MDKP. naslednjima dvema pogojema: Slika 4 prikazuje shematski prikaz dela MDKP, ki predstavlja • Pridobljeni KP mora ostati determinističen. končnice besed za slovar z 28 vnosi. Kompleksnost MDKP, ki • Pridobljeni KP mora sprejemati vse ključe prvotnega slovarja predstavlja slovar z manj vnosi, je precej večja. Zato je smiselno, ter za sprejete ključe oddati pravilne pripadajoče vrednosti. da so v slovarju, ki ga želimo realizirati s KP, prisotne vse možne 785 Tako smo lahko združevali samo stanja, ki so imela določene 6 Zaključek lastnosti. Takšna stanja smo poimenovali združljiva stanja. Dve V članku je predstavljen nov tip KP, ki smo jih poimenovali končni stanji sta združljivi, če zadoščata naslednjim pogojem: super pretvorniki (KSP), ki poleg želenih besed sprejemajo še • Če je eno od stanj končno stanje, stanji ne smeta imeti nekatere druge z namenom, da lahko pretvorbo želenih besed izhodnih prehodov s praznimi vhodnimi simboli oz. ε simboli. predstavimo bolj kompaktno. Rezultat združevanja takšnih stanj je lahko nedeterministični KP. Pokazali smo, da lahko pri predstavitvi slovarja izgovarjav s • Stanji nimata izhodnih prehodov z enakimi vhodnimi simboli pomočjo KSP število stanj in prehodov zmanjšamo za več kot 20%, ter različnimi izhodnimi simboli. ko so za vsebovane leme v slovarju izgovarjav prisotne tudi vse • Stanji nimata izhodnih prehodov z enakimi vhodnimi simboli pripadajoče pregibne oblike besed. ter enakimi izhodnimi simboli, ki prehajajo v različna naslednja Ker KSP sprejemajo še druge, neznane besede, za katere lahko stanja, ki so nezdružljiva. oddajo napačen izhodni niz, so KSP uporabni predvsem v Da bi lahko določili združljiva stanja, je potrebno preveriti aplikacijah, kje ne potrebujemo informacije o tem, katere besede so zgornje pogoje, kar pa je v praksi lahko problematično, saj je vsebovane v KP ampak le informacijo o pravilni pretvorbi danih preverjanje združljivosti stanj zaradi rekurzivnosti, ki je lahko besed oz. besed, iz katerih smo zgradili KSP. ciklična, zahtevno. V ta namen smo zadnji pogoj poenostavili: • Stanji nimata izhodnih prehodov z enakimi vhodnimi simboli ter enakimi izhodnimi simboli, ki prehajajo v različna nasled Zahvala nja stanja. Razvojno raziskovalno delo je delno sofinancirala Javna agencija Zaradi poenostavitve pogoja za združljivost stanj nekaterih za raziskovalno dejavnost Republike Slovenije v sklopu združljivih stanj nismo mogli zaznati. KSP smo zgradili tako, da aplikativnega raziskovalnega projekta OptiLEX (L7-9406). smo najprej zgradili MDKP, nato pa smo nadalje združili vsa stanja, ki so združljiva. Za vsako stanje je bilo potrebno preveriti, LITERATURA IN VIRI ali je združljivo s katerim koli drugim stanjem. Ker nekatera stanja [1] Cyril A., Michael R., Johan S., Wojciech S., Mohri M., 2007. OpenFst: A postanejo združljiva šele, ko združimo neka druga stanja, je bilo General and Efficient Weighted Finite-State Transducer Library. Proceedings of potrebno to storiti v več iteracijah. the 12th International Conference on Implementation and Application of Automata (CIAA 2007). Lecture Notes in Computer Science, Prague, Springer- Verlag, Heidelberg, Germany, 4783: 11-23. [2] Daciuk J., Piskorski J., Ristov S., 2011. Natural Language Dictionaries 5 Predstavitev slovarja izgovarjav s končnimi Implemented as Finite Automata. Scientific Applications of Language Methods. super pretvorniki KSP London: Imperial College Press, World Scientific Publishing. [3] Golob Ž., 2009. Samodejno določanje mesta besednega naglasa pri sintezi Za razširjeni slovar izgovarjav iz razdelka 3 smo najprej zgradili slovenskega govora. Diplomsko delo, Fakulteta za elektrotehniko v Ljubljani. MDKP s pomočjo odprtokodnega orodja OpenFST (Cyril at al., [4] Golob Ž., Žganec-Gros J., Žganec M., Vesnicer B., Dobrišek S., 2012. FST- 2007), nato pa smo s postopkom, ki smo ga opisali v razdelku 4, Based Pronunciation Lexicon Compression for Speech Engines. International zgradili še KSP. Tabela 2 prikazuje število stanj in prehodov Journual of advanced robotic systems, 9: 2012. MDKP in KSP. [5] Golob Ž., Žganec-Gros J., Štruc, V., Mihelič, F., Dobrišek S, 2016. A composition algorithm of compact finite-state super transducers for grapheme- to-phoneme conversion. Proceedings of the Text, speech and dialogue Tabela 2: Zmanjšanje števila stanj in prehodov pri gradnji Conference, Brno, Czech Republic, September 12-16, 2016. Switzerland: KSP iz MDKP. Springer, str. 375-382, Lecture notes in artificial intelligence, 2016. [6] Gros J., Mihelič F., 1999. Acquisition of an Extensive Rule Set for Slovene MDKP KSP Sprememba Grapheme-to-Allophone Transcription. Proceedings 6th European Conference on Speech Communication and Technology. September 5–9. 1999. Eurospeech 1999. Budapest, 5: 2075–2078. 1 izhodni Stanja 246.262 186.476 24.3% simbol Prehodi 556.723 441.234 20.7% [7] Hellis T., 2004. On minimality and size reduction of one-tape and multitape finite automata. Doktorska disertacija. [8] Lucchesi C., Kowaltowski T., 1993. Applications of Finite Automata Opazimo lahko, da smo velikost KSP v primerjavi z velikostjo Representing Large Vocabularies. Software-Practice & Experience, 23: 15-30. MDKP uspeli zmanjšati za več kot 20%. [9] Mohri M., 1994. Compact Representations by Finite-State Transducers. 32nd Čeprav lahko s KSP vnose v slovarju predstavimo z manjšim Meeting of the Association for Computational Linguistics (ACL '94). KP kot v primeru MDKP, pri tem izgubimo informacijo o tem, Proceedings of the Conference. Las Cruces. NM, pp. 204–209. katere besede so vsebovane v slovarju. Tako se lahko zgodi, da KSP [10] Mohri M., 1997. Finite-State Transducers in Language and Speech Processing. Computational Linguistics, 33: 269–311. sprejme določeno besedo, ki je slovnično pravilna, vendar ni bila vsebovana v slovarju. V tem primeru je lahko oddan alofonski [11] Ristov S., 2005. LZ Trie and Dictionary Compression. Jurnual Software- prepis napačen. Practice & Experience, pp. 445–465. [12] Žganec-Gros J., Cvetko-Orešnik V., Jakopin P., 2006. SI-Pron Pronunciation Lexicon: A New Language Resource for Slovenian. Informatica, 30: 447–452. 786 The Fundamentals of Sound Field Reproduction Using a Higher Order Ambisonics System Rok Prislan* rok.prislan@innorenew.eu InnoRenew CoE Livade 6, SI-6310, Izola, Slovenia ABSTRACT Conventional sound recording methods are based on record- ing the sound pressure level with a microphone which is after some signal processing reproduced by loudspeakers. In spa- tial audio, more than one microphone and loudspeaker are required to provide the sound source location information to the listener. Several spatial audio formats have been de- veloped and some have successfully entered our homes, such as the the multichannel 5.1 surround system. Among spatial audio formats, Ambisonics stands out due to its capability of capturing and reproducing the whole sound field and is not limited to predefined loudspeaker setups. In the paper, the InnoRenew CoE’s Ambisonics system is introduced and some of its underlying principles are explained. Furthermore, practical examples of the use of Ambisonics, also in relation to Virtual reality applications, are presented. KEYWORDS higher order Ambisonics, sound field reproduction 1 INTRODUCTION Figure 1: The higher order Ambisonics reproduction Michael Gerzon [1] invented Ambisonics in the 1970s, and system with 64 loudspeakers (top) and the Ambison- since it has mainly been a research topic in acoustics. It’s ics microphone [2] (bottom) which are part of the higher order version was developed twenty years later but only InnoRenew CoE’s acoustic laboratory equipment. recently it has become a commercially available recording system [2]. Currently, more and more user applications of Am- bisonics are emerging since Ambisonicsis is being positioned as the audio framework of choice for virtual reality [3, 4]. 2 RECORDING AND ENCODING The acoustic laboratory of InnoRenew CoE has currently Ambisonics is a method of recording and reproducing a sound been equipped with a higher order Ambisonics system. The field and preserving its directional properties. The signal system is composed of a 32 channel microphone [2], a set of is coded, which is different in comparison with traditional 64 full range loudspeakers, a dedicated low frequency loud- multichannel audio formats (e.g., stereo, and 5.1 surround). speaker, all the required AD/DA converters and accessories, In those, each channel contains the signal corresponding to such as stands and cables. The equipment in shown on Fig- a loudspeaker while in Ambisonics each channel contains ure 1. derivatives of the pressure field. The encoded signals are The system will be used for perceptual acoustic experi- known as B format. ments, mainly by exposing test subjects to different acoustic In Ambisonics we record with several microphones spher- conditions and investigating their response. In fact, room ically arranged on a (virtual) sphere. Summing properly acoustic conditions are essential for a healthy and creative weighted signals from each microphone is equivalent to record- working environment – one of the important research topics ing with a microphone of a certain directional characteristic. at InnoRenew CoE. Another use of Ambisonics is in combi- Such processing is the basis of Ambisonics encoding [2], in nation with virtual reality systems (e.g. [7]) that can provide which case the chosen directional patterns correspond to a multi-sensoric immersion experience to users. spherical harmonic functions (see figure 2). 787 HCI-IS ’20, October 05–09, 2020, Ljubljana, Slovenia R. Prislan Figure 3: Example of a cardioid (left) and super- cardioid (right) microphone polar pattern (figure Figure 2: Polar patterns of spherical harmonics from [8]). 𝑌 𝑚 𝑛 (𝜃, 𝜙) of zero, first, second, third and fourth or- der (from top to bottom) (figure from [5]). surround) that consider fixed loudspeakers position is in- Spherical harmonic functions are grouped by their order dependence on the loudspeaker setup. In Ambisonics, the number 𝑛 and particular coefficient 𝑚 = −𝑛, ...𝑛. Mathemat- decoding from the B format takes into account the actual ically, each spherical harmonic corresponds to the angular position of the available loudspeakers, which can be arbitrary portion of the solution of the wave equation. This way it is chosen. Nevertheless, a high number of loudspeakers spatially possible to capture the whole sound filed as it can be, in fact, distributed around the listener are required to provide a full decomposed into spherical harmonic functions and precise spatial impression. ∞ 𝑛 The number of loudspeakers required is as well dependent ∑︁ ∑︁ 𝑝(𝑘, r, 𝜃, 𝜙) = 4𝜋𝑖𝑛𝑗𝑛(𝑘𝑟)𝐴𝑛,𝑚𝑌 𝑚 𝑛 (𝜃, 𝜙) (1) on the order of the system. The 𝑁 −th order requires a 𝑛=0 𝑚=−𝑛 minimum (𝑁 +1)2 loudspeakers, meaning that 9 loudspeakers where 𝜙 and 𝜃 are the azimuth and elevation, r is the spatial are required for the 2nd order, 16 for the 3rd and 25 for the coordinate and 𝑘 is the wavenumber. 4th. The general idea of a higher order Ambisonics encoding is There are several strategies for decoding the B format to to record sound with directionality patterns that correspond be reproduced on a setup of loudspeakers. The basic idea is to to polar patterns of spherical harmonics. As such, it is possible directionally filter the recorded signals by virtual microphones to encode the sound field in form of spherical harmonic pointing in the direction of each loudspeaker. decomposition factors instead of the sound pressure level at Setting the proper directionality patterns (see Fig 3) is the each microphone position. important part of the decoding process. In a regular layout, The maximum order 𝑁 at which we perform the expansion the signal emitted by a loudspeaker is the same as it would defines the order of the Ambisonic system. Each order con- be recorded by a supercardioid microphone pointing towards tains 2𝑁 + 1 channels, meaning that in total the ambisonics that direction [6]. This means almost all loudspeakers emit system of order 𝑁 has (𝑁 + 1)2 channels that have to be sound at the same time, and for a given sound source position, stored. Increasing the order to which the decomposition is loudspeakers in the opposite direction emit in opposite phase. done improves the directionality of the recording. An important limiting factor for increasing the Ambisonic 4 THE AMBISONICS SYSTEM IN USE order is the number of microphones positioned on the sphere: Ambisonics systems are an useful research tool in acoustics, the pressure is discretely sampled, which leads to artifacts, mainly because they enable to reproduce sound emitted by such as aliasing. Issues related to low frequency noise and sources together with the acoustic environment in which they several other technical limitations have been studied [3]. Gen- are located. An important example of such use are the inves- erally, increasing the number of microphones is favored, al- tigations carried out by Tapio Lokki [9] with his group who though this obviously increases the cost of the system. have been investigating perceptually relevant acoustic prop- It is important to understand that the B format encoded erties of concert halls. In their research, listeners have been signals can be as well manipulated with proper signal pro- asked about their preferences about the acoustics of different cessing. For example, the sound field can be easily rotated for concert halls in which the same orchestra was performing. As a certain angle, and it is also possible to focus to a certain an individual’s acoustic memory is strongly affected by the direction of the sound field [6]. time that has passed since each concert experience, it is re- quired for such research to migrate the listener and orchestra 3 REPRODUCING THE SOUND FILED between concert halls immediately. This can be achieved by The biggest advantage of Ambisonics over conventional mul- an Ambisonics system in which recordings can be switched tichannel spatial audio techniques (e.g. stereo, 5.1 and 7.1 by a push of a button. 788 The Fundamentals of Sound Field Reproduction Using a Higher Order Ambisonics System HCI-IS ’20, October 05–09, 2020, Ljubljana, Slovenia wearable equipment, which is a more natural condition for the user. A relevant use of Ambisonics in relation to VR is also recording the sound field using an Ambisonics microphone and reproducing it over headphones instead of an Ambisonics reproduction system composed of a high number of loudspeak- ers. In fact, the B format encoded signals can be processed for a binaural playback for any arbitrarily chosen head rotation. Recently, many commercial second order Ambisonics micro- phones containing four microphones have become available on the market together with dedicated digital audio work station plug-ins for binaural decoding. 5 ACKNOWLEDGMENTS Figure 4: Photo of a listener in the Ambisonics loud- The author gratefully acknowledges the European Commis- speakers ring at the InnoRenew CoE’s Acoustic lab. sion for funding the InnoRenew project (Grant Agreement The control over the system and perceptual response #739574) under the Horizon2020 Widespread-Teaming pro- is based on a tablet PC as an interface. gram and the Republic of Slovenia (Investment funding from the Republic of Slovenia and the European Union’s European Regional Development Funds). Currently at InnoRenew CoE, we are setting up the Am- REFERENCES bisonics system for the listener to rate different acoustic [1] Michael A Gerzon. Periphony: With-height sound reproduction. environments. The research is not limited to a specific envi- In: Journal of the Audio Engineering Society 21.1 (1973), pp. 2–10. [2] Eigenmike — mh acoustics LLC, url: ronment type, such as concert halls, but includes acoustic https://mhacoustics.com/products (visited on 16/09/2020). environments to which we are exposed on a daily basis (com- [3] F. Zotter and M. Frank: Ambisonics: A Practical 3D Audio Theory monly referred to as soundscape [12]). The recording will be for Recording, Studio Production, Sound Reinforcement, and Virtual Reality, SpringerOpen, 2019 performed on several different locations that include noisy [4] S. Sherbourne et al. 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Therefore, when using headphones in VR head tracking and real time audio processing are required. In this perspective, the use of Ambisonics advantageous as the full sound field is reproduced and the listener can freely rotate his head while localization clues are correctly perceived. Additionally, in Ambisonics the ears are free from 789 The use of eCare services among informal carers of older people and psychological outcomes of their use Kaja Smole-Orehek Vesna Dolničar Simona Hvalič-Touzery kaja.smole-orehek@fdv.uni-lj.si vesna.dolnicar@fdv.uni-lj.si simona.hvalic-touzery@fdv.uni-lj.si University of Ljubljana, Faculty of University of Ljubljana, Faculty of University of Ljubljana, Faculty of Social Sciences Social Sciences Social Sciences Ljubljana, Slovenija Ljubljana, Slovenija Ljubljana, Slovenija ABSTRACT Informal carers provide not just physical support, but also With increasing age and longevity, the need for informal social and emotional, as well as making sure that the older care will increase significantly in the coming decades. The people are safe and healthy, so informal care is very demand- use of eCare services has potential benefits in meeting some ing and dynamic [17]. Informal carers are spending a lot of informal carer’s needs. However, there is only a limited of time at the home of the care receiver and the demands understanding of the psychological outcomes of using eCare of providing care can be high, especially to those who are services for informal carers of older people. The aim of this employed. Because of caring duties, some informal carers ad- study is to identify positive and negative psychological out- dressed different issues, such as work interruptions, absences comes of the use of eCare services for employed informal and reduced productivity [3, 17, 20]. Combining employment carers of older people, and to review the psychological out- and care is a challenge to many carers and it can have an comes of the use of different functionalities of eCare ser- influence of informal carers’ physical health, social relation- vices. We have conducted a four-month intervention study ships, as well as the work situations [17]. Many are having among 22 dyads of informal carers and older people. The troubles being understood by their employers or co-workers preliminary results showed a prevalent pattern of positive and to some the career opportunities cannot be obtained outcomes of eCare services for employed informal carers. [17]. Further research is needed on the relationship between the ECare services have a potential to address those needs, use of different functionalities, psychological outcomes and such as decrease the demand on carers and stress alleviation care situations. [1, 4, 11, 17]. Many studies are studying the link between psychological outcomes and the functionalities of eCare ser- KEYWORDS vices, but these studies are very disease-specific, such as psychological outcomes, employed informal carers, telecare, dementia [2, 12, 19]. Informal carers of people with dementia ageing in place have specific needs, and these needs cannot be fully trans- ferred to the needs of informal carers providing a different 1 INTRODUCTION type of care, therefore there is a gap in understanding which The growing pressure on families to provide informal care, functionalities of eCare services can help informal carers in due to demographic aging of the population, leads to a search general to better combine work and care. In addition, many for new and innovative solutions to meet those challenges. studies examined different outcomes and models of eCare An increasing attention is being paid to the role of technology services use and acceptance among the older people [8, 15], and its potentials in supporting older people in their own living aside informal carers of older people. homes and their informal carers. However, understanding The aim of the study was to fill this gap and to identify the the psychological outcomes of the use of eCare services is positive and negative psychological outcomes of the use of limited for informal carers of older people and even more so eCare services on employed informal carers and to review the for working informal carers [1, 4, 6, 11, 14, 18]. psychological outcomes of the use of different functionalities of eCare services. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies 2 METHODS bear this notice and the full citation on the first page. Copyrights for third- Study design party components of this work must be honored. For all other uses, contact the owner/author(s). A four-month qualitative intervention study was performed in 2018 and 2019 in Central Slovenia region. In accordance Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia © 2020 Copyright held by the owner/author(s). with the aim of the study, surveys and interviews were con- ducted with employed informal carers only. The intervention 790 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Kaja Smole-Orehek, Vesna Dolničar, and Simona Hvalič-Touzery study included a dyad of an informal carer and an older per- recorded and completely transcribed. Personal information son (65+). A total of 26 dyads, including older care receivers was made anonymous. All participants received gift vouchers and their primary informal carers, were recruited. The final in recognition of their time and were not charged for their use sample included 22 dyads. of the eCare services. The study was approved by the Slove- nian Commission for Medical Ethics (0120-193/2018/15). Apparatus Older people had one of the two eCare equipment installed Analysis in their homes. Their informal carers used the mobile appli- A descriptive analysis of the quantitative data, comprising cation, which allowed them to monitor certain activities in 755 pages of transcribed interview recordings, was carried the older person’s home and receive notifications in case of out. The qualitative data were subjected to a thematic analy- unexpected event. Both services tested had motion and door sis using the programme Atlas.ti 8 for qualitative data anal- sensors, a pendant alarm, a smoke detector and a mobile ysis. A structural coding was used. This is question-based application for the carers, with alarms in the form of push code that “acts as a labelling and indexing device, allowing notifications and activity monitoring. The second service researchers to quickly access data likely to be relevant to a also offered two additional functionalities, a 24/7 call center particular analysis from larger data set” [13, 16]. Deductive and fall detection, and was used by 7 out of 22 carers. and inductive approaches were combined for data coding and analysis [7]. Participants Purposive sample was used. Eligibility criteria for informal 3 RESULTS carers were: (i) primary carers, (ii) family members of older We examined psychological outcomes of five eCare services person, (iii) providers of a long-term care to older person functionalities: motion detection on the App, Push notifica- (providing at least 5 hours of help per week and minimum 1 tions and alarms on the App, Emergency pendant, Smoke year), (iv) owned a smartphone, (v) interested in study par- detector, Call center and Fall detector. The most frequently ticipation. Care receiver’s eligibility criteria were as follows: reported positive psychological outcome was reassurance, (i) interested in study participation, (ii) old 65 years or more, followed by peace of mind and reduced anxiety. In addition, (iii) need help with activities of daily living, (iv) use also the informal carers mentioned several other positive psy- formal care, (v) live alone in their own household. chological outcomes of using eCare services, including an Informal carers ranged in age from 35 to 67 (M = 53.9, increased sense of control, less stress, the feeling of being SD = 7.56). More than half of them were female (n = 14). less burdened, having positive feelings, a feeling of relief and On average they provided 8.5 hours of care per week (SD = satisfaction (Table 1). 12.15), on average for 6.1 years (SD = 5.89). A great majority of carers were care receiver’s children (n = 20) and two were Push daughters-in-law. notifications and Sensor-based alarms on the motion detection Call centre Emergency Care receivers were on average 83 years old (SD = 6.04), app on the app assistance Fall detector pendant Total Reassurance 8 18 7 2 8 43 ranging from 73 to 92 years. All but two were females and Peace of mind 8 12 4 1 6 31 Reduced anxiety 5 12 2 0 3 22 all but one fell in the last five years, with 14 of them needed Reduced stress 3 6 1 0 1 11 medical assistance afterwards. Five of them were severely Feeling less burdened 2 4 2 0 1 9 Positive feelings 0 2 1 0 1 4 dependent, eight moderately dependent, eight slightly de- A sense of relief 0 3 0 0 0 3 Satisfaction 0 0 1 0 1 2 pendent and one needing some help only occasionally. Total 26 57 18 3 21 Table 1: Positive psychological outcomes of eCare services Procedure use on the employed informal carers During the intervention, quantitative (screening question- naire) and qualitative (semi-structured interviews) data were “Yes, yes, that gives you the feeling of reassurance that they will collected, with qualitative methodology playing a fundamen- inform you, if you are not around when he presses the button. tal role. The survey at the beginning of the intervention col- And then you go on vacation or somewhere else, as I say, even if lected basic social, health, care and demographic data. Two something would happen, you organize other family members semi-structured interviews per informal carer were then con- to make an action.” (Carer 15) ducted (the first after 3 weeks of use and the fourth month), “I will say it, if I did not reach mum over the phone call because each lasting about one hour. They were asked about their of her bad hearing, then I looked at this application and saw caregiving situation, their experience with new technology, that mom is inside doing something. If something was wrong, their use of the tested eCare services and the psychological there is also an option for an emergency pendant, which she outcomes of eCare services. The in-depth interviews were could activate, right . . . ” (Carer 6) 791 The use of eCare services among informal carers of older people ... Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia In our study, informal carers recognized that the emer- would approach to older person too technically rather than gency pendant and sensor-based motion detection are two attentively. of the most helpful functionalities of eCare services, as they “. . . I know, even when mom falls, she is always very confused. are the most common contributors to positive psychological It is much easier when she says, "daughter, I fell," opposing to outcomes. The most useful functionality for those who cared explain it to them. Well, "lady, this and that". I do not know, I for people with severe disabilities was an emergency pen- am absolutely for an option that one of the family members dant, while sensor-based motion detection was more useful has it.” (Carer 4) for those carers who cared for people with mild or moderate dependency. “It would not help much. It would not help us, because if mum The few negative psychological outcomes in our study is alone when she falls (...). I can assume that she is able to say were mostly caused by technical failure and false alarms, something on her own, maybe not, right.” (Carer 8) although some participants were less disturbed than oth- For some carers, eCare services contributed to their ability ers. The most frequently mentioned negative outcome was to be in paid employment and was useful in reconciling care anxiety, followed by distrust and stress. Other reasons for and work obligations. They mentioned that eCare services negative psychological outcomes were mentioned: feelings supported their work and increased their labor productivity of false security, invasion into older person’s privacy, feel- by making it easier for them to concentrate on their work. ings of guilt because they do not help enough, increased “Yes, I can concentrate at work. I do not have to think about worries because they know the everyday patterns of older what if ... It helps, and it relieves you, but still, if she falls, person (Table 2). and her phone is ten feet away and she cannot use it, then it’s useless ...” (Carer 9) “Hm, yes, it caused me more stress personally because I was worried, under other circumstances I would not do that. Under 4 DISCUSSION other circumstances, I would not think about whether she was still cooking or not.” (Carer 2) Our study yielded several important findings. We found that positive psychological outcomes of eCare services use for employed informal carers were much more common than Push Push Sensor-based Call centre Fall detector Emergency Total notifications and Sensor-based notifications motion assistance pendant negative ones. This finding supports the findings of previ- alarms on the motion detection Call centre Emergency and alarms on detection on app on the app assistance Fall detector pendant Total the app the app ous limited studies of informal carers [1, 9, 14]. Despite the Reassurance 8 18 7 2 8 43 Anxiety 6 3 1 0 0 10 Peace of mind 8 12 4 1 6 31 Hesitant 0 0 7 0 0 7 prevalence of positive psychological outcomes, the negative Reduced anxiety 5 12 2 0 3 22 Distrust 1 3 1 1 0 6 Reduced stress 3 6 1 0 1 11 Stress 2 2 0 0 0 4 should not be ignored. In particular studies show that unre- Feeling less burdened 2 4 2 0 1 9 Feeling burdened 1 3 0 0 0 4 Positive feelings 0 2 1 0 1 4 Lack of relief 0 1 0 0 2 3 liable and/or inappropriate technology, which in our study A sense of relief 0 3 0 0 0 3 Doubts 0 1 0 0 2 3 Satisfaction 0 0 1 0 1 2 Discomfort 0 2 0 0 0 2 was the main cause of negative psychological outcomes, can Total 26 57 18 3 21 Less peace of mind 0 2 0 0 0 2 Additional problem 1 1 0 0 0 2 be harmful to both older people and their informal carers No reduced burden 0 1 0 0 0 1 Feeling a moral obligation 0 1 0 0 0 1 [5, 10]. In addition, a difference was also observed in the Sense of guilt 0 1 0 0 0 1 perceived usefulness of individual functionalities in relation Bothered 1 0 0 0 0 1 Unpleasant feeling 1 0 0 0 0 1 to the degree of dependence. However, due to the small num- Total 13 21 9 1 4 Table 2: Negative psychological outcomes of eCare services ber of participants in different dependency groups, further use on the employed informal carers empirical and conceptual studies are needed. Our study also confirmed the complex relationship between the functional- ities of eCare services and the psychological outcomes for “Even more, because she does not want to wear this neckless, employed informal carers. then it seems to me to be useless. You do not need it for anything, We also demonstrated that reassurance was the most fre- it will not be very functional, because then it will not matter if quently identified positive psychological outcome. It was she only has a mobile phone.” (Carer 2) mainly related to sensor-based motion detection on the ap- In the present study, all call center users mentioned pos- plication, the possibility of monitoring the activities of an itive psychological outcomes in relation to it. They mostly older person from distance, e.g. to verify that he or she is felt reassured by their service. However, a few participants moving around home safely. In addition, employed informal who did not have access to the call center service felt reluc- carers reported that reassurance makes it easier for them to tant to use it because they said that they might not have go on business trips, work and concentrate on their work, as enough information about the older person to be able to they are notified in case of an emergency. From this, we can react well, that they would not feel comfortable talking to a conclude that eCare services can provide opportunities for "stranger" and that their situation was too specific for a call employed informal carers of older people to reconcile work center to be helpful. They were worried that the call center and care responsibilities. 792 Information Society 2020, 5–9 October, 2020, Ljubljana, Slovenia Kaja Smole-Orehek, Vesna Dolničar, and Simona Hvalič-Touzery This study examined under-researched aspect of eCare [3] Jill I Cameron, Rene-Louise Franche, Angela M Cheung, and Donna E use in relation to informal care of older people. The method- Stewart. 2002. Lifestyle interference and emotional distress in family ology used allowed a detailed account of the experiences of caregivers of advanced cancer patients. Cancer 94, 2 (2002), 521–527. employed informal carers’ with eCare as well as their percep- [4] Stephanie Carretero, James Stewart, and Clara Centeno. 2015. Infor- mation and communication technologies for informal carers and paid tions of it. However, there are some limitations to this study. assistants: benefits from micro-, meso-, and macro-levels. European The first is the duration of the intervention. When conduct- Journal of Ageing 12, 2 (2015), 163–173. ing an intervention study to investigate the detection and [5] Sara J Czaja. 2016. Long-term care services and support systems for vigilance of a potentially harmful event, a longer duration of older adults: The role of technology. Am Psychol 71, 4 (2016), 294. the intervention is usually advisable, but we were limited in [6] Anna Davies, Lorna Rixon, and Stanton Newman. 2013. Systematic review of the effects of telecare provided for a person with social care time and resources. In addition, the incidence of a harmful or needs on outcomes for their informal carers. Health & social care in unexpected event during the testing phase in our study was the community 21, 6 (2013), 582–597. low, so many participants had no real experience with the [7] Jennifer Fereday and Eimear Muir-Cochrane. 2006. Demonstrating support and protocols for using eCare services. Moreover, rigor using thematic analysis: A hybrid approach of inductive and one of the eCare services tested was still in the testing phase deductive coding and theme development. Int. J. Qual. Methods 5, 1 (2006), 80–92. during the intervention study, so that several false alarms [8] Jean D Hallewell Haslwanter and Geraldine Fitzpatrick. 2018. The occurred, especially at the beginning of the study. development of assistive systems to support older people: issues that affect success in practice. Technologies 6, 1 (2018), 2. [9] Nat Harward. 2016. Caregivers & technology: What they want 5 CONCLUSIONS and need. http://www.aarp.org/content/dam/aarp/home-and- Our study confirmed the potential of eCare services to ad- family/personal-technology/2016/04/Caregivers-and-Technology- dress challenges related to long-term care provision. There AARP.pdf. Accessed: 2020-09-10. are many challenges that Slovenian society needs to address [10] Helen Hawley-Hague, Elisabeth Boulton, Alex Hall, Klaus Pfeiffer, and Chris Todd. 2014. Older adults’ perceptions of technologies aimed at in order to realize the full potential of eCare technologies: falls prevention, detection or monitoring: a systematic review. Inter- (i) Public authorities must recognize the role and caring national journal of medical informatics 83, 6 (2014), 416–426. demands of informal carers and provide them with much [11] Kara Jarrold and Sue Yeandle. 2009. A weight off my mind: Exploring needed support as soon as possible. (ii) Policy makers should the impact and potential benefits of telecare for unpaid carers in promote a policy framework for the creation of eCare ser- Scotland. https://www.scie-socialcareonline.org.uk/a-weight-off- my-mind-exploring-the-impact-and-potential-benefits-of-telecare- vices for carers and beyond [19]. (iii) Affordable and accessi- for-unpaid-carers-in-scotland/r/a11G0000001825wIAA. Accessed: ble eCare services must be made available to informal carers 2010-09-30. and older people [18, 19]. At the same time, we must increase [12] Guang Ying Mo, Renée K Biss, Laurie Poole, Bianca Stern, Karen Waite, their acceptance of such technologies. Therefore, the design and Kelly J Murphy. 2020. Technology Use among Family Caregivers and usability of these technologies should be adapted and of People with Dementia. CAG/ACG (2020), 1–13. [13] Emily Namey, Greg Guest, Lucy Thairu, and Laura Johnson. 2008. personalized to the needs of informal carers [2, 18]. End users Data reduction techniques for large qualitative data sets. should therefore be involved in the test phases [5, 18]. [14] Kaja Smole Orehek, Ines Kožuh, Andraž Petrovčič, Vesna Dolničar, Matjaž Debevc, and Simona Hvalič-Touzery. 2018. Psychological out- comes of eCare technologies on informal carers of older people. IJIC ACKNOWLEDGMENTS 18 (2018). The authors acknowledge the projects (Smart ICT Solutions [15] Sebastiaan Theodorus Michaël Peek. 2017. Understanding technology for Active and Healthy Ageing: Integrating Informal eCare acceptance by older adults who are aging in place: A dynamic perspective. Services in Slovenia, ID L5-7626, Factors impacting inten- Ph.D. Dissertation. Tilburg University. tion to use smart technology enabled care services among [16] Johnny Saldaña. 2015. The coding manual for qualitative researchers. Sage. family carers of older people in the context of long-distance [17] Alice Spann, Joana Vicente, Camille Allard, Mark Hawley, Marieke care, ID J5-1785, Programme Internet research, P5-0399) were Spreeuwenberg, and Luc de Witte. 2020. Challenges of combining financially supported by the Slovenian Research Agency. work and unpaid care, and solutions: A scoping review. Health & Social Care in the Community 28, 3 (2020), 699–715. [18] Vimal Sriram, Crispin Jenkinson, and Michele Peters. 2019. Informal REFERENCES carers’ experience of assistive technology use in dementia care at [1] Stefan Andersson, Christen Erlingsson, Lennart Magnusson, and Eliz- home: a systematic review. BMC geriatrics 19, 1 (2019), 160. abeth Hanson. 2017. Information and communication technology- [19] Vimal Sriram, Crispin Jenkinson, and Michele Peters. 2020. Carers’ mediated support for working carers of older family members: an experience of using assistive technology for dementia care at home: a integrative literature review. IJCC 1, 2 (2017), 247–273. qualitative study. BMJ open 10, 3 (2020), e034460. [2] Laura Block, Andrea Gilmore-Bykovskyi, Anna Jolliff, Shannon Mullen, [20] Birgit Trukeschitz, Ulrike Schneider, Richard Mühlmann, and Ivo and Nicole E Werner. 2020. Exploring dementia family caregivers’ Ponocny. 2013. Informal eldercare and work-related strain. J GERON- everyday use and appraisal of technological supports. 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(2020). 793 794 Indeks avtorjev / Author index Adams Jennifer ........................................................................................................................................................................... 104 Ajda Centa .................................................................................................................................................................................. 173 Albreht Jaka ............................................................................................................................................................................... 433 Aleš Oblak .................................................................................................................................................................................. 166 Andova Andrejaana ........................................................................................................................................................................ 7 Andrej Bauer .............................................................................................................................................................................. 245 Anže Marinko ............................................................................................................................................................................. 158 Attygale Nuwan ......................................................................................................................................................................... 759 Babič Davorin ............................................................................................................................................................................ 438 Baggia Alenka .................................................................................................................................................................... 444, 451 Baloh Miha ......................................................................................................................................................................... 457, 462 Bevčič Mateja ............................................................................................................................................................................. 727 Bierhoff Ilse ................................................................................................................................................................................. 80 Bizjak Jani ............................................................................................................................................................ 27, 35, 39, 43, 51 Bizjak Miha .................................................................................................................................................................................. 11 Blaž Počervina ........................................................................................................................................................................... 173 Boben Dušica ............................................................................................................................................................................. 732 Bohanec Marko ............................................................................................................................................................................ 27 Bolliger Larissa ............................................................................................................................................................................ 63 Borovnik Aleksandra .................................................................................................................................................................. 466 Bosnić Zoran .......................................................................................................................................................... 76, 88, 100, 116 Bradeško Luka ........................................................................................................................................................................... 257 Brank Janez ................................................................................................................................................................................ 245 Brence Jure ................................................................................................................................................................................. 104 Breznikar Tilen ........................................................................................................................................................................... 547 Bromuri Stefano ............................................................................................................................................................................. 7 Bučar Maja ................................................................................................................................................................................. 338 Bučer Maja ................................................................................................................................................................................. 451 Budna Borut ............................................................................................................................................................................... 112 Butkovič Amanda ....................................................................................................................................................................... 451 Cadorin Lucia ............................................................................................................................................................................. 444 Carolin Gaiser ............................................................................................................................................................................ 147 Carolina Petrič ............................................................................................................................................................................ 169 Cej Rok....................................................................................................................................................................................... 779 Čerin Matej ................................................................................................................................................................................. 261 Cerkovnik Pia ............................................................................................................................................................................. 547 Cimperman Miha........................................................................................................................................................................ 257 Clays Els....................................................................................................................................................................................... 63 Čopič Pucihar Klen .................................................................................................................................................... 759, 767, 775 Darja Kobal Grum ...................................................................................................................................................................... 143 Dayana Hristova ......................................................................................................................................................................... 184 De Boer Jasmijn ........................................................................................................................................................................... 80 De Masi Carlo M. ......................................................................................................................................................................... 15 Debevc Matjaž ........................................................................................................................................................................... 771 Deja Jordan Aiko ........................................................................................................................................................................ 759 Delovec Urška ............................................................................................................................................................................ 470 Deželak Ferdinand...................................................................................................................................................................... 412 Dobrišek Simon .......................................................................................................................................................................... 783 Dojčinović Aleksandar ............................................................................................................................................................... 474 Dolanc Gregor .............................................................................................................................................................................. 27 Dolenec Rok ............................................................................................................................................................................... 321 Dolnicar Vesna ........................................................................................................................................................................... 790 Dovgan Erik ........................................................................................................................................................................... 19, 92 Drvarič Radmila ......................................................................................................................................................................... 480 Džeroski Sašo ............................................................................................................................................................................. 104 795 Eftimov Tome ............................................................................................................................................................................ 213 Ema Demšar ............................................................................................................................................................................... 125 Ema Jemec ................................................................................................................................................................................. 158 Erjavec Tomaž ................................................................................................................................................................... 197, 209 Eva Koderman ............................................................................................................................................................................ 147 Evkoski Bojan ............................................................................................................................................................................ 233 Fanedl Nina ................................................................................................................................................................................ 451 Filipič Bogdan .............................................................................................................................................................................. 19 Fink Betka .................................................................................................................................................................................. 451 FitzGerald Christine ................................................................................................................................................................... 444 Fric Urška ................................................................................................................................................................................... 331 Gabrijelčič Barbara .................................................................................................................................................................... 484 Gajšek Brigita ............................................................................................................................................................................. 451 Gams Matjaž .............................................................................................................................................................................. 272 Gams Matjaž ...................................................................................................................................... 27, 35, 39, 43, 47, 51, 55, 68 Gams Matjaž .............................................................................................................................................................................. 389 Gams Matjaž .............................................................................................................................................................................. 418 Gašper Slapničar ........................................................................................................................................................................ 176 Gazvoda Samo ....................................................................................................................................................................... 35, 43 Gjoreski Hristijan ............................................................................................................................................................. 47, 72, 84 Gjoreski Martin ............................................................................................................................................................................ 23 Globokar Roman ........................................................................................................................................................................ 281 Golob David ................................................................................................................................................................................. 27 Golob Žiga ................................................................................................................................................................................. 783 Gradišek Anton ............................................................................................................................................................................ 32 Gregor Geršak .................................................................................................................................................................... 169, 173 Grobelnik Marko ................................................................................................................................................................ 229, 245 Grušovnik Tomaž ....................................................................................................................................................................... 269 Gselman Peter ............................................................................................................................................................................ 312 Guid Matej ................................................................................................................................................................................... 11 Gulin Vesna ................................................................................................................................................................................ 488 Gültekin Várkonyi Gizem ............................................................................................................................................................ 32 Hribar Grega ............................................................................................................................................................................... 492 Hvalič Touzery Simona .............................................................................................................................................................. 790 Istenič Tanja ....................................................................................................................................................................... 400, 408 Jacobs Tobias ............................................................................................................................................................................. 257 Jakop Sara .................................................................................................................................................................................. 732 Jan Babič .................................................................................................................................................................................... 169 Janez Bregant ............................................................................................................................................................................. 188 Jani Toroš ................................................................................................................................................................................... 138 Jaya Caporusso ........................................................................................................................................................................... 125 Jelenčič Jakob ............................................................................................................................................................................. 253 Jeram Bojan ................................................................................................................................................................................ 495 Jereb Eva .................................................................................................................................................................................... 707 Jereb Robert ............................................................................................................................................................................... 499 Jerin Matija ................................................................................................................................................................................. 547 Jernej Čamernik.......................................................................................................................................................................... 169 Jevšnik Barbara .......................................................................................................................................................................... 503 Jordan Marko ............................................................................................................................................................................... 80 Jos van der Geest ........................................................................................................................................................................ 147 Jovanovska Lidija ....................................................................................................................................................................... 237 Jurač Vesna ................................................................................................................................................................................ 507 Kalabakov Stefan ............................................................................................................................................................. 27, 35, 51 Karanjac Blanka ......................................................................................................................................................................... 511 Karin Kasesnik ........................................................................................................................................................................... 138 Katarina Marjanovič ................................................................................................................................................................... 162 Katrašnik Marko ........................................................................................................................................................................... 63 Kenda Klemen .................................................................................................................................................................... 249, 261 Khvorostyanaya Anna Sergeevna............................................................................................................................................... 335 Kiprijanovska Ivana ......................................................................................................................................................... 39, 43, 47 796 Klampfer Viktor ......................................................................................................................................................................... 515 Klara Golob ................................................................................................................................................................................ 158 Kljun Matjaž ............................................................................................................................................................... 759, 767, 775 Knez Jožica ................................................................................................................................................................................ 518 Kobe Spomenka ......................................................................................................................................................................... 317 Kocuvan Primož ............................................................................................................................................................... 27, 35, 51 Kokelj Martina ........................................................................................................................................................................... 522 Kolenc Metka ............................................................................................................................................................................. 525 Kolenik Tine ................................................................................................................................................................................. 55 Kolidžić Jovana .......................................................................................................................................................................... 451 Kolmanič Simon ......................................................................................................................................................................... 763 Korošec Tamara ......................................................................................................................................................................... 312 Koroušič Seljak Barbara ............................................................................................................................................................. 213 Korun Blažka ............................................................................................................................................................................. 732 Košak Babuder Milena ............................................................................................................................................................... 732 Kosem Goran ............................................................................................................................................................................. 530 Kotnik Klaužer Lidija ................................................................................................................................................................. 534 Kozole Blaž ................................................................................................................................................................................ 312 Kožuh Ines ................................................................................................................................................................................. 771 Krajnc Mitja ............................................................................................................................................................................... 312 Kralj Novak Petra ....................................................................................................................................................................... 233 Kupec Lucija ...................................................................................................................................................................... 537, 541 Kurbašić Azur ............................................................................................................................................................................ 257 Kušar Luka ................................................................................................................................................................................. 544 Kuzmanovski Vladimir ................................................................................................................................................................ 23 Lambić Ana ................................................................................................................................................................................ 547 Lauko Lina ................................................................................................................................................................................. 547 Lavrač Nada ............................................................................................................................................................................... 205 Leben Jazbec Sanja .................................................................................................................................................................... 552 Lenart Gregor ............................................................................................................................................................................. 630 Leskovar Kristina ....................................................................................................................................................................... 555 Leskovar Robert ......................................................................................................................................................................... 444 Leštan Domen ............................................................................................................................................................................ 404 Levstek Andraž ............................................................................................................................................................................ 59 Lillo-Crespo Manuel .................................................................................................................................................................. 444 Lipnik Aleš ................................................................................................................................................................................. 338 Ljubešić Nikola .......................................................................................................................................................................... 233 Lochrie Mark .............................................................................................................................................................................. 775 Lokar Matija ....................................................................................................................................................................... 558, 564 Luka Stopar ................................................................................................................................................................................ 245 Lukač Niko ................................................................................................................................................................................. 763 Lukan Junoš ................................................................................................................................................................................. 63 Luštrek Mitja .................................................................................................................................................... 7, 15, 63, 80, 92, 96 Maarten Frens ............................................................................................................................................................................. 147 Machidon Alina .................................................................................................................................................................... 68, 418 Malačič Janez ............................................................................................................................................................................. 422 Malina Edward ........................................................................................................................................................................... 104 Malovič Janez ............................................................................................................................................................................. 570 Marolt Marjeta ........................................................................................................................................................................... 630 Martinovic Andrej ...................................................................................................................................................................... 743 Massri M.Besher ................................................................................................................................................................ 217, 245 Mastnak Adrijana ....................................................................................................................................................................... 451 Matej Perovnik ........................................................................................................................................................................... 162 Matjaž Gams ...................................................................................................................................................................... 158, 176 Mazgan Lidija ............................................................................................................................................................................ 574 Medved Tilen ............................................................................................................................................................................. 547 Mihael Kline ............................................................................................................................................................................... 138 Mileva Boshkoska Mileva .......................................................................................................................................................... 241 Minić Miroslava ......................................................................................................................................................................... 579 Mitja Luštrek .............................................................................................................................................................................. 176 797 Mladenić Dunja .......................................................................................................................... 197, 201, 209, 213, 217, 225, 229 Mladenić Grobelnik Adrian........................................................................................................................................................ 229 Mlakar Miha ....................................................................................................................................................................... 112, 751 Mlakar Saša ................................................................................................................................................................................ 444 Močnik Alenka ........................................................................................................................................................................... 525 Mozetič Igor ............................................................................................................................................................................... 233 Mrak Matej ................................................................................................................................................................................. 321 Mrak Nataša ............................................................................................................................................................................... 584 Mrkela Vesna ............................................................................................................................................................................. 589 Mujkić Maja ....................................................................................................................................................................... 558, 564 Narduzzi Barbara........................................................................................................................................................................ 444 Neceva Marija .............................................................................................................................................................................. 72 Nenadović Gaja .......................................................................................................................................................................... 732 Neža Marija Slosar ..................................................................................................................................................................... 180 Nina Demšar ............................................................................................................................................................................... 130 Novak Erik ................................................................................................................................................................................. 221 Ograjenšek Irena ........................................................................................................................................................................ 400 Ogrin Alenka .............................................................................................................................................................................. 396 Ogrin Tomaž .............................................................................................................................................................................. 412 Opravž Ostrelič Lea ................................................................................................................................................................... 593 Osipov Evgeny ..................................................................................................................................................................... 76, 100 Osredkar Mari Jože .................................................................................................................................................................... 276 Ovčar Silvestar ........................................................................................................................................................................... 598 Pajnik Tina ................................................................................................................................................................................. 602 Pal Levin .................................................................................................................................................................... 303, 341, 680 Panov Panče ....................................................................................................................................................................... 237, 241 Paradiž Alan ............................................................................................................................................................................... 607 Pejović Veljko ............................................................................................................................................................................ 743 Peruš Andreja ............................................................................................................................................................................. 611 Pesjak Katja ................................................................................................................................................................................ 444 Pestotnik Rok ............................................................................................................................................................................. 321 Pestotnik Stres Svit............................................................................................................................................................. 348, 614 Peterka Ana .................................................................................................................................................................................. 76 Peternelj Jože ............................................................................................................................................................................. 249 Petrovčič Janko ............................................................................................................................................................................ 27 Petrželková Nela ........................................................................................................................................................................ 205 Pirc Anja..................................................................................................................................................................................... 620 Pita Costa Joao ........................................................................................................................................................................... 245 Pivec Franci ................................................................................................................................................................................ 270 Plankelj Marko ........................................................................................................................................................................... 763 Počkar Žan ................................................................................................................................................................................. 418 Podgorelec Mateja ...................................................................................................................................................................... 451 Podlogar Mateja ......................................................................................................................................................................... 451 Podmiljšak Benjamin ................................................................................................................................................................. 317 Podobnik Metka ......................................................................................................................................................................... 547 Polner Nikita .............................................................................................................................................................................. 547 Popovski Gorjan ......................................................................................................................................................................... 213 Praprotnik Žaucer Tatjana .......................................................................................................................................................... 625 Prelog Martin ............................................................................................................................................................................. 474 Primc Gregor .............................................................................................................................................................................. 312 Prislan Rok ................................................................................................................................................................................. 787 Pucihar Andreja .......................................................................................................................................................................... 630 Purg Peter ................................................................................................................................................................................... 634 Rajher Polona ............................................................................................................................................................................. 638 Rajkovič Uroš ..................................................................................................................................................................... 444, 474 Ramšak Špela ............................................................................................................................................................................. 547 Ravničan Jože ............................................................................................................................................................................... 27 Rebec Suzana ............................................................................................................................................................................. 642 Recek Nina ................................................................................................................................................................................. 312 Rehberger Roman ............................................................................................................................................................... 647, 653 798 Reščič Nina .................................................................................................................................................................................. 80 Riquelme Galindo Jorge ............................................................................................................................................................. 444 Rizvić Selma .............................................................................................................................................................................. 763 Robida Maruša ........................................................................................................................................................................... 659 Roglej Peter ................................................................................................................................................................................ 767 Romih Miro ................................................................................................................................................................................ 755 Rudel Drago ............................................................................................................................................................................... 393 Rugelj Jože ................................................................................................................................................................................. 727 Rupnik Maja ............................................................................................................................................................................... 312 Šabec Ana................................................................................................................................................................................... 547 Samar Brenčič Neja .................................................................................................................................................................... 393 Sambt Jože ......................................................................................................................................................................... 400, 408 Samida Cerk Simona .................................................................................................................................................................. 663 Sara Jakša ................................................................................................................................................................................... 134 Scarsini Sara ............................................................................................................................................................................... 444 Schlamberger Niko ..................................................................................................................................................................... 285 Šebjanič Oražem Maja ............................................................................................................................................................... 686 Šef Tomaž .................................................................................................................................................................................. 755 Seljak Andrej .............................................................................................................................................................................. 321 Shrikanth Kulashekhar ............................................................................................................................................................... 151 Shulajkovska Miljana ................................................................................................................................................................... 84 Silan Darja .................................................................................................................................................................................... 59 Silovšek Saša .............................................................................................................................................................................. 667 Simon Šalomon .......................................................................................................................................................................... 184 Simončič Žiga .............................................................................................................................................................................. 88 Šircelj Beno ................................................................................................................................................................................ 249 Sittar Abdul ................................................................................................................................................................................ 197 Škrlj Blaž .................................................................................................................................................................................... 205 Škrlj Peter ................................................................................................................................................................................... 775 Skumavc Nuša .................................................................................................................................................................... 671, 676 Slapničar Gašper .......................................................................................................................................................................... 92 Slodnjak Valentina ..................................................................................................................................................................... 451 Smerkol Maj ................................................................................................................................................................. 68, 112, 418 Šmitek Branislav ........................................................................................................................................................................ 444 Smole Orehek Kaja .................................................................................................................................................................... 790 Solina Franc ............................................................................................................................................................................... 779 Sotlar Gregor .............................................................................................................................................................................. 767 Stankoski Simon ........................................................................................................................................................................... 96 Stanković Erika .......................................................................................................................................................................... 732 Štarkl Ema .................................................................................................................................................................................. 732 Štepec Dejan ............................................................................................................................................................................... 108 Stoilkovska Emilija ...................................................................................................................................................................... 72 Stopar Luka ................................................................................................................................................................................ 257 Štrancar Janez ............................................................................................................................................................................. 326 Štravs Miha ................................................................................................................................................................................ 751 Stres Špela .................................................................................................................................................................. 303, 326, 680 Strgar Sonja ................................................................................................................................................................................ 602 Stropnik Vid ............................................................................................................................................................................... 100 Šturm Sašo ................................................................................................................................................................................. 317 Šuštaršič Urška ........................................................................................................................................................................... 690 Svetelšek Ajda ............................................................................................................................................................................ 396 Swati ................................................................................................................................................................................... 209, 225 Szlupowicz Michał Artur ........................................................................................................................................................... 104 Tadej Todorović ......................................................................................................................................................................... 188 Tine Kolenik ............................................................................................................................................................................... 176 Tomić Marina ............................................................................................................................................................................. 696 Tomić Starc Nina ....................................................................................................................................................................... 331 Tomše Tomaž ............................................................................................................................................................................. 317 Tonić Aleksandar ....................................................................................................................................................................... 700 Tušar Tea .................................................................................................................................................................................... 747 799 800 Indeks avtorjev nerecenziranih prispevkov v dodatku conference 13. ITTC / Index of authors of unreviewed contributions in the appendix of 13 ITTC conference Blatnik Robert .................................................................................................................................................... 363, 365, 368, 384 Bohre Ashish .............................................................................................................................................................................. 373 Cmok Luka ................................................................................................................................................................................. 375 Dobnik David ............................................................................................................................................................................. 374 Dular Matevž .............................................................................................................................................................................. 374 Filipić Arijana ............................................................................................................................................................................ 374 Grilc Miha .................................................................................................................................................................................. 373 Gutierrez Aguirre Ion ................................................................................................................................................................. 374 Justin Tomaž ...................................................................................................................................................................... 363, 365 Kosec Gregor ............................................................................................................................................................................. 372 Likozar Blaž ....................................................................................................................................................................... 373, 376 Merše Stane ................................................................................................................................................................................ 376 Mozetič Miran ............................................................................................................................................................................ 374 Ocepek Martin ............................................................................................................................................................................ 373 Osterman Natan .......................................................................................................................................................................... 375 Petelin Andrej ............................................................................................................................................................................. 375 Petkovšek Martin........................................................................................................................................................................ 374 Pitako Miha ........................................................................................................................................................................ 363, 365 Primc Gregor .............................................................................................................................................................................. 374 Škapin Srečo ............................................................................................................................................................................... 371 Slak Jure ..................................................................................................................................................................................... 372 Snoj Luka ................................................................................................................................................................................... 376 Steinbücher Miha ....................................................................................................................................................................... 373 Suvorov Danilo .......................................................................................................................................................................... 371 Trkov Andrej .............................................................................................................................................................................. 376 Trobec Marjeta ........................................................................................................................................................................... 384 van Elteren Johannes T. ............................................................................................................................................................. 376 Venturini Peter ........................................................................................................................................................................... 373 Vukomanović Marija .................................................................................................................................................................. 371 Zaplotnik Rok ............................................................................................................................................................................. 374 801 Slovenska konferenca o umetni inteligenci Slovenian Conference on Artificial Intelligence Kognitivna znanost Cognitive Science Odkrivanje znanja in podatkovna skladišča - SiKDD Data Mining and Data Warehouses - SiKDD Etika in stroka IS Professional Ethics 13. Mednarodna konferenca o prenosu tehnologij – 13. ITTC 13th International Technology Transfer Conference – 13 ITTC Ljudje in okolje 20 People and Environment Vzgoja in izobraževanje v informacijski družbi Education in Information Society 20 Interakcija človek-računalnik v informacijski družbi Human-Computer Interaction in Information Society Mitja Luštrek, Matjaž Gams, Rok Piltaver, Toma Strle, Jaša Černe, Olga Markič, Dunja Mladenić, Marko Grobelnik, Franci Pivec, Marjan Krisper, Špela Stres, Robert Blatnik, Janez Malačič, Tomaž Ogrin, Uroš Rajkovič, Borut Batagelj, Veljko Pejović, Matjaž Kljun, Vida Groznik, Domen Šoberl, Klen Čopič Pucihar, Bojan Blažica, Jure Žabkar, Matevž Pesek, Jože Guna, Simon Kolmanič Document Outline 02 - Naslovnica - notranja - All 03 - Kolofon - All 04, 05 - IS2020 - Predgovor & Odbori 07 - Kazalo - All IS2020_Volume_A - SLAIS 02 - Naslovnica - notranja - A - TEMP 03 - Kolofon - A - TEMP 04 - IS2020 - Predgovor 05 - IS2020 - Konferencni odbori 07 - Kazalo - A 08 - Naslovnica - podkonferenca - A 09 - Predgovor podkonference - A 10 - Programski odbor podkonference - A 01 - IS2020-3 Abstract 1 Introduction 2 Related Work 3 Dataset 4 Methodology 4.1 Baseline Model 4.2 DeepSpeech Model 4.3 Transfer Learning Using DeepSpeech 5 Results 6 Conclusion 7 Acknowledgments 02 - IS2020_Chess_Motifs Abstract 1 Introduction 1.1 Related Work 2 Domain Description 3 Similarity Computation 3.1 Static Features 3.2 Dynamic Features 4 Experimental Results 4.1 Evaluation of Similarity Detection 4.2 Similar Position Retrieval 5 Conclusions 03 - DeMasiLustrek-2 Abstract 1 Introduction 1.1 Video Activity Recognition 2 System Architecture 2.1 User Localization And Interaction With the Environment 2.2 Drinking Vessel Position Detection 2.3 Clip Recording and Activity Recognition 3 Results and discussion 3.1 User Localization - Results 3.2 Drinking Vessel Position Detection - Results 3.3 Activity Recognition - Results 4 Conclusions 04 - plamtex-is2020-1 Abstract 1 Introduction 2 Predicting Operation Durations with AI Methods 2.1 Relevant Positions and Related Operations 2.2 Description of the Extracted Features 2.3 Semantic Feature Selection 3 Experiments and Results 4 Conclusion Acknowledgments 05 - Gjoreski_DEXi_Alternatives_IS2020_revised 06 - Paper_David_revised_fixed 07 - GDPR-Gizem-Anton 08 - Paper_IS___Revised-2 Abstract 1 Introduction 2 Problem definition 2.1 Data 3 Method 3.1 Segmentation 3.2 Augmentation 3.3 Deep Transfer Learning 4 Evaluation 4.1 Experimental Setup 4.2 Evaluation Metric 5 Results and discussion 6 Conclusion and future work Acknowledgments 09 - Fall_detection_IS_paper_1_v3 10 - Machine_vision_IS_paper_2_v2 11 - Gait_abnormalities_IS_paper_3_v3 12 - Napovedovanje_obrabe_posnemalnih_igel_v3 Abstract 1 Uvod 2 Definicija problema 3 Reševanje problema 4 Rezultati 5 Zaključek Acknowledgments 13 - Povečevanje-enakosti-s-prepričljivo-tehnologijo_Kolenik_Gams_V2 14 - levstek_is20 Abstract 1 Uvod 2 Podatki 3 Metodologija 4 Rezultati 5 Diskusija 6 Zaključek 15 - STRAWapp Abstract 1 Application Overview 1.1 Data Types 2 Ecological Momentary Assessment 2.1 EMA Triggering 2.2 Question Database 3 Privacy Enhancements 4 Server Application 5 Client-Server Communication and Login 6 Conclusion Acknowledgments 16 - Urbanite_IS2020_revised_2 Abstract 1 Introduction 2 System's architecture 2.1 Data Analysis Module 2.2 Recommendation Engine 2.3 Policy Simulation and Validation Engine 2.4 Advanced Visualization Methods 3 Data Sources 4 Conclusions Acknowledgments 17 - Towards-end-to-end-text-to-speech-synthesis-in-Macedonian-language-3 18 - Peterka-mammogram-r1-v2 19 - Nutrition_monitoring_IS2020_v1 Abstract 1 Introduction 2 Method 2.1 Method Overview 2.2 FFQ - Qualitative Monitoring 2.3 Quantitative Monitoring 3 Results 3.1 Bite Counting 3.2 Application Implementation 4 Conclusion 5 Acknowledgments 20 - Paper_IS 21 - Simoncic-Bosnic-Sistem-za-ocenjevanje-esejev-v6.1 Abstract 1 Uvod 2 Sorodna dela 3 Opis implementacije in metode 3.1 Uporabljena orodja 3.2 Implementacija gradnikov v Orange 3.3 Semantična analiza 3.4 Rezultati 4 Zaključek 22 - slapnicar_dovgan_valic_lustrek_Mental_State_Estimation_of_People_with_PIMD_using_Physiological_Signals Abstract 1 Introduction 2 Related Work 3 Data 3.1 Annotating the ground truth 4 Methodology of mental state estimation 4.1 Using rPPG Reconstruction 4.2 Using Empatica PPG 5 Experiments and Results 5.1 Using Empatica PPG 5.2 Using rPPG reconstruction 6 Conclusion Acknowledgments 23 - SimonStankoski_IS-1 24 - Stropnik-Bosnic-v2.2 25 - IS2020_Surrogates_v2 Abstract 1 Introduction 2 Dataset 3 Surrogate Models 3.1 Dimensionality Reduction 3.2 Prediction Models 4 Experiment 4.1 Visualization 4.2 Feature Importance 4.3 Regression 5 Discussion and further work 6 Acknowledgements 26 - PASD_IS_paper_2020_final Abstract 1 Introduction 2 Related Work 3 CheXpert: A Large Chest Radiograph Dataset 3.1 Methods 3.2 End-To-End Deep Learning 3.3 Predictive Clustering Trees 4 Results 5 Conclusion Acknowledgments 27 - SIRA-Mlakar-corrected Abstract 1 Introduction 2 SIRA Architecture 3 SIRA Functionality 3.1 Processing 3.2 Search 3.3 Logging 4 Discussion and Conclusion Acknowledgments 28 - Adaptation_of_Text_to_Publication_Type-2.0 Abstract 1 Introduction 2 Related work 3 Adaptation of text 4 Evaluation and results 5 Conclusion 12 - Index - A-2 Blank Page Blank Page Blank Page Blank Page Blank Page 12 - Napovedovanje_obrabe_posnemalnih_igel_final.pdf Abstract 1 Uvod 2 Definicija problema 3 Reševanje problema 4 Rezultati 5 Zaključek Acknowledgments Blank Page IS2020_Volume_B - Kognitivna znanost 02 - Naslovnica - notranja - B - TEMP 03 - Kolofon - B - TEMP 04, 05 - IS2020 - Predgovor & Odbori 07 - Kazalo - B 08 - Naslovnica podkonference - B 09 - Predgovor podkonference - B 10 - Programski odbor podkonference - B 01 - Caporusso & Demsar_Phenomenology of dissolution experiences An exploratory study 02 - Demšar_Primerjava rezultatov analize funkcijske magnetne resonance z različnimi programskimi orodji 03 - Jakša_What anime to watch next The effect of personality on anime genre selection Abstract 1 Introduction 1.1 Personality 1.2 Entertainment preferences 2 Methodology 3 Results 3.1 Analysis of Review Presence 3.2 Analysis of Review Scores 4 Discussion A Online Resources 04 - Kasesnik et al_Zaznavanje lastnosti zdravil brez recepta 05 - Kobal Grum_Kognitivno–motivacijski model čustvovanja v vsakdanjem življenju 06 - Koderman et al_Motor learning and cortical plasticity TMS motor mapping using the pseudorandom walk method 07 - Kulashekhar_Chronotopic maps in temporal processing and perception 08 - Lipič_Being in brackets A first-person exploration of the phenomenological method of epoché 09 - Marinko et al_A new study of expected human longevity Abstract 1 Introduction 2 Related work 3 Estimating the longevity of human civilization with four basic models 3.1 Model 1 3.2 Model 2 3.3 Model 3 3.4 Model 4 4 Experiments 4.1 Single Models 4.2 All Models Merged 4.3 Results 5 Conclusion and discussion Acknowledgments 10 - Marjanovič & Perovnik_Does sight provide insight into Alzheimer’s dementia Abstract 1 Introduction 2 Diagnosis of dementia 3 Vison impairments in Alzheimer’s dementia 3.1 Eye movements and their alterations in AD 4 Conclusion 11 - Oblak_Patterns of mental behavior during psychological task 12 - Petrič et al_Vpliv posturalnih perturbacij na stresni odziv pri človeku 13 - Počervina_Facial skin temperature during deception 14 - Slapničar et al_Cognitive, psychological and social influence on spread of COVID-19 Abstract 1 Introduction 2 Related Work 3 Research hypotheses 4 Data 4.1 Features on social psychology 4.2 Virus spread classes 5 Methodology 5.1 Feature group importance 5.2 Individual feature importance 6 Experiments and Results 7 Conclusion Acknowledgments 15 - Slosar_Od orodja do umetnika 16 - Šalomon & Hristova_Social media use & digital stress among adolescents 17 - Todorović & Bregant_Special sciences Still not reducible after all these years 12 - Index - B Blank Page Blank Page Blank Page Blank Page 03 - Jakša_What anime to watch next The effect of personality on anime genre selection.pdf Abstract 1 Introduction 1.1 Personality 1.2 Entertainment preferences 2 Methodology 3 Results 3.1 Analysis of Review Presence 3.2 Analysis of Review Scores 4 Discussion A Online Resources Blank Page IS2020_Volume_C - SiKDD 02 - Naslovnica - notranja - C - TEMP 03 - Kolofon - C - TEMP 04, 05 - IS2020 - Predgovor & Odbori 07 - Kazalo - C 08 - Naslovnica - podkonferenca - C 09 - Predgovor podkonference - C 10 - Programski odbor podkonference - C 01 - A-Dataset-for-Information-Spreading-over-the-News Abstract 1 Introduction 2 Related Work 3 Data collection methodology 4 Semantic similarity between news articles 4.1 Dataset annotations 4.2 Evaluation of dataset 5 Conclusions 6 Acknowledgements 02 - Zajec_SiKDD Abstract 1 Introduction 2 Methodology 2.1 Problem Definition 2.2 Overview of the proposed method 2.3 Representing the entities 2.4 Selecting the topics 2.5 Using multiple languages 2.6 Assigning pseudo labels 3 Experiments 3.1 Dataset 3.2 Evaluation Settings 3.3 Results and discussion 4 Conclusion and future work Acknowledgments 03 - Knowledge_graph_aware_text_classification__SiKDD_-6 Abstract 1 Introduction 2 Background and related work 3 Knowledge graph-based semantic feature construction 3.1 Feature selection 3.2 Microsoft Concept Graph 3.3 Proposed approach extending tax2vec 4 Experiments and results 4.1 Data sets 4.2 Results 5 Conclusion Acknowledgments 04 - swati_eve_out Abstract 1 Introduction 1.1 Contributions 2 Dataset 2.1 Data Source 2.2 Data Generation Process 3 Availability 3.1 Reusability 4 Potential Use Cases 4.1 Examine Event-Selection Bias 4.2 Outlet Prediction 5 Statistics and Analysis 6 Related Work 7 Conclusions and Future Work Acknowledgments 05 - Ontology_alignment_using_Named_Entity_Recognition_methods_in_the_domain_of_food-1 Introduction Related work Hansard corpus FoodIE Wikifier Data Ontology alignment Evaluation and experimental setup Match types Evaluation metrics Results and discussion Conclusion and future work 06 - Extracting-structured-metadata-from-multilingual-textual-descriptions-in-the-domain-of-silk-heritage Abstract 1 Introduction 2 Description of Data 3 Methodology 3.1 Annotating datasets with slot values 3.2 Binary Classification Tasks 3.3 Multi-class Classification Tasks 4 Results 4.1 Experimental Datasets 4.2 Binary Classification Tasks 4.3 Multi Class Classification Class 5 Conclusion and Future Work Acknowledgments 07 - SiKDD2020__Hierarchical_Classification_of_Educational_Resources-1 Abstract 1 Introduction 2 Related Work 3 Data Set 4 Methodologies 4.1 Feature Extraction 4.2 Multi-class SVM Classifier 4.3 Lecture Weights 5 Evaluation 5.1 Parameters and Specifications 5.2 Results 6 Discussion 7 Future Work 8 Conclusion Acknowledgments References 08 - swati_outlet_prediction Abstract 1 Introduction 1.1 contributions 1.2 Problem Statement 2 Literature Review 3 Data Description 3.1 Raw Data Source 3.2 Dataset 4 Materials and Methods 4.1 Problem Modeling 4.2 Methodology 5 Experimental Evaluation 5.1 Baselines 5.2 Evaluation Metric 5.3 Results and Analysis 6 Conclusions and Future Work Acknowledgments 09 - MultiCOMET-FINAL-2 10 - A_Slovenian_Retweet_Network_2018_2020 11 - Semantic_annotation_of_food_and_nutrition_data__SiKDD_2020_-final Abstract 1 Introduction 2 Background 3 Critical overview of food and nutrition semantic resources 4 Proposal 5 Conclusion Acknowledgments 12 - 23nd_international_multiconference___Information_Society_2020-1 Abstract 1 Introduction 2 Data 2.1 MojeUre system 2.2 Data prepossessing and feature engineering 3 Data analysis scenarios and experiments 4 Results and discussion 5 Conclusion and Future Work Acknowledgments 13 - Monitoring-COVID-19-through-text-mining-and-visualization Abstract 1 Introduction 2 Related work 3 Description of Data 3.1 Historical COVID-19 Data 3.2 Live Data from Worldometer 3.3 Live News about Coronavirus 3.4 Google COVID-19 Community Mobility Data 3.5 MEDLINE: Medical Research Open Dataset 4 CORONAVIRUS WATCH DASHBOARD 4.1 Coronavirus Data Table 4.2 Coronavirus Live News 4.3 Statistical Visualizations 4.4 Time Gap 4.5 Mobility 4.6 Social Distancing Simulator 4.7 Biomedical Research Explorer 5 Conclusion and Future Work Acknowledgments 14 - PRAZEN _ TREBA ZAMENJATI Abstract 1 Introduction 2 Data 2.1 MojeUre system 2.2 Data prepossessing and feature engineering 3 Data analysis scenarios and experiments 4 Results and discussion 5 Conclusion and Future Work Acknowledgments Blank Page Blank Page Blank Page Blank Page 15 - skidd Introduction Data description Tweets processing Deep learning models Analysis of underlying embedding matrix Conclusion Acknowledgments References 16 - SIKDDCogLo_2020_Final_V2_22_09_2020 17 - SI_KDD_2020__Amazon-forest-fire-detection-with-an-active-learning-approach Introduction Data Data Acquisition Data Preprocessing Methodology Experiment 1 Experiment 2 Results Conclusions Acknowledgments 12 - Index - C Blank Page Blank Page Blank Page 14 - SI_KDD_2020___Usage_of_Incremental_Learning_in_Land_Cover_Classification.pdf Introduction Data EO data LULC data Feature Engineering Methodology Results Conclusions Acknowledgments References Blank Page IS2020_Volume_D - Etika in stroka 02 - Naslovnica - notranja - D - TEMP 03 - Kolofon - D - TEMP 04, 05 - IS2020 - Predgovor & Odbori 07 - Kazalo - D 08 - Naslovnica podkonference - D 09 - Predgovor podkonference - D 10 - Programski odbor podkonference - D 01 - povzetek grusovnik etika in stroka POPRAVLJENO 02 - IS Berleur LIBRE pisava POPRAVLJENO 03 - etika gams IS 4 POPRAVLJENO 04 - etika-Osredkar POPRAVLJENO 05 - IJS_Globokar_Vloga-religij-pri-oblikovanju-globalne-etike POPRAVLJENO 06 - Etika in informatika (Repaired) POPRAVLJENO 12 - Index - D Blank Page Blank Page Blank Page Blank Page Blank Page IS2020_Volume_E - ITTC Naslovnica-sprednja-E 02 - Naslovnica - notranja - E 03 - Kolofon - E 04, 05 - IS2020 - Predgovor & Odbori 07 - Kazalo - E 08 - Naslovnica podkonference - E 09 - Predgovor podkonference - E 10 - Programski odbor podkonference - E 01 - A decade of knowledge transfer in Slovenia_StresPal_final_PDF 02 - Patents on plasma treatments in agriculture_PrimcRecekPDF 03 - Rare Earth-based Permanent Magnets_Zuzek_A4_PDF 04 - Real-time fluorescence lifetime acquisition system_Pestotnik_PDF 05 - Regulated toxicity-testing_Strancar_PDF 06 - Status quo of computer-implemented inventions in Slovenia and EU_Fric_PDF 07 - Strategic intellectual property management system_KhvorostyanAnna_PDF 08 - Strategic research and innovation partnerships_BucarLipnik_PDF 09 - The awareness on environmental protection issues_Pal_PDF 10 - Transfer of knowledge and skills in STEM_Pestotnik Stres_PDF 11_A - Dodatek - E 12 - Index - E 12 - Index - Dodatek - E Blank Page Blank Page Blank Page Blank Page Blank Page Blank Page Blank Page IS2020_Volume_F - Ljudje in okolje 02 - Naslovnica - notranja - F - TEMP 03 - Kolofon - F - TEMP 04, 05 - IS2020 - Predgovor & Odbori 07 - Kazalo - F 08 - Naslovnica podkonference - F 09 - Predgovor podkonference - F 10 - Programski odbor podkonference - F 01 - Demography Gams5 POPRAVLJENO 02 - IJS-2020-Samar-Brencic-Standardi-kakovosti-storitev-zdravja-na-daljavo-za-starejse-odrasle POPRAVLJENO 03 - IS2020-Ogrin-Svetelsek POPRAVLJENO 04 - IstenicOgrajensekSambt_IJS2020_final POPRAVLJENO 05 - Lestan, Soil remediation using ReSoil POPRAVLJENO 06 - SambtIstenic_IJS2020 POPRAVLJENO 07 - IS2020-Ogrin_Dezelak_VE_4_fin POPRAVLJENO 08 - Traffic_Sim_in_the_Context_of_Mobility_Policy_Support POPRAVLJENO Abstract 1 Introduction 2 Traffic simulation 3 Simulation software packages 3.1 Evaluated software packages 3.2 Reasons for simulating traffic 3.3 Evaluation results 4 Discussion Acknowledgments 09 - KAKO SO PREDVIDEVALE RAZVOJ PREBIVALSTVA SLOVENIJE TRI IZBRANE PROJEKCIJE_IJS_2020_Malacic_stolpci POPRAVLJENO 12 - Index - F Blank Page Blank Page Blank Page Blank Page Blank Page IS2020_Volume_G - VIVID 02 - Naslovnica - notranja - G - TEMP 03 - Kolofon - G - TEMP 04, 05 - IS2020 - Predgovor & Odbori 07 - Kazalo - G 08 - Naslovnica podkonference - G 09 - Predgovor podkonference - G 10 - Programski odbor podkonference - G Zbornik VIVID 2020 - prispevki 1 UVOD 2 METODA DELA 2.1 Izpeljava učne situacije 2.2 Pedagoško-didaktične ustreznosti učne situacije 2.3 Kreativno kodiranje v konceptu splošne medijske umetnosti 2.4 Programski jezik p5.js ter spletni učni okolji editor.p5js in peblio.co 3 REZULTATI IMPLEMENTACIJE POVEZOVALNIH KONCEPTOV 4 ZAKLJUČEK VIRI 1 UVOD 2 E-IZOBRAŽEVANJE 2.1 Skupnost praks 2.2 Bralni klub 2.3 MOOC 2,4 Interaktivne vsebine 2.5 Igrifikacija 3 METODOLOGIJA 4 PRIMERI NA DOKAZIH PODPRTEGA UČENJA ZDRAVSTVENE NEGE 4.1 Videokonferenčni sistem BBB 4.2 Skupnost praks 4.3 Bralni klub 4.4 MOOC 4.5 Interaktivne vsebine 5 ZAKLJUČEK ZAHVALA LITERATURA IN VIRI 1 UVOD 2 METODOLOGIJA 2.1 Analiza obstoječega stanja izobraževanja o standardih GS1 2.2 Izdelava prototipa spletne učilnice 3 INOVATIVNI PRISTOPI V IZOBRAŽEVANJU 3.1 Mobilne aplikacije 3.2 Virtualna resničnost 3.3 Igrifikacija 3.4 E-učilnica 4 PROTOTIPNA REŠITEV 4.1 Nadgradnja uvodnega predavanja 4.2 Prototip spletne učilnice 5 ZAKLJUČEK ZAHVALA LITERATURA 1 UVOD 2 NAMESTITEV STREŽNIKA 3 KONFIGURACIJA STREŽNIKA 3.1 Ustvarjanje uporabnikov in skupin Če želimo, da bodo vsi učitelji in dijaki lahko dostopali do storitve, moramo za vse ustvariti uporabniška imena in gesla. To storimo preko enostavnega vmesnika (Slika 4). 3.2 Ustvarjanje odložišča 4 DOSTOP IN UPORABA 4.1 Dostop do odložišča 4.2 Delo v odložišču 5 ZAKLJUČEK VIRI 1 UVOD 2 PROBLEMSKO STANJE 3 PREDSTAVITEV GLAVNIH PONUDNIKOV 4 PREGLED IN OCENA BREZPLAČNE PONUDBE SPLETNIH STORITEV 5 PREGLED IN OCENA PLAČLJIVE PONUDBE SPLETNIH STORITEV 6 KONČNA OCENA IN PREGLED BREZPLAČNIH IN PLAČLJIVIH SPLETNIH STORITEV 7 ZAKLJUČEK VIRI 1 UVOD 2 ZNAČILNOSTI UČENCA 3 IZOBRAŽEVANJE NA DALJAVO 3.1 Usvajanje in uporaba spletnih orodij 3.1.2 Spletna učilnica 3.1.3 Skype 3.2 Ure dodatne strokovne pomoči preko spleta 4 VEŠČINE VZGOJE NA DALJAVO – POMOČ IN SVETOVANJE STARŠEM 5 ZAKLJUČEK REFERENCE 1 UVOD 2 QUIZLET 3 USTVARJANJE NALOG 4 AKTIVNOSTI ZNOTRAJ NALOG 4.1 Zavihek 'Flashcards' 4.2 Zavihek 'Learn' 4.3 Zavihek 'Write' 4.4 Zavihek 'Spell' 4.5 Zavihek 'Test' 4.6 Igri za utrjevanje znanja 4.7 Quizlet Live 5 PREDNOSTI QUIZLETA 6 ZAKLJUČEK VIR 1 UVOD 2 METODOLOGIJA 2.1 Opredelitev problema 2.2 Cilj 2.3 Predpostavke in omejitve 2.4 Predvidene metode raziskovanja 3 REZULTATI 4 DISKUSIJA 5 ZAKLJUČEK REFERENCE 1 UVOD 2 DELO NA SPLETU Dijaki: - razvijajo veščine dela v skupini in iskanja kompromisov za doseganje ciljev ter razvijajo ustvarjalnost in samoiniciativnost (elementi podjetnosti); - oblikujejo definicijo pojmov izum in odkritje; - ovrednotijo pomen izumov za človeka in zgodovinski razvoj; - argumentirajo, kakšno bi bilo njihovo življenje brez izumov; - predlagajo nove izume za zmanjšanje okoljske krize, izboljšanje udobja, reševanje življenj; - razvijajo občutljivost za zaznavanje aktualnih problemov in iščejo rešitve; LITERATURA IN VIRI [1] Johnson, M. New Roles for Educators. Fev. 2000. Dostopno 25. 6. 2018 na http://mff.org/edtech/article.taf?_function=detail&Content_uid1=290 [2] Levy, P. Cyberculture. (2000), Minnesotta, University of Minnesota press. [4] Šink, J. Prihodnost učitelja in šole. Dostopno 21. 7. 2017 http://www.frodx.com/2012/04/30/prihodnost-ucitelja-in-sole/ 2.1 Učenje na daljavo 1 UVOD  možnost večperspektivnega prikaza snovi (interaktivni način učenja),  poljubnosti prostora (posameznik se lahko uči na katerikoli lokaciji želi),  poljubnost hitrosti (posameznik izbira kako hitro oziroma počasi jemlje snov),  poljubnost časa (posameznik izbere čas učenja). Slika 1. V i-učbeniku so učenci spoznali zapis in izgovorjavo novega besedišča. (4( 12 - Index - G Blank Page Blank Page Blank Page Blank Page IS2020_Volume_H - HCI 02 - Naslovnica - notranja - H - TEMP 03 - Kolofon - H - TEMP 04, 05 - IS2020 - Predgovor & Odbori 07 - Kazalo - H 08 - Naslovnica podkonference - H 09 - Predgovor podkonference - H 10 - Programski odbor podkonference - H 01 - HCI-IS_2020_paper_1 Abstract 1 Introduction and Background 2 Methodology Mobile Application Data collection campaign 3 Mobile Ad Perception Modelling User ID-based model Personality-based model Predictive personality-based model 4 Discussion and Conclusion References 02 - HCI-IS_2020_paper_20 Abstract 1 Uvod 2 Državni proračun 2.1 Struktura proračuna 2.2 Dostopnost podatkov 2.3 Obstoječe vizualizacije 3 Interaktivna vizualizacija s Sankeyevim diagramom 3.1 Sankeyev diagram 3.2 Uporaba interakcije 3.3 Izdelava vizualizacije 3.4 Razprava 4 Zaključki Zahvala 03 - HCI-IS_2020_paper_25 Abstract 1 Introduction 2 MFVoice Architecture 3 The MFVoice NLU Service 3.1 Application View Context Processing 3.2 Intent Recognition 3.3 Entity Recognition 4 Testing 4.1 Laboratory Testing Set-up and Results 4.2 Real-life Testing Set-up and Results 5 Discussion 6 Conclusion Acknowledgments 04 - HCI-IS_2020_paper_4 05 - HCI-IS_2020_paper_11 Abstract 1 Introduction 2 Re-imagining music and the music interface 3 Design Scenarios 4 Conclusion References 06 - HCI-IS_2020_paper_23 07 - HCI-IS_2020_paper_3 Abstract 1 Uvod 2 Pregled področja 3 Opis sistema 4 Raziskava 5 Rezultati in razprava 6 Zaključek Literatura 08 - HCI-IS_2020_paper_14 09 - HCI-IS_2020_paper_15 Abstract 1 Introduction 2 System design 3 Prototype implementation Floor plane detection Point cloud processing RGB optimization Rendering 4 Prototype game 5 Conclusions References 10 - HCI-IS_2020_paper_18 Abstract 1 Uvod 1.1 Vrste anamorfoz 2 Motivacija 3 Sorodna dela 4 Oprema 5 Perspektivna anamorfoza na neravno površino 6 Rezultati in zaključek Zahvala 11 - HCI-IS_2020_paper_5 12 - HCI-IS_2020_paper_17 Abstract 1 Introduction 2 Recording and encoding 3 Reproducing the sound filed 4 The Ambisonics system in use 5 Acknowledgments References 13 - HCI-IS_2020_paper_10 Abstract 1 Introduction 2 Methods Study design Apparatus Participants Procedure Analysis 3 Results 4 Discussion 5 Conclusions Acknowledgments References 12 - Index - H Blank Page Blank Page Blank Page Blank Page 05 - HCI_IS_2020_Paper_Jordan_Nuwan (1).pdf Abstract 1 Introduction 2 Re-imagining music and the music interface 3 Design Scenarios 4 Conclusion References Blank Page 12 - Index - All 12 - Index - Dodatek - All Blank Page Blank Page Blank Page